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A Quick Tour of Tech for Early-Career Professionals in Scholarly Communications
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A Quick Tour of Tech for Early-Career Professionals in Scholarly Communications
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REBECCA BENNER: Thank you and welcome to today's SSP Early Career Subcommittee Webinar, A Quick Tour of Tech for Early-Careers Professionals. We are very pleased that you could join us today. My name is Rebecca Benner. And I am a member of the SSP Early-Career Subcommittee. I have just a few housekeeping items to review before we get started. Your phone will be muted automatically in consideration of our presenters and your fellow webinar participants.
REBECCA BENNER: This one hour session will be recorded and posted on the SSP website 60 days following today's broadcast. If you have questions for the panelists or experience technical issues during the webinar, please use the question box to the right of your screen. s will be compiled for the presenters at the end of the webinar. It is now my pleasure to introduce our moderator today Jeff Froustet.
REBECCA BENNER: Jeff is a data administrator for the American Society of Civil Engineers, where he helps manage the use and distribution of publication metadata. Jeff over to you.
JEFF FROUSTET: Thanks Rebecca. It's my pleasure to moderate and introduce the speakers for today's webinar. Our speakers come from different roles, and enterprises, and scholarly publishing. Our first speaker today is Allison Belan. Allison is the director for Strategic Innovation and Services at Duke University Press. She's also the director of the Scholarly Publishing Collective, an initiative that provides infrastructure services such as hosting and digital fulfillment to nonprofit journal publishers and scholarly societies.
JEFF FROUSTET: Our second speaker is Melissa Harrison. Melissa is head of Production Operations at eLife. And then she has over 20 years of experience in STEM publishing. She is chair of JATS4R, a board member of Crossref, and has also contributed to the community via FORCE11 working groups, JATS4R recommendations, and other initiatives and working groups. Our third speaker today is Andrew Robinson.
JEFF FROUSTET: Andrew has more than 30 years of experience in the areas of content platforms, processing, and delivery. As principal consultant at Copyright Clearance Center, Andrew works with clients to drive innovation in their content operations and the transformation of capability through the optimal use of technology to fit their unique business strategy.
JEFF FROUSTET: And our fourth speaker today is Dr. Chhavi Chauhan. Dr. Chauhan works as director for Scientific Outreach at the American Society for Investigative Pathology and is director of the Continuing Medical Education Program at the Journal of Molecular Diagnostics. She's one of the leaders of the Women in AI Ethics collective and is an expert at the AI Policy Exchange. She's a biomedical researcher, and expert scholarly communicator, and a sought after mentor in the fields of scientific research, scholarly publishing, and AI ethics, especially for women and minorities.
JEFF FROUSTET: Thank you very much to the speakers for participating today. I'll share my screen now. All right. Apologies everyone. Housekeeping.
JEFF FROUSTET: As an introduction, I wanted to frame technology as something that supports the linear flow of scholarly communications. Whether it's a book or a journal article, publications are generally built up. There are things that progress through departments, like acquisitions, editorial, production, and marketing. I wanted to start off thinking how tech, like publishing staff, are organized to meet the needs of those departments.
JEFF FROUSTET: If we think of tech in this way as technology by stage of publication, we can think of some of the larger classes of tech that are more unique to each stage. Asset and title management systems are going to be used as a new project is being developed. Peer review systems enable editorial to coordinate with editors and peer reviewers. Production management systems allow staff to perform and track the many tasks that are associated with manuscript finalization.
JEFF FROUSTET: Marketing can use content management systems and asset distribution systems to reach your audience. In this way, tech is a tool. It's something that enables us to do our jobs. And like staff, it can be tailored to very different parts of the publishing process. But as you pull on that thread, as you think about the tools that editorial uses and how they might contrast with the tools that marketing uses, overlaps become clear.
JEFF FROUSTET: You find that it's not just editorial using workflow management systems. And it's not just marketing who are using analytics platforms. The discrete bins of tech become more of a pool with overlapping activity between departments. And when you get down to the level of file formats, the types of files we see on a regular basis and scholarly communications, XML, CSV, XLSX, you find that just about every stage of publication is involved.
JEFF FROUSTET: Every department is using Word and Excel to record and share information in some way. Every department needs to track task progress somehow. So technology relates to areas of operation and professional development in different ways. It influences how products are brought to market, how they're stored and distributed. Technology can be a disruptive force that upends product lines.
JEFF FROUSTET: It's the subject that does something to areas of scholarly publishing that the speakers are addressing today, broadly speaking, skill sets, production, content consumption, and governance. But that relationship can also be bidirectional, where these areas of focus can affect technology. Developing new skills can enable new ways of using existing technology. New product lines or content formats can make use of technology in new ways.
JEFF FROUSTET: Governance policies can influence how we use or don't use technology. The purpose of today's webinar is, among other things, to demystify industry technologies and to provide high level overview of tech that's established in publishing workflows, as well as tech that's new to the industry and still emerging. With that, I will hand things over to our first speaker Alison Belan.
JEFF FROUSTET: Alison.
ALLISON BELAN: Thank you Jeff. And my thanks to the panel organizers for inviting me and this opportunity to talk with everybody today. I'll get my screen shared. Is everybody seeing my slide--
JEFF FROUSTET: Yeah.
ALLISON BELAN: --deck? Great. Thank you. So my name is Alison Belan. And I'm at Duke University Press. And while I started off as a journals production manager, I have wound up in senior leadership where I manage a team of business analysts, project managers, who are responsible for our core enterprise technology systems.
ALLISON BELAN: And then I also manage our IT team. So I am a publishing professional who morphed into a technologist somewhere along the way. So something that I want to get across really clearly early on is that publishing is technology. These are not two separate things. And I've shared here some of the iconic examples of technology that get included in history lessons about technology.
ALLISON BELAN: These are all examples of knowledge dissemination technologies, writing, the printing press, the internet. And I want to highlight this because I really want to drive home that every role in every sector of scholarly publishing is an opportunity to build technological knowledge, skills, and experience. As Jeff showed, there isn't any segment of the publishing disciplines that doesn't intersect with technology these days.
ALLISON BELAN: And also to echo what Jeff said, because it's really important, is that to be successful as a technologist you need to understand the proper role of technology. It is an enabler. It is a tool. It is not a solution in and of itself. So just as Stone Age technology brought people chisels. A chisel without a vision is just a rock.
ALLISON BELAN: And so technology can't substitute for knowing what the goal is, what the business context is, and why you're working toward that goal. And I think that that means that you can't really separate learning the technical skills from the process of learning about the whole endeavor, which makes your entire career in scholarly publishing a chance to acquire technology skills. And so, I think if you approach your career that way the toolkit metaphor is pretty helpful.
ALLISON BELAN: Rarely does a craftsperson enter a trade with a full and complete toolkit. They acquire those tools over time. So if you're in your early stages of career, you're at a perfect moment to set about building this toolkit that hopefully will serve you throughout your entire career arc. And your opportunities to build that kit are each new project you participate in, each new role you assume within scholarly publishing, each new initiative that you get to intersect with.
ALLISON BELAN: And another great thing about scholarly publishing and technology in it is that these technologies are very specific to our incredibly specific context. Which means that no matter what you studied and come into this industry with, the technology skills are best acquired on the job and are readily acquired on the job. So I'm going to start with the first portion of your toolkit. And it's a fuzzy portion.
ALLISON BELAN: And that's attitudes. So these are sort of behavioral stances that I think will help you build and navigate a career as a technologist. The first one is to engage. When you engage with new technology, engage it at the conceptual level. Because the software will change, but the underlying concepts probably won't.
ALLISON BELAN: And I'm just going to take a quick example like project management software. If you use Asana, if the first project management tool you use is Asana, and then somebody-- your organization shifts to Smartsheet, you're still trying to manage projects. And these are just two different approaches to managing them. My next piece of advice is to seek the problem first, never start with the solution.
ALLISON BELAN: And when you are looking at the problem, you want to ask just a lot of questions to the point that you become super annoying to all of your colleagues. And so the question is what problem are you trying to solve. Why are you trying to solve it? Why is it even a problem? What are all the different ways that problem could be solved? What are the relative benefits and drawbacks of each solution that you've come up with?
ALLISON BELAN: And what external factors limit or expand the solution set? I call this coming to love the problem. It's really, really helpful to understand the supporting infrastructure that undergirds publishing, scholarly publishing, scholarly communications, and the technology. And these things intersect. So you want to understand the standards that shape both the technology you might be dealing with and the industry that you're working in.
ALLISON BELAN: That means learning protocols. What HTTP? What is FTP? What are they good for? Another thing that's really helpful that I'll talk about later is all of this technology comes to us, or a lot of it comes to us in the form of software that somebody else has written then given to us or that we have worked with vendors to build to meet our needs.
ALLISON BELAN: Understanding software design, not necessarily being able to do it, but understanding how software is architected can be really helpful. And finally, and I think most importantly, cultivating an attitude of curiosity, flexibility, and adaptability is really critical because again, the software is going to change and new technologies will emerge. So you always have to be ready to learn, embrace, and then jettison that thing you spent so much time learning because there's something new to focus on and you have to restart.
ALLISON BELAN: So if I look-- if I think more about what are the specific skill sets you might want to investigate and acquire, I've grouped them into these categories of data management, data literacy, structured content and metadata, which Melissa next is going to talk a lot about, core software concepts, and digital marketing. And in each area, I've; identified some tools that can be entry points and then rungs up the complexity ladder for building your skill sets.
ALLISON BELAN: So when it comes to data management honestly there's no better tool than a spreadsheet. Get into Excel. Start putting data in it and trying to do things with it. Take classes in this. And then that might lead you to recognize its limits and then lead you to a relational database like Microsoft Access. And the next step from there is enterprise level data management with SQL.
ALLISON BELAN: But also recognize-- if you work with the core data and tools like this, you'll start to understand how data driven applications that you use every day. Like these title management databases or the peer review systems are driven and built in managed data. Data literacy, again your best friend is a spreadsheet and it's charting tools for getting familiar with some of the basic concepts of how to make sense out of data.
ALLISON BELAN: And then you can move up into tools like Tableau for data visualization, and business data analytics tools like Power BI. Structured content and metadata is what drives our entire endeavor. It makes it possible for us to exchange this knowledge and information we're bringing into the world with each other and with the scholarly research world. Some really easy entry points to that are HTML5, which is actually XML, and starting to play with that.
ALLISON BELAN: And then you can get into XML. But what-- again I'm going to go back to the fact that our context is incredibly specific. So it's not just about XML. It's about the specific dominant forms of XML, specifications of XML, that we play with like JATS for journals and BITS for books. But also other formats for exchanging metadata, like ONIX and MARC, that are more book-centric.
ALLISON BELAN: I meant-- I talked before about core software concepts. So I won't spend a lot of time there. But the basic one to really understand is the fundamental separation in software usually of the data from the business logic. That's what somebody goes in and writes code to tell the system what to do with the data, to the display. Separation of those three layers. And then finally, an area that is just really interesting in terms of technology is what I'm grouping broadly as digital marketing.
ALLISON BELAN: Digital marketing is really all about the data and the specialized tools to understand and act on that data. So understanding how Google Analytics works and how to use it. Other analytics programs include Adobe Analytics. Social media management and the analytics, so tools like Hootsuite and TweetDeck. The concepts-- the UX concepts of personas and A/B testing, and how to use heat maps.
ALLISON BELAN: So I'm just throwing a lot of stuff out there in case something grabs your ear and your interest and you want to go looking for it later. And then finally, the next toolkit is kind of a metalayer. So an organization also needs to have people who manage the application of technology within that organization. Technology and skilled technologists are not enough for success.
ALLISON BELAN: So several disciplines that are highlighted here are ones that you may be interested in investigating as you gain industry experience and technical skills. Business analysts are the people who both understand the business and the technology at hand and figure out how to apply that technology to the business problem or opportunity. Project management is keeping the wheels on everything in budget, everything on time.
ALLISON BELAN: Vendor management, because so much of this technology now comes to us through partners out beyond our publishing organization's four walls. And then compliance, when you're dealing with data and technology, you're dealing with especially privacy but also often credit card banking and PCI compliance. So really becoming familiar with what forms of compliance and legal standards you have to be familiar with.
ALLISON BELAN: So the takeaways I will leave you with are you come to technology through any aspect of publishing, scholarly publishing, and you can go into any aspect of scholarly publishing through technology, especially if you cultivate those foundational attitudes and skills to become and stay technology0fluent. And I really want to encourage you to learn from every experience and seek the connection between those experiences.
ALLISON BELAN: What was common about them? How did they build on each other? Become a problem seeker. And then finally, position yourself for success in the organization by being able-- by understanding and being able to convey to the organization what technology can and cannot solve. Because when you're realistic, you can be successful.
ALLISON BELAN: And that is it. Thank you. And happy to pass it on back to Jeff.
JEFF FROUSTET: Thank you, Allison That was fantastic. I really-- It really resonates with me the focus on the concept behind some of these classes of technologies. If you can develop proficiency in something like Asana or Smartsheets, that's great. But perhaps even more important is to nail down the core, the foundation of it. We know-- What does this product class do? How does it enable us to do something?
JEFF FROUSTET: So next we'll go to Melissa Harrison from eLife.
MELISSA HARRISON: Hi there. So Yeah. Thank you Allison. It's great to follow you because there are so many different things in there that resonate as well with kind of what I do. So I want to talk a little bit about production. Which is often-- it can sometimes feel like you're the forgotten part. Or people don't quite understand it that much.
MELISSA HARRISON: And as Allison was saying, there are so many different aspects of production as well as many of the other kind of different areas that we work on. So production what do we actually do? Quite a lot. So I've started with key take home messages. So in the sense-- whenever I advertise for roles for my team, I've stopped using the word production in the advert and in the job title, because I get a lot of people think that we're talking about film-making.
MELISSA HARRISON: And in publishing, that's not what production is. It's something quite different. But I still find it really exciting. So one of the key things is that the metadata is the queen/king of what we're doing. So even though we're looking after all the content and all the output, it's the key components and the small pieces of content that's tagged appropriately, which is getting further reach and getting things further on.
MELISSA HARRISON: And to think of the semantics of the content, not of the display. So I have lots of experience where-- And I've done it myself, where I just used to think about how things looked on the PDF and not the semantic meaning or the understanding of what was going on underneath. And that's the thing. So where Allison's talked about things shifting on, the PDF is not the product anymore for journal, scholarly publishing.
MELISSA HARRISON: Many of our authors will still want their pretty typeset PDF. But that's not the thing that is going to get them the reach. Also thinking of the future, so in the sense it's a similar thing, not how it looks on the PDF but the semantics underlying it and the information that's there, and how that's going to get moved along in the pipeline and going to different people. That's the key.
MELISSA HARRISON: And also pointy brackets are not that scary. So as you can see from the little example there, it's quite clear. Like it's a simple one, but that's a bunch of keywords. But it's semantically tagged so that that information can go elsewhere and it can be read by people and machines. And I think that's one of the key things, is that a lot of our-- not our most important reader, but a massive reader for us now is the machines.
MELISSA HARRISON: And that's pretty key. So just-- My background is in journals. I've worked on books a little bit, but it's mainly journals. So the journal publishing workflow. This is how it's been for many, many years. It's changing. I know my own organization is trying to change the way journal publishing is working. But generally speaking, you've got peer review.
MELISSA HARRISON: You've got the peer review system there. And there are some amazing peer review systems that are technology-based. And they've had to grow and grow to look after the masses of submissions, the editors, and reviewers, evaluation, and all the things that are going on in the peer review process. And then you've got conversion and author proofing. That's a stage that I look after in production, converting whatever the authors provided when it's accepted into PDF, XML, other formats.
MELISSA HARRISON: You've got copy editing. You've got to process that content so it's available. Now the next part-- I've got publication and beyond. So as Allison mentioned, there are so many different things that are going on. There are so many different access, ways you can get into publishing. There's data analytics.
MELISSA HARRISON: There's downstream deliverables. There's so many different things that are happening to your content and what's going on afterwards. So I don't even know what it's called now. We've got hosting and display. I look after bits of that but so does a website service. And downstream deliverables, where I work, I'm looking after that. But some different organizations, it's sliced and diced differently.
MELISSA HARRISON: And some of the downstream deliverables, I don't look after but some do others. So just to say, there's flexibility there but there's options and things that you can do to get involved. And as Allison said, one of the key things is just to be curious to know what's going on, to look at all the different things that are happening, and talk to your peers in other parts of the group.
MELISSA HARRISON: So production, it's not just the jam in the middle of the sandwich. So the way I've always approached it is by looking downstream and upstream. So rather than production getting instructions from the editorial group saying, OK, we've got this new piece of content that you've got to process through the system. Oh we're doing this differently now.
MELISSA HARRISON: This is what's coming out of the system. There's no new policies. Things are going on. You've got to think about those things and how you can apply them in your area. And maybe you've got ideas within like the XML that is key that people in the editorial team might not have thought about. And also for downstream, so it's just thinking, not just I'm getting this stuff from someone else, I've got to process it and push it on.
MELISSA HARRISON: How can you extend and think about what's happening beforehand and afterwards as well? How will it look on your site? That's quite often probably where you'll be checking. But what about elsewhere? Where is that your content going to? Where is it being hosted by somewhere else? Who else needs the information to index your articles? And what can you do to improve all of these things?
MELISSA HARRISON: So in my opinion, XML is where the magic is. It's structured-- And I'm no XML expert. But I just believe in the power of it. And I enjoy working on things like JATS4R and working groups that are taking policies and kind of age-old ways of how content is being tagged and trying to come together with standards that kind of work across corpus so that meta analysis can happen and more can be done with the content across different publishing groups.
MELISSA HARRISON: But again from a human reader, a PDF and a website, it looks pretty. But your website and your PDF is not enough anymore. And it's got to be discovered and go elsewhere and further on. And like I said so I think the structure that you get from XML allows you to transport it to other places, convert it more easily. And it really is the kind of semantics of the content that helped with that.
MELISSA HARRISON: So XML stands for extensible markup language. And it basically defines a set of rules for encoding a document. So it is both for humans to be able to read, also the machines which are kind of the key area. And as Allison mentioned, JATS is a standard that a lot of-- most journal publishers use now. And as content, and as we move across, as things change, so as open access become more important.
MELISSA HARRISON: And like for instance, who's funding the publishing, who's funding the research, all of these sorts of things have become more important. And they need to be encoded in a way so that more and more-- so when you can send that information, the upstream, downstream, all over the place, and everybody knows. And machines can find out who funded that content more easily.
MELISSA HARRISON: So there's an example of how that can be marked up in the XML. It can be used within your own system and to store your content, but also to transmit it and also to convert to display it. So just to give an example as well of downstream deliverables-- I am on the Crossref board. But again with Crossref, with eLife, we send as much of our metadata to them as possible.
MELISSA HARRISON: And their metadata APIs are used by so many different people now. So the more you can send-- So it's not just about registering your DOI and that going to Crossref. The more other information that can be sent, it goes into their APIs. And it goes to all these end users. So I've got a whole big long list there.
MELISSA HARRISON: And then even the top one, 3,000 libraries are using it. I haven't followed on the dots, but you know-- and that that's the key thing, like I would say now is that your website is great but it's all these other places where your content can go to. So I would be remiss working for eLife to not mention Open Access and Open Science. But again-- And these are things that if you're curious and you're looking into things that are going on in the industry-- So the funder registry, I4OC, these and I4OA, they're very linked to Crossref but it's about open access of these content and for them to be tagged appropriately, so that then they can be moved around the system and machines and people can find out more and more.
MELISSA HARRISON: I've been very involved in the fair principles. So again, for-- especially within science, if the software and the data that supports the research is reproducible and it can be found, that helps build on all the things we're working on. So again, it's publishing. But the content that we're publishing and the scientific endeavor that we're supporting, the more we can do to make it reproducible and fair, and all these things, helps.
MELISSA HARRISON: Credit, another is a taxonomy that is being promoted that kind of allows authors to indicate what they contributed to the research more. is identifies metadata-- I could go on. There's loads of different organizations and things going on. And it's quite easy to find out by Googling and getting involved.
MELISSA HARRISON: A bit like JATS4R, we're desperate for people to help and to get involved. And a lot of these, like the links I've got here, it's voluntary work. So if you have the time and you can get involved, then do it. Because it will help with your career as well. So I won't go through this list because I know I've run over time. But much as Allison said, it's a case of being curious.
MELISSA HARRISON: And nobody is born knowing this stuff. We all learn it as we go. Thanks.
JEFF FROUSTET: Thank you so much, Melissa. That was fantastic. It's really eye-opening, this focus on XML and structured content. I think, understandably, we have a tendency to focus on the PDF, the final product that gets in the hands of a user, the kind of payload. But just as important nowadays, perhaps more important in certain contexts, is the XML. That's what really drives the discoverability.
JEFF FROUSTET: It's how we structure our content. It's how we transmit it from one organization to the other. And in some instances metadata is just as valuable as the full text. We'll next turn things over to Andrew Robinson of Copyright Clearance Center.
ANDREW ROBINSON: Thank you Jeff. And great presentations from Allison and Melissa. I'm going to really try hard to build on what they've been saying and hope I can find a way to be complementary to what's gone before. So I'm absolutely delighted, honored to be here. And hopefully, I can share some useful information with you. If we consider open access as a business model disruption-- or please consider open access as business model disruption.
ANDREW ROBINSON: What do we mean by that? If you're from an organization that is earning its revenues from subscriptions and everything's been working through from subscription-based method and we now move to open access, then everything is turned on its head. Everything is different. It affects the whole organization, the whole way of working.
ANDREW ROBINSON: All the systems, the processes, the finance reporting, everything's changed. And even if you're from a pure open access organization, you're doing OA from the start, and there's still changes in the marketplace that affect your business. And we need to be alive to those. But of course, you still, as Allison said, you still got your content to produce, the revenue to earn, a collective standards to maintain.
ANDREW ROBINSON: It's really important. But with higher access levels and the changing landscape technology-- changing technology landscape, the ability to do more things, the demands of content and media consumption continue to evolve. And consumers can change their expectations as well. So the changes that are taking place are that there's more models for funding are taking place. More challenges happening.
ANDREW ROBINSON: Authors are expecting simplified workflows. And institutions are ever demanding of more data, clearer reporting, and the ability to have transparency and insight into the data. So if we look at the customer and look at the downstream use of the content, then I think there are a number of areas that are worthy of considering. And so if we start by saying, well, how do people discover content?
ANDREW ROBINSON: How do you find the articles you want to read? And maybe you're used to subscribing to journals. And these are known and respected to you. And does the editor, effectively the editorial, picks from the content you want to see? But now, of course, we're now in an open access world. And more content is produced in more places. It's deposited in many different areas. So how do people find the content that they're after?
ANDREW ROBINSON: So maybe people start on a project. There's a new project taking place in a research organization or an institution. And you have the tools that are made available to you. There's the specialist libraries. There's specific locations. So you might be doing your-- starting your searches for the content on these larger systems, using content that may have been purchased for you.
ANDREW ROBINSON: And you need to share and manage that content according to whatever licenses and restrictions that are available. But you're also searching outside that. Maybe some of the tools you're able to use are semantic based. And you can apply taxonomies and ontologies to help you search and find things in a better way. Perhaps you have recommendations from other people that have helped you identify the things for you.
ANDREW ROBINSON: Or maybe the recommendations are coming from the search profiles that you've set. You set up, alerts that deliver the content to you. Or perhaps when you're searching, you have the tools that say, hey somebody like you who's been looking at this content, are you also interested in this. Twitter is a tremendous source of discovery as well. I certainly, for the last 18 months, finding all my recommendations for looking at COVID related content from Twitter.
ANDREW ROBINSON: And that was certainly a new thing for me. Clearly also citations and bibliographies are also really good sources. Other tools that you can have or things like, I like this paper, I'm reading something that's really of interest to me, can I upload this into the search profile and say, find me more like this. These are great ways of finding things. And then there's just traditional browse by topics.
ANDREW ROBINSON: I'm not sure what I'm looking for, but I'm going to have a look and see if I can find something of interest. So the search actually covers a multitude of systems, and tools, and areas. And as publishers, you need to think about how you feed into that, how you make those work better. And I think some of the things that Melissa was talking about are really important.
ANDREW ROBINSON: This rich metadata and so on. So then we found our content in some shape or form, how do we read everything? Well that's most unlikely. People don't have the time. I had a conversation fairly recently with a large publisher who shared some insight which was really fascinating. And they were saying that actually people don't start where I might think.
ANDREW ROBINSON: You look at the title and the abstract. It's actually look at the conclusions. What's the findings that have come from this piece of research? Is it interesting? Is it applicable? And if it is, then I might go to the method and have a look at how the work was done. And is it again relevant?
ANDREW ROBINSON: And if that's appropriate, then I might go to the abstract to find out more about it and then maybe the whole paper. So actually-- and I think Melissa was talking about this as well. The way people look at, use, and consume content is really changing. Maybe they actually acquire the content and run some tools over them. This may be simple tools to help classify or make notes or whatever.
ANDREW ROBINSON: But then there are far more sophisticated than richer tool. So I'll come onto in a second. And then two people always want the article. What do we mean by the article anyway? There's often supplemental data or there's some models or the algorithms that are associated with the articles. People want these as well.
ANDREW ROBINSON: And they need to be able to apply them and use them in their own situations. So it might be that people want to access data through data feeds. And then there's the early advance warnings of new knowledge can come out through conference papers and posters. So again, it's not just articles. It's other types of content, which can include monographs, and books, and so on.
ANDREW ROBINSON: So I think the unit of information currency or knowledge currency of the article is also wider and perhaps not so clear. Maybe it used to be. And then when we go inside the content. Then there are elements in there that people might want to pick up and consume, And particularly into machines. So it could be that people want to pick up on the formulae or have machine readable methods that they can pick up and ingest and run into their machines.
ANDREW ROBINSON: That's particularly important in the areas of standards for example, where there could be test methods that people want to pick up and put into a machine to make sure that that machine is now conforming to that standard. But the principles can apply into other areas of content. Another challenge for publishers particularly I think is [INAUDIBLE] on consumer's content is which version of the article am I looking at.
ANDREW ROBINSON: Is it the preprints? Is it the author-accepted manuscript? Is it the version of record? What happens when these are updated? And again, for a publisher, I think trying to signpost, and message, and drive people to the version of record is really important, and providing some role there, and then connecting them. We can then move on and say, well actually beyond the individual articles and think about the application of more systematic tools and more systematic integration into processing engines that people want to ingest large bodies of content and run machine learning tools or deep learning tools on these to perhaps make new connections in content, or to try and create some predictions, or identify other connections in the content that are just not possible in reading smaller numbers of articles.
ANDREW ROBINSON: And some of the tools here can include semantic markup, and identification of entities. So those are tools that says we've identified components. It could be a drug that perhaps causes a side effect that's identified as B. So A can have an impact on B. It can be positive. It could be negative. It could be a solid. It could be a solution for it, whatever.
ANDREW ROBINSON: We can encode these. We can identify these. We can encode these and then we can pick them up and push them into tools such as knowledge graphs. And then within these knowledge graphs, we can then search on these and make other connections. And in fact, what we can do then with the knowledge graph is connect these to other data sets and other systems, and particularly repositories of public information or open information, whatever that happens to be.
ANDREW ROBINSON: And very quickly, you start to build up a new body of knowledge and new tooling that is way, way, way beyond what's been produced as the article, but that's still essential components of these systems. And then you can start to think of a situation where, well can I combine these tools, can I the search and find the discovery and the assessment and the markup and the extraction of knowledge. And start to think of a digital, perhaps a digital research assistant as a system for me that will go off and do my work for me and then bring it back.
ANDREW ROBINSON: So it's beyond a search alert. But think of search alert 2.0 or 3.0, or whatever it is. It's a tool that really helps me become much more effective. So then we come down to the added value. How, as a publisher, can we make these systems work, work better, work smarter? And again, I think Melissa talked a lot about rich metadata as being really essential. And I would say within that, very specifically, the application of IDs, Persistent IDs or PIDs, for absolutely everything anywhere, these are the glue that make things happen.
ANDREW ROBINSON: And I can't stress enough how useful they are. We also have other plug-ins and other useful tools. And there are many that are people are very, very familiar with. But just thinking about some of the innovation that's taking place, we can have tools that can assess an article maybe for its data quality, for its structural integrity, and its quality, and perhaps its reproducibility.
ANDREW ROBINSON: There are other tools that can actually go and have a look at the citation and follow citation links, and are these in favor, are they positive or negative citations, rather than just listing. So [INAUDIBLE] would be an example of the former. And [INAUDIBLE] is an example of the latter. As examples of Autograph, CCC, the organization I work for produces novel tools.
ANDREW ROBINSON: And we have an Autograph that has novel application. So if we move on to perhaps some tools-- some recommendations about how to apply the technology and innovation, I think I'm building it on very much, the kind of messages that Allison was saying. Essentially here, be clear about your objectives up front. Know what problem it is you're trying to solve.
ANDREW ROBINSON: What questions are you-- What's your question you're trying to answer? These are really, really important. And delivering technology, deliver in small increments and improve as you go. Essentially, when we're dealing with the systems, I'll be talking about here, and connecting data and sucking content in, you really need to understand your data sources. And the provenance and licensing is really, really important.
ANDREW ROBINSON: And as you scale up from pilot to production, it's absolutely essential that you have the ability to connect to feed, and receive the updates, and know what you're dealing with, and have this traceability back to the original content. Pilot to production can be harder than it looks actually. When producing a pilot, you often ignore the hard stuff. And then when you go into production, actually you got to make that hard stuff work.
ANDREW ROBINSON: And finally, I'd say, remember the network. What we're talking about here is content within a network setting. And the more you can do to make this network effect work adds power to the content you're producing and aids the users and the consumption of it. And then, just to very quickly finish off, at CCC we produce Open Access everywhere as [INAUDIBLE]..
ANDREW ROBINSON: Open access is an example where publishers have to know their customers and experiment with technology to drive value and innovate. And writing scientific communications underpins the open access transactions supporting complex pricing policies and agreements and multiple business models and automated workflows. And with a RESTful API, we can integrate this into the OA ecosystem, enabling automation and transparency.
ANDREW ROBINSON: And a little bit of a rush there. But I think I'll finish, hopefully, on time.
JEFF FROUSTET: Great. Thank you so much Andrew. That was great. The challenge of knowing your customer, how they consume, and what they consume. I think we have a tendency to think of an article as kind of this start to finish document, this product, that understandably, a lot of customers do want. But there are other customers, audiences, that value particular components of an article.
JEFF FROUSTET: To see it as not just a one thing but as a composite of other things. And so that there are entire business lines built around the consumption of the abstract, or references, or formula. And for our last speaker today, we'll go to now Dr. Chhavi Chauhan from the American Society for Investigative Pathology. Dr. Chauhan.
CHHAVI CHAUHAN: Thank you Jeff. Thanks, everyone. I'm honored to be in this company. And thank you SSP for the opportunity. Jeff gave a really nice introduction. But honestly, I am a passionate science nerd. I have been all my life. Almost a decade ago, I was introduced to scholarly publishing. And I became passionate about it and my journey with the scholarly publishing world began.
CHHAVI CHAUHAN: Around three years ago, I was introduced to artificial intelligence. And since then I have become passionate about AI ethics. So if my professional journey is any indication, no matter how technologically challenged you are, if you're passionate, you will succeed. So from my presentation, I really want you to take home two messages. And this has been discussed a lot by previous panelists as well.
CHHAVI CHAUHAN: First and foremost, just remember that change is the only constant. So instead of resisting change and holding on to our technology, I invite you to embrace change. Be aware of new technologies and integrate them in your workflows, to stay relevant and to stay current. And time and time again we hear this phrase, technology leads to disruption. So my second take home message for you is think of technology as an opportunity to innovate.
CHHAVI CHAUHAN: When technology leads to innovation, new avenues open up. And these are new opportunities for you to explore and take your career to new levels. So for the sake of simplicity, let's break down the scholarly publishing landscape into three. So this is content creation, content validation and curation, and content dissemination.
CHHAVI CHAUHAN: So you can imagine authors being in the content creation bucket, peer review systems and editorial offices or production staff being in the content validation and curation bucket. And then there are societies, publishers, libraries, now preprint servers, and also marketing, that helps with content dissemination. So I'm here today to talk about emerging technologies. So let's place some emerging technologies in the scholarly publishing landscape.
CHHAVI CHAUHAN: We have heard from other panelists about metadata. And we've been dealing with it for quite some time now. But in the recent past we have started seeing AI generated data. So for the ASIP flagship journal, The American Journal of Pathology, in 2019, we expanded the scope to include a topic category of AI and computational pathobiology. So I'll give you an example.
CHHAVI CHAUHAN: So we see content where authors have generated algorithms that do image analysis, for example, that can look at tumor sections to grade them. So we have published studies such as validating those algorithms. So it has been found that these algorithms perform better than in-training pathologists. But they're not as superior or as good or superior than a trained pathologist.
CHHAVI CHAUHAN: So now we're dealing with AI generated data. So we have to think our processes again how are we going to validate, and curate this content, and how we're going to disseminate it. And I'll come back to that in a little bit. In the editorial processes, lately we have seen a lot of integration of AI. But essentially it's at the level of robotic process automation.
CHHAVI CHAUHAN: So in the last six years in our own editorial office, we have switched three peer review platforms. We have a very dedicated and committed staff. And we are grateful for that to go through the motions with us. So essentially-- Now we are using Elsevier's or Aries' editorial management platform. So what robotic process automation is doing is freeing up the editorial staff from the mundane. For example, if they were sending-- editorial staff were sending out reminders to target reviewers, the robotic process is going to do it automatically to keep things on track.
CHHAVI CHAUHAN: I think Allison and also Andrew talked a little bit about this. And Jeff used it in his primer. In content dissemination one can focus on data driven marketing and data analytics. So when you're surfing Netflix, it gives you a recommendation about what you should see next. If you're buying on Amazon, it tells you, oh if you bought this, you may be interested in buying this. So similarly when you're browsing through some pages, looking at some content online, if you're looking at an article, you often get recommendations to similar related reading.
CHHAVI CHAUHAN: So that is data driven analytics and data driven marketing that's prompting you to look at this content. A lot of publishers are looking into this to expand their foothold. So organizations or publishers may have great foothold in one geography, so how they can now use very specific marketing techniques to maintain this customer base or to come up with new campaigns to explore new geographies.
CHHAVI CHAUHAN: A lot of publishers are looking into emerging areas. For example, a couple of years ago or last year, Springer came up with a title on AI ethics. So they saw a need for content to be published and an absence of a journal to showcase that content. There could be publishers who are seeking people to write on different avenues of different aspects of quantum computing, for example. So emerging technology is being used in content dissemination as well.
CHHAVI CHAUHAN: I'm giving here just a handful of examples. But there's so many. There's a whole industry that's been built upon these emerging technologies, where authors are being supported in how they can share the content with the publishers. They've been provided with services to check for English language, or grammar, or confront the needs of a particular publisher.
CHHAVI CHAUHAN: There are softwares and widgets available that show how content interacts with other published content and, of course, how this content can be disseminated. And each one of them use different aspects of AI. It could be natural language processing. It could be machine learning or just simple data regression models. As I mentioned earlier, I'm passionate about AI ethics. So time and time again, I think about the ethics of these emerging technologies and how they can be safely developed and safely deployed in the different aspects of scholarly publishing landscape.
CHHAVI CHAUHAN: So in content creation, especially I deal with medical journals. So I can give my own example. It has been-- Collaboration has been a challenge amongst folks to share their data. But now there are technologies such as blockchain that are available. Federated learning which essentially allows you to bring in the algorithm to your institute to do whatever you want to do with your data safely and privately, and then share the findings with your collaborators.
CHHAVI CHAUHAN: For content validation and curation, we have been using a lot of heuristic models, where an input is given to the machine to get to a particular output. And these algorithms work beautifully on training data sets. But often, these training data sets are not truly representative of the real world data. So there are algorithmic accountability teams in place to ensure that when these algorithms are used on real world data, they perform the way they are supposed to and then they are transparent and scalable.
CHHAVI CHAUHAN: And we're all familiar, especially in the COVID landscape, how much amount of misinformation that has been floating around. So as scholarly publishing professionals, as guardians of scholarly publishing, we have to contain the spread of this misinformation. So a lot of preprint servers have been using humans to analyze the articles that they're putting up on their preprint servers.
CHHAVI CHAUHAN: I know researchers are doing that. So people are not extrapolating the findings that are being disseminated prior to peer review. But activity has been checked on social media. And often, information is either labeled as challenging or to be challenged, or oftentimes taken off of social media. So with emerging technologies come emerging roles. So I would like you to focus a little bit on things that we may not have even been thinking about so far.
CHHAVI CHAUHAN: So we talked about AI generated data. And our journals are seeing that already. But in the near future, maybe in 5 or 10 years down the line, AI will be altering content where there could be poems. There could be articles. There could be books written by these machines. So how in the scholarly publishing landscape are we going to deal with that, data that is not authored by a human, but an AI.
CHHAVI CHAUHAN: A lot of ethics boards for algorithmic accountability need to be put into motion. So Elsevier has been on the forefront of putting an ethics board for algorithmic accountability. And these ethics boards are very, very diverse. So of course they need subject matter experts who may be data scientists or computer scientists. And scientists, they have knowledge of a particular language to design these algorithms.
CHHAVI CHAUHAN: But you also need other experts, subject matter experts, from the scholarly publishing landscape who understand what the processes are, what are the questions to be asked, what are the outcomes that need to be addressed. And of course, these ethics boards are a collection of diverse individuals from different data sets. So climbing up the scholarly publishing ladder is not that difficult. I invite you to pair a technology with a skill.
CHHAVI CHAUHAN: So focus on your strengths. And as it has been said already before, upskill constantly. And I would invite you to be hungry to look for new opportunities, not hold yourself back. And most importantly, just be present. So understand what your team does, what your contribution means to your team, how that fits into the goals and missions of your own company, and how that fits into the goals and missions of the whole landscape.
CHHAVI CHAUHAN: If you know those, you will be able to use any emerging technologies to benefit, and even think about the new technologies, how they can help you answer problems that have not even been answered by the currently available technologies. So I hope you all will embrace change and look at technology as a source of innovation. Thank you.
JEFF FROUSTET: Thank you Dr. Chauhan. That was great, the idea that change is a constant and we can't just relegate it as an afterthought, that we need to embrace it. There are market forces driving that change. And it's not just singular companies. No. It's entire industries dedicated to kind of driving that change. And I think now we'll have time for some Q&A. We're just about 3 minutes to the top of the hour.
JEFF FROUSTET:
REBECCA BENNER: Thanks Jeff. This is Rebecca Benner again. If any of our attendees would like to ask a question, the Q&A is open. While we wait for folks to ask a question, one thing I want to ask, we've had a lot of conversations in this hour about sort of continual learning and being hungry and just being curious. So could the panelists talk about how do you, as publishing professionals, stay ahead of new technologies, practically speaking.
REBECCA BENNER:
CHHAVI CHAUHAN: I could go first. And it's sort of building on what Allison had said before. So don't go explore technologies. Look at the problems at hand. So just be very aware of what are the questions that you're asking. And then just seek individuals. Like you may not be an expert in technology, but try to pair up with someone who understands the technology and understands your problem.
CHHAVI CHAUHAN: So you can collaborate with them to come have creative solutions.
ALLISON BELAN: I would echo that really. Mostly I come across new technologies very often, new standards or emerging standards, by recognizing a problem that's been existing in our workflow and thinking like there's got to be a solution to this and then just starting to Google. It's all very unmysterious just using common tools. But once I run across something I say, oh, what is that.
ALLISON BELAN: And then I can start diving in. I've also over the years-- I've really relied on webinars, and SSP conferences, and other industry conferences and offerings to jump start. So once I know something is something I should know more about, I try to find a resource where I can hear from experts in it, in addition to doing my own independent research and learning.
ALLISON BELAN: And then very often, it's coming from our technology partners, the vendors that supply our publishing platform or our peer review system. So those are some sources that I try to keep my ear to the ground with to guide sort of what is the next thing I need to know about.
ANDREW ROBINSON: I could have a go at trying to answer that question. It's a great question. I've never been ceased to be amazed at the amazing technology that's applied in publishing. It's awesome at times. I found myself once with one client-- I was talking about it because I'd understood very little about it. But the application of ontologies and mapping ontologies to people, places, events, and this organization was producing guidebooks.
ANDREW ROBINSON: And then how do we plug-in the guidebooks to connect to tube maps, to events, to what restaurants are nearby, and things like this. And then when you start to have these conversations, you think, yeah wouldn't it be great to do that. You then think how do we make that happen. How do you map? And what data do you surface within these? It's just incredible that the simple conversation, apparently simple conversations like that throw out some amazing tools, and technologies, and challenges, which are just fantastic.
ANDREW ROBINSON: And it just keeps happening. It's amazing.
MELISSA HARRISON: Yeah I don't have a huge amount to add from what everyone said. I agree with all those things. And I think also just kind of from what Andrew said as well, it's that idea of applying what you see going on elsewhere or how you think other things work to the day job, so to speak. And if you hear about something, Googling it, finding out more about it, and then kind of trying to apply that.
MELISSA HARRISON: I'd agree with that.
REBECCA BENNER: Great. Thanks everyone. A question from an attendee. How do you as publishing technologists push through the hype that comes with almost all new technologies? How to develop a sense of what any technology is capable of delivering versus the new loose ends, shifts in labor, potential new problems?
ALLISON BELAN: So I'll jump in. I think I-- there's a couple of immediate answers I have to this. One is that I am decidedly mid-career maybe. I don't know. Maybe even getting into later career. I'm not sure. So I have perspective. I've been through a lot of hype cycles at this point. So I've learned to recognize them or at least to recognize my reaction to a new technology of being like, oh this will solve everything, this is the Holy Grail.
ALLISON BELAN: So I've gained some healthy skepticism over the years. But probably I will also say that working in a resource constricted part of scholarly publishing-- So I'm at a university press that publishes books and journals in the humanities. We can't jump on every new technology that comes down the road. We don't have the human resources or the financial resources to really dive into AI in a serious way.
ALLISON BELAN: So there's a little bit of cooling off that naturally happens. And over time, it becomes-- So between that moment of like there's a new technology on the block and it's really exciting and let's go for it, and when we might actually be able to consider going for it. Some things have become clear, very often.
REBECCA BENNER: Thanks Allison. We have two other questions in the chat. So I'm going to-- The first one is, how do we get editors engage with new technologies and processes? I have some editors who aren't interested in online-only or using other measurement of quality, other than the impact factor. Who'd like to take that?
REBECCA BENNER:
CHHAVI CHAUHAN: I would say, if you find the answer let me know too. I think it's a constant battle we all face in the scholarly publishing world. But I think an engaged editorial board is important. And if you feel like your editors are not engaged enough and are not open to the new technology that can help them, or ease the burden on the authors who are the users, or make things available to our readers who are also the users or consumers, then there might be a need to include more engaged members in the editorial board.
CHHAVI CHAUHAN: Having said that, most publishers and most societies come up with resources that can help the editors get acquainted with new technology. I mentioned that we have gone over three peer review systems in the last six years or so. So that was a rough transition for our staff, as well as for our editors. But we tried to ease the pain for everyone by providing trainings and be open to answering their questions.
CHHAVI CHAUHAN: Be available from the staff side. And I'm sure-- They're volunteers and they would be happy to keep serving if they get the resources that they need to perform their responsibility.
REBECCA BENNER: Thank you so much. All right. And our final question for today is, just by sheer numbers, opportunities diminish as companies shift their resources to outsourcing and automation. What do you recommend for folks early in their career should or as opportunities diminish and competition increases?
ANDREW ROBINSON: I've-- Oh go on Melissa.
MELISSA HARRISON: Oh no. I was just going to say that like I understand that. Because the higher you go up the ladder, there are fewer opportunities, and like with outsourcing. But it's something that Allison mentioned early on, there were different threads. So you might not necessarily kind of be the technologist. But vendor management is a massive area. The more you outsource, you do need staff to manage those vendors.
MELISSA HARRISON: And so you can shift then. And there are different kind of opportunities there, when things like that happen. Sorry, Andrew. You go ahead.
ANDREW ROBINSON: No. I was going to say a similar thing. I think there's different opportunities. New opportunities apply. So whilst there is considerable automation, as somebody who puts automation in many places, the idea is that it frees people up to do higher value work. Sometimes we, as consultants say that, say things like that, and it doesn't always transpire. I realize that.
ANDREW ROBINSON: But it should create new opportunities. And as I was trying to say in my talk about added value, where can you add value, where can you add value. And I think that's a challenge. If you can find a way to add value to something, it makes it more worthwhile. And it benefits many more people and many more systems and ultimately is of use. There's always, always, always going to be an opportunity for those kinds of things.
ANDREW ROBINSON: I think.
CHHAVI CHAUHAN: Yeah. Continue to upskill as well. Because as new-- If there is outsourcing on automation, then that's your opportunity to learn something new.
ALLISON BELAN: Yeah. And I think that outsourcing puts an even greater demand on publishers to have in-house understanding of the technology. That doesn't necessarily mean you need to know how to code or you need to know how to write SQL. But you need to have some basic understanding, at the conceptual and infrastructural level, of what your contractors and vendors are doing in order to manage them, and in order to be sure that they're working in a way to achieve your goals.
ALLISON BELAN: So you still need those technical skills and that technical understanding. But it does move you more toward those disciplines that I mentioned, business analysis, project management, vendor management.
ANDREW ROBINSON: I'd like to add. Just, I think, critical thinking and being able to discern hype from reality is really an important skill. People can bring you things, and try to sell you things, and try to show you things. And you really need to try and see past some of the facades, and understand what's going on underneath and how you can make that work. Because it could be that somebody comes to you with an idea or an opportunity for something.
ANDREW ROBINSON: And you look at it and you go, well it doesn't work for me as you've described. But actually over here, it's a really good application that could really make a difference. And so I think the ability to assess, discern, apply, or reject is a critical skill, useful skill.
REBECCA BENNER: Wonderful. Well, thank you to our speakers for their time and engaging presentations. And thank you to our attendees for your participation in today's webinar. You will receive a webinar evaluation via email. And we encourage you to provide feedback and to help us determine topics for future webinars. Don't miss the next couple events on the SSP calendar, including Accessibility in Publishing on September 23rd, as well as our New Direction Seminar on October 6th and 7th.
REBECCA BENNER: Today's webinar was recorded. And all registrants will be sent a link to the recording when it is posted on the SSP website. This concludes our session today.
Segment:0 .
REBECCA BENNER: Thank you and welcome to today's SSP Early Career Subcommittee Webinar, A Quick Tour of Tech for Early-Careers Professionals. We are very pleased that you could join us today. My name is Rebecca Benner. And I am a member of the SSP Early-Career Subcommittee. I have just a few housekeeping items to review before we get started. Your phone will be muted automatically in consideration of our presenters and your fellow webinar participants.
REBECCA BENNER: This one hour session will be recorded and posted on the SSP website 60 days following today's broadcast. If you have questions for the panelists or experience technical issues during the webinar, please use the question box to the right of your screen. s will be compiled for the presenters at the end of the webinar. It is now my pleasure to introduce our moderator today Jeff Froustet.
REBECCA BENNER: Jeff is a data administrator for the American Society of Civil Engineers, where he helps manage the use and distribution of publication metadata. Jeff over to you.
JEFF FROUSTET: Thanks Rebecca. It's my pleasure to moderate and introduce the speakers for today's webinar. Our speakers come from different roles, and enterprises, and scholarly publishing. Our first speaker today is Allison Belan. Allison is the director for Strategic Innovation and Services at Duke University Press. She's also the director of the Scholarly Publishing Collective, an initiative that provides infrastructure services such as hosting and digital fulfillment to nonprofit journal publishers and scholarly societies.
JEFF FROUSTET: Our second speaker is Melissa Harrison. Melissa is head of Production Operations at eLife. And then she has over 20 years of experience in STEM publishing. She is chair of JATS4R, a board member of Crossref, and has also contributed to the community via FORCE11 working groups, JATS4R recommendations, and other initiatives and working groups. Our third speaker today is Andrew Robinson.
JEFF FROUSTET: Andrew has more than 30 years of experience in the areas of content platforms, processing, and delivery. As principal consultant at Copyright Clearance Center, Andrew works with clients to drive innovation in their content operations and the transformation of capability through the optimal use of technology to fit their unique business strategy.
JEFF FROUSTET: And our fourth speaker today is Dr. Chhavi Chauhan. Dr. Chauhan works as director for Scientific Outreach at the American Society for Investigative Pathology and is director of the Continuing Medical Education Program at the Journal of Molecular Diagnostics. She's one of the leaders of the Women in AI Ethics collective and is an expert at the AI Policy Exchange. She's a biomedical researcher, and expert scholarly communicator, and a sought after mentor in the fields of scientific research, scholarly publishing, and AI ethics, especially for women and minorities.
JEFF FROUSTET: Thank you very much to the speakers for participating today. I'll share my screen now. All right. Apologies everyone. Housekeeping.
JEFF FROUSTET: As an introduction, I wanted to frame technology as something that supports the linear flow of scholarly communications. Whether it's a book or a journal article, publications are generally built up. There are things that progress through departments, like acquisitions, editorial, production, and marketing. I wanted to start off thinking how tech, like publishing staff, are organized to meet the needs of those departments.
JEFF FROUSTET: If we think of tech in this way as technology by stage of publication, we can think of some of the larger classes of tech that are more unique to each stage. Asset and title management systems are going to be used as a new project is being developed. Peer review systems enable editorial to coordinate with editors and peer reviewers. Production management systems allow staff to perform and track the many tasks that are associated with manuscript finalization.
JEFF FROUSTET: Marketing can use content management systems and asset distribution systems to reach your audience. In this way, tech is a tool. It's something that enables us to do our jobs. And like staff, it can be tailored to very different parts of the publishing process. But as you pull on that thread, as you think about the tools that editorial uses and how they might contrast with the tools that marketing uses, overlaps become clear.
JEFF FROUSTET: You find that it's not just editorial using workflow management systems. And it's not just marketing who are using analytics platforms. The discrete bins of tech become more of a pool with overlapping activity between departments. And when you get down to the level of file formats, the types of files we see on a regular basis and scholarly communications, XML, CSV, XLSX, you find that just about every stage of publication is involved.
JEFF FROUSTET: Every department is using Word and Excel to record and share information in some way. Every department needs to track task progress somehow. So technology relates to areas of operation and professional development in different ways. It influences how products are brought to market, how they're stored and distributed. Technology can be a disruptive force that upends product lines.
JEFF FROUSTET: It's the subject that does something to areas of scholarly publishing that the speakers are addressing today, broadly speaking, skill sets, production, content consumption, and governance. But that relationship can also be bidirectional, where these areas of focus can affect technology. Developing new skills can enable new ways of using existing technology. New product lines or content formats can make use of technology in new ways.
JEFF FROUSTET: Governance policies can influence how we use or don't use technology. The purpose of today's webinar is, among other things, to demystify industry technologies and to provide high level overview of tech that's established in publishing workflows, as well as tech that's new to the industry and still emerging. With that, I will hand things over to our first speaker Alison Belan.
JEFF FROUSTET: Alison.
ALLISON BELAN: Thank you Jeff. And my thanks to the panel organizers for inviting me and this opportunity to talk with everybody today. I'll get my screen shared. Is everybody seeing my slide--
JEFF FROUSTET: Yeah.
ALLISON BELAN: --deck? Great. Thank you. So my name is Alison Belan. And I'm at Duke University Press. And while I started off as a journals production manager, I have wound up in senior leadership where I manage a team of business analysts, project managers, who are responsible for our core enterprise technology systems.
ALLISON BELAN: And then I also manage our IT team. So I am a publishing professional who morphed into a technologist somewhere along the way. So something that I want to get across really clearly early on is that publishing is technology. These are not two separate things. And I've shared here some of the iconic examples of technology that get included in history lessons about technology.
ALLISON BELAN: These are all examples of knowledge dissemination technologies, writing, the printing press, the internet. And I want to highlight this because I really want to drive home that every role in every sector of scholarly publishing is an opportunity to build technological knowledge, skills, and experience. As Jeff showed, there isn't any segment of the publishing disciplines that doesn't intersect with technology these days.
ALLISON BELAN: And also to echo what Jeff said, because it's really important, is that to be successful as a technologist you need to understand the proper role of technology. It is an enabler. It is a tool. It is not a solution in and of itself. So just as Stone Age technology brought people chisels. A chisel without a vision is just a rock.
ALLISON BELAN: And so technology can't substitute for knowing what the goal is, what the business context is, and why you're working toward that goal. And I think that that means that you can't really separate learning the technical skills from the process of learning about the whole endeavor, which makes your entire career in scholarly publishing a chance to acquire technology skills. And so, I think if you approach your career that way the toolkit metaphor is pretty helpful.
ALLISON BELAN: Rarely does a craftsperson enter a trade with a full and complete toolkit. They acquire those tools over time. So if you're in your early stages of career, you're at a perfect moment to set about building this toolkit that hopefully will serve you throughout your entire career arc. And your opportunities to build that kit are each new project you participate in, each new role you assume within scholarly publishing, each new initiative that you get to intersect with.
ALLISON BELAN: And another great thing about scholarly publishing and technology in it is that these technologies are very specific to our incredibly specific context. Which means that no matter what you studied and come into this industry with, the technology skills are best acquired on the job and are readily acquired on the job. So I'm going to start with the first portion of your toolkit. And it's a fuzzy portion.
ALLISON BELAN: And that's attitudes. So these are sort of behavioral stances that I think will help you build and navigate a career as a technologist. The first one is to engage. When you engage with new technology, engage it at the conceptual level. Because the software will change, but the underlying concepts probably won't.
ALLISON BELAN: And I'm just going to take a quick example like project management software. If you use Asana, if the first project management tool you use is Asana, and then somebody-- your organization shifts to Smartsheet, you're still trying to manage projects. And these are just two different approaches to managing them. My next piece of advice is to seek the problem first, never start with the solution.
ALLISON BELAN: And when you are looking at the problem, you want to ask just a lot of questions to the point that you become super annoying to all of your colleagues. And so the question is what problem are you trying to solve. Why are you trying to solve it? Why is it even a problem? What are all the different ways that problem could be solved? What are the relative benefits and drawbacks of each solution that you've come up with?
ALLISON BELAN: And what external factors limit or expand the solution set? I call this coming to love the problem. It's really, really helpful to understand the supporting infrastructure that undergirds publishing, scholarly publishing, scholarly communications, and the technology. And these things intersect. So you want to understand the standards that shape both the technology you might be dealing with and the industry that you're working in.
ALLISON BELAN: That means learning protocols. What HTTP? What is FTP? What are they good for? Another thing that's really helpful that I'll talk about later is all of this technology comes to us, or a lot of it comes to us in the form of software that somebody else has written then given to us or that we have worked with vendors to build to meet our needs.
ALLISON BELAN: Understanding software design, not necessarily being able to do it, but understanding how software is architected can be really helpful. And finally, and I think most importantly, cultivating an attitude of curiosity, flexibility, and adaptability is really critical because again, the software is going to change and new technologies will emerge. So you always have to be ready to learn, embrace, and then jettison that thing you spent so much time learning because there's something new to focus on and you have to restart.
ALLISON BELAN: So if I look-- if I think more about what are the specific skill sets you might want to investigate and acquire, I've grouped them into these categories of data management, data literacy, structured content and metadata, which Melissa next is going to talk a lot about, core software concepts, and digital marketing. And in each area, I've; identified some tools that can be entry points and then rungs up the complexity ladder for building your skill sets.
ALLISON BELAN: So when it comes to data management honestly there's no better tool than a spreadsheet. Get into Excel. Start putting data in it and trying to do things with it. Take classes in this. And then that might lead you to recognize its limits and then lead you to a relational database like Microsoft Access. And the next step from there is enterprise level data management with SQL.
ALLISON BELAN: But also recognize-- if you work with the core data and tools like this, you'll start to understand how data driven applications that you use every day. Like these title management databases or the peer review systems are driven and built in managed data. Data literacy, again your best friend is a spreadsheet and it's charting tools for getting familiar with some of the basic concepts of how to make sense out of data.
ALLISON BELAN: And then you can move up into tools like Tableau for data visualization, and business data analytics tools like Power BI. Structured content and metadata is what drives our entire endeavor. It makes it possible for us to exchange this knowledge and information we're bringing into the world with each other and with the scholarly research world. Some really easy entry points to that are HTML5, which is actually XML, and starting to play with that.
ALLISON BELAN: And then you can get into XML. But what-- again I'm going to go back to the fact that our context is incredibly specific. So it's not just about XML. It's about the specific dominant forms of XML, specifications of XML, that we play with like JATS for journals and BITS for books. But also other formats for exchanging metadata, like ONIX and MARC, that are more book-centric.
ALLISON BELAN: I meant-- I talked before about core software concepts. So I won't spend a lot of time there. But the basic one to really understand is the fundamental separation in software usually of the data from the business logic. That's what somebody goes in and writes code to tell the system what to do with the data, to the display. Separation of those three layers. And then finally, an area that is just really interesting in terms of technology is what I'm grouping broadly as digital marketing.
ALLISON BELAN: Digital marketing is really all about the data and the specialized tools to understand and act on that data. So understanding how Google Analytics works and how to use it. Other analytics programs include Adobe Analytics. Social media management and the analytics, so tools like Hootsuite and TweetDeck. The concepts-- the UX concepts of personas and A/B testing, and how to use heat maps.
ALLISON BELAN: So I'm just throwing a lot of stuff out there in case something grabs your ear and your interest and you want to go looking for it later. And then finally, the next toolkit is kind of a metalayer. So an organization also needs to have people who manage the application of technology within that organization. Technology and skilled technologists are not enough for success.
ALLISON BELAN: So several disciplines that are highlighted here are ones that you may be interested in investigating as you gain industry experience and technical skills. Business analysts are the people who both understand the business and the technology at hand and figure out how to apply that technology to the business problem or opportunity. Project management is keeping the wheels on everything in budget, everything on time.
ALLISON BELAN: Vendor management, because so much of this technology now comes to us through partners out beyond our publishing organization's four walls. And then compliance, when you're dealing with data and technology, you're dealing with especially privacy but also often credit card banking and PCI compliance. So really becoming familiar with what forms of compliance and legal standards you have to be familiar with.
ALLISON BELAN: So the takeaways I will leave you with are you come to technology through any aspect of publishing, scholarly publishing, and you can go into any aspect of scholarly publishing through technology, especially if you cultivate those foundational attitudes and skills to become and stay technology0fluent. And I really want to encourage you to learn from every experience and seek the connection between those experiences.
ALLISON BELAN: What was common about them? How did they build on each other? Become a problem seeker. And then finally, position yourself for success in the organization by being able-- by understanding and being able to convey to the organization what technology can and cannot solve. Because when you're realistic, you can be successful.
ALLISON BELAN: And that is it. Thank you. And happy to pass it on back to Jeff.
JEFF FROUSTET: Thank you, Allison That was fantastic. I really-- It really resonates with me the focus on the concept behind some of these classes of technologies. If you can develop proficiency in something like Asana or Smartsheets, that's great. But perhaps even more important is to nail down the core, the foundation of it. We know-- What does this product class do? How does it enable us to do something?
JEFF FROUSTET: So next we'll go to Melissa Harrison from eLife.
MELISSA HARRISON: Hi there. So Yeah. Thank you Allison. It's great to follow you because there are so many different things in there that resonate as well with kind of what I do. So I want to talk a little bit about production. Which is often-- it can sometimes feel like you're the forgotten part. Or people don't quite understand it that much.
MELISSA HARRISON: And as Allison was saying, there are so many different aspects of production as well as many of the other kind of different areas that we work on. So production what do we actually do? Quite a lot. So I've started with key take home messages. So in the sense-- whenever I advertise for roles for my team, I've stopped using the word production in the advert and in the job title, because I get a lot of people think that we're talking about film-making.
MELISSA HARRISON: And in publishing, that's not what production is. It's something quite different. But I still find it really exciting. So one of the key things is that the metadata is the queen/king of what we're doing. So even though we're looking after all the content and all the output, it's the key components and the small pieces of content that's tagged appropriately, which is getting further reach and getting things further on.
MELISSA HARRISON: And to think of the semantics of the content, not of the display. So I have lots of experience where-- And I've done it myself, where I just used to think about how things looked on the PDF and not the semantic meaning or the understanding of what was going on underneath. And that's the thing. So where Allison's talked about things shifting on, the PDF is not the product anymore for journal, scholarly publishing.
MELISSA HARRISON: Many of our authors will still want their pretty typeset PDF. But that's not the thing that is going to get them the reach. Also thinking of the future, so in the sense it's a similar thing, not how it looks on the PDF but the semantics underlying it and the information that's there, and how that's going to get moved along in the pipeline and going to different people. That's the key.
MELISSA HARRISON: And also pointy brackets are not that scary. So as you can see from the little example there, it's quite clear. Like it's a simple one, but that's a bunch of keywords. But it's semantically tagged so that that information can go elsewhere and it can be read by people and machines. And I think that's one of the key things, is that a lot of our-- not our most important reader, but a massive reader for us now is the machines.
MELISSA HARRISON: And that's pretty key. So just-- My background is in journals. I've worked on books a little bit, but it's mainly journals. So the journal publishing workflow. This is how it's been for many, many years. It's changing. I know my own organization is trying to change the way journal publishing is working. But generally speaking, you've got peer review.
MELISSA HARRISON: You've got the peer review system there. And there are some amazing peer review systems that are technology-based. And they've had to grow and grow to look after the masses of submissions, the editors, and reviewers, evaluation, and all the things that are going on in the peer review process. And then you've got conversion and author proofing. That's a stage that I look after in production, converting whatever the authors provided when it's accepted into PDF, XML, other formats.
MELISSA HARRISON: You've got copy editing. You've got to process that content so it's available. Now the next part-- I've got publication and beyond. So as Allison mentioned, there are so many different things that are going on. There are so many different access, ways you can get into publishing. There's data analytics.
MELISSA HARRISON: There's downstream deliverables. There's so many different things that are happening to your content and what's going on afterwards. So I don't even know what it's called now. We've got hosting and display. I look after bits of that but so does a website service. And downstream deliverables, where I work, I'm looking after that. But some different organizations, it's sliced and diced differently.
MELISSA HARRISON: And some of the downstream deliverables, I don't look after but some do others. So just to say, there's flexibility there but there's options and things that you can do to get involved. And as Allison said, one of the key things is just to be curious to know what's going on, to look at all the different things that are happening, and talk to your peers in other parts of the group.
MELISSA HARRISON: So production, it's not just the jam in the middle of the sandwich. So the way I've always approached it is by looking downstream and upstream. So rather than production getting instructions from the editorial group saying, OK, we've got this new piece of content that you've got to process through the system. Oh we're doing this differently now.
MELISSA HARRISON: This is what's coming out of the system. There's no new policies. Things are going on. You've got to think about those things and how you can apply them in your area. And maybe you've got ideas within like the XML that is key that people in the editorial team might not have thought about. And also for downstream, so it's just thinking, not just I'm getting this stuff from someone else, I've got to process it and push it on.
MELISSA HARRISON: How can you extend and think about what's happening beforehand and afterwards as well? How will it look on your site? That's quite often probably where you'll be checking. But what about elsewhere? Where is that your content going to? Where is it being hosted by somewhere else? Who else needs the information to index your articles? And what can you do to improve all of these things?
MELISSA HARRISON: So in my opinion, XML is where the magic is. It's structured-- And I'm no XML expert. But I just believe in the power of it. And I enjoy working on things like JATS4R and working groups that are taking policies and kind of age-old ways of how content is being tagged and trying to come together with standards that kind of work across corpus so that meta analysis can happen and more can be done with the content across different publishing groups.
MELISSA HARRISON: But again from a human reader, a PDF and a website, it looks pretty. But your website and your PDF is not enough anymore. And it's got to be discovered and go elsewhere and further on. And like I said so I think the structure that you get from XML allows you to transport it to other places, convert it more easily. And it really is the kind of semantics of the content that helped with that.
MELISSA HARRISON: So XML stands for extensible markup language. And it basically defines a set of rules for encoding a document. So it is both for humans to be able to read, also the machines which are kind of the key area. And as Allison mentioned, JATS is a standard that a lot of-- most journal publishers use now. And as content, and as we move across, as things change, so as open access become more important.
MELISSA HARRISON: And like for instance, who's funding the publishing, who's funding the research, all of these sorts of things have become more important. And they need to be encoded in a way so that more and more-- so when you can send that information, the upstream, downstream, all over the place, and everybody knows. And machines can find out who funded that content more easily.
MELISSA HARRISON: So there's an example of how that can be marked up in the XML. It can be used within your own system and to store your content, but also to transmit it and also to convert to display it. So just to give an example as well of downstream deliverables-- I am on the Crossref board. But again with Crossref, with eLife, we send as much of our metadata to them as possible.
MELISSA HARRISON: And their metadata APIs are used by so many different people now. So the more you can send-- So it's not just about registering your DOI and that going to Crossref. The more other information that can be sent, it goes into their APIs. And it goes to all these end users. So I've got a whole big long list there.
MELISSA HARRISON: And then even the top one, 3,000 libraries are using it. I haven't followed on the dots, but you know-- and that that's the key thing, like I would say now is that your website is great but it's all these other places where your content can go to. So I would be remiss working for eLife to not mention Open Access and Open Science. But again-- And these are things that if you're curious and you're looking into things that are going on in the industry-- So the funder registry, I4OC, these and I4OA, they're very linked to Crossref but it's about open access of these content and for them to be tagged appropriately, so that then they can be moved around the system and machines and people can find out more and more.
MELISSA HARRISON: I've been very involved in the fair principles. So again, for-- especially within science, if the software and the data that supports the research is reproducible and it can be found, that helps build on all the things we're working on. So again, it's publishing. But the content that we're publishing and the scientific endeavor that we're supporting, the more we can do to make it reproducible and fair, and all these things, helps.
MELISSA HARRISON: Credit, another is a taxonomy that is being promoted that kind of allows authors to indicate what they contributed to the research more. is identifies metadata-- I could go on. There's loads of different organizations and things going on. And it's quite easy to find out by Googling and getting involved.
MELISSA HARRISON: A bit like JATS4R, we're desperate for people to help and to get involved. And a lot of these, like the links I've got here, it's voluntary work. So if you have the time and you can get involved, then do it. Because it will help with your career as well. So I won't go through this list because I know I've run over time. But much as Allison said, it's a case of being curious.
MELISSA HARRISON: And nobody is born knowing this stuff. We all learn it as we go. Thanks.
JEFF FROUSTET: Thank you so much, Melissa. That was fantastic. It's really eye-opening, this focus on XML and structured content. I think, understandably, we have a tendency to focus on the PDF, the final product that gets in the hands of a user, the kind of payload. But just as important nowadays, perhaps more important in certain contexts, is the XML. That's what really drives the discoverability.
JEFF FROUSTET: It's how we structure our content. It's how we transmit it from one organization to the other. And in some instances metadata is just as valuable as the full text. We'll next turn things over to Andrew Robinson of Copyright Clearance Center.
ANDREW ROBINSON: Thank you Jeff. And great presentations from Allison and Melissa. I'm going to really try hard to build on what they've been saying and hope I can find a way to be complementary to what's gone before. So I'm absolutely delighted, honored to be here. And hopefully, I can share some useful information with you. If we consider open access as a business model disruption-- or please consider open access as business model disruption.
ANDREW ROBINSON: What do we mean by that? If you're from an organization that is earning its revenues from subscriptions and everything's been working through from subscription-based method and we now move to open access, then everything is turned on its head. Everything is different. It affects the whole organization, the whole way of working.
ANDREW ROBINSON: All the systems, the processes, the finance reporting, everything's changed. And even if you're from a pure open access organization, you're doing OA from the start, and there's still changes in the marketplace that affect your business. And we need to be alive to those. But of course, you still, as Allison said, you still got your content to produce, the revenue to earn, a collective standards to maintain.
ANDREW ROBINSON: It's really important. But with higher access levels and the changing landscape technology-- changing technology landscape, the ability to do more things, the demands of content and media consumption continue to evolve. And consumers can change their expectations as well. So the changes that are taking place are that there's more models for funding are taking place. More challenges happening.
ANDREW ROBINSON: Authors are expecting simplified workflows. And institutions are ever demanding of more data, clearer reporting, and the ability to have transparency and insight into the data. So if we look at the customer and look at the downstream use of the content, then I think there are a number of areas that are worthy of considering. And so if we start by saying, well, how do people discover content?
ANDREW ROBINSON: How do you find the articles you want to read? And maybe you're used to subscribing to journals. And these are known and respected to you. And does the editor, effectively the editorial, picks from the content you want to see? But now, of course, we're now in an open access world. And more content is produced in more places. It's deposited in many different areas. So how do people find the content that they're after?
ANDREW ROBINSON: So maybe people start on a project. There's a new project taking place in a research organization or an institution. And you have the tools that are made available to you. There's the specialist libraries. There's specific locations. So you might be doing your-- starting your searches for the content on these larger systems, using content that may have been purchased for you.
ANDREW ROBINSON: And you need to share and manage that content according to whatever licenses and restrictions that are available. But you're also searching outside that. Maybe some of the tools you're able to use are semantic based. And you can apply taxonomies and ontologies to help you search and find things in a better way. Perhaps you have recommendations from other people that have helped you identify the things for you.
ANDREW ROBINSON: Or maybe the recommendations are coming from the search profiles that you've set. You set up, alerts that deliver the content to you. Or perhaps when you're searching, you have the tools that say, hey somebody like you who's been looking at this content, are you also interested in this. Twitter is a tremendous source of discovery as well. I certainly, for the last 18 months, finding all my recommendations for looking at COVID related content from Twitter.
ANDREW ROBINSON: And that was certainly a new thing for me. Clearly also citations and bibliographies are also really good sources. Other tools that you can have or things like, I like this paper, I'm reading something that's really of interest to me, can I upload this into the search profile and say, find me more like this. These are great ways of finding things. And then there's just traditional browse by topics.
ANDREW ROBINSON: I'm not sure what I'm looking for, but I'm going to have a look and see if I can find something of interest. So the search actually covers a multitude of systems, and tools, and areas. And as publishers, you need to think about how you feed into that, how you make those work better. And I think some of the things that Melissa was talking about are really important.
ANDREW ROBINSON: This rich metadata and so on. So then we found our content in some shape or form, how do we read everything? Well that's most unlikely. People don't have the time. I had a conversation fairly recently with a large publisher who shared some insight which was really fascinating. And they were saying that actually people don't start where I might think.
ANDREW ROBINSON: You look at the title and the abstract. It's actually look at the conclusions. What's the findings that have come from this piece of research? Is it interesting? Is it applicable? And if it is, then I might go to the method and have a look at how the work was done. And is it again relevant?
ANDREW ROBINSON: And if that's appropriate, then I might go to the abstract to find out more about it and then maybe the whole paper. So actually-- and I think Melissa was talking about this as well. The way people look at, use, and consume content is really changing. Maybe they actually acquire the content and run some tools over them. This may be simple tools to help classify or make notes or whatever.
ANDREW ROBINSON: But then there are far more sophisticated than richer tool. So I'll come onto in a second. And then two people always want the article. What do we mean by the article anyway? There's often supplemental data or there's some models or the algorithms that are associated with the articles. People want these as well.
ANDREW ROBINSON: And they need to be able to apply them and use them in their own situations. So it might be that people want to access data through data feeds. And then there's the early advance warnings of new knowledge can come out through conference papers and posters. So again, it's not just articles. It's other types of content, which can include monographs, and books, and so on.
ANDREW ROBINSON: So I think the unit of information currency or knowledge currency of the article is also wider and perhaps not so clear. Maybe it used to be. And then when we go inside the content. Then there are elements in there that people might want to pick up and consume, And particularly into machines. So it could be that people want to pick up on the formulae or have machine readable methods that they can pick up and ingest and run into their machines.
ANDREW ROBINSON: That's particularly important in the areas of standards for example, where there could be test methods that people want to pick up and put into a machine to make sure that that machine is now conforming to that standard. But the principles can apply into other areas of content. Another challenge for publishers particularly I think is [INAUDIBLE] on consumer's content is which version of the article am I looking at.
ANDREW ROBINSON: Is it the preprints? Is it the author-accepted manuscript? Is it the version of record? What happens when these are updated? And again, for a publisher, I think trying to signpost, and message, and drive people to the version of record is really important, and providing some role there, and then connecting them. We can then move on and say, well actually beyond the individual articles and think about the application of more systematic tools and more systematic integration into processing engines that people want to ingest large bodies of content and run machine learning tools or deep learning tools on these to perhaps make new connections in content, or to try and create some predictions, or identify other connections in the content that are just not possible in reading smaller numbers of articles.
ANDREW ROBINSON: And some of the tools here can include semantic markup, and identification of entities. So those are tools that says we've identified components. It could be a drug that perhaps causes a side effect that's identified as B. So A can have an impact on B. It can be positive. It could be negative. It could be a solid. It could be a solution for it, whatever.
ANDREW ROBINSON: We can encode these. We can identify these. We can encode these and then we can pick them up and push them into tools such as knowledge graphs. And then within these knowledge graphs, we can then search on these and make other connections. And in fact, what we can do then with the knowledge graph is connect these to other data sets and other systems, and particularly repositories of public information or open information, whatever that happens to be.
ANDREW ROBINSON: And very quickly, you start to build up a new body of knowledge and new tooling that is way, way, way beyond what's been produced as the article, but that's still essential components of these systems. And then you can start to think of a situation where, well can I combine these tools, can I the search and find the discovery and the assessment and the markup and the extraction of knowledge. And start to think of a digital, perhaps a digital research assistant as a system for me that will go off and do my work for me and then bring it back.
ANDREW ROBINSON: So it's beyond a search alert. But think of search alert 2.0 or 3.0, or whatever it is. It's a tool that really helps me become much more effective. So then we come down to the added value. How, as a publisher, can we make these systems work, work better, work smarter? And again, I think Melissa talked a lot about rich metadata as being really essential. And I would say within that, very specifically, the application of IDs, Persistent IDs or PIDs, for absolutely everything anywhere, these are the glue that make things happen.
ANDREW ROBINSON: And I can't stress enough how useful they are. We also have other plug-ins and other useful tools. And there are many that are people are very, very familiar with. But just thinking about some of the innovation that's taking place, we can have tools that can assess an article maybe for its data quality, for its structural integrity, and its quality, and perhaps its reproducibility.
ANDREW ROBINSON: There are other tools that can actually go and have a look at the citation and follow citation links, and are these in favor, are they positive or negative citations, rather than just listing. So [INAUDIBLE] would be an example of the former. And [INAUDIBLE] is an example of the latter. As examples of Autograph, CCC, the organization I work for produces novel tools.
ANDREW ROBINSON: And we have an Autograph that has novel application. So if we move on to perhaps some tools-- some recommendations about how to apply the technology and innovation, I think I'm building it on very much, the kind of messages that Allison was saying. Essentially here, be clear about your objectives up front. Know what problem it is you're trying to solve.
ANDREW ROBINSON: What questions are you-- What's your question you're trying to answer? These are really, really important. And delivering technology, deliver in small increments and improve as you go. Essentially, when we're dealing with the systems, I'll be talking about here, and connecting data and sucking content in, you really need to understand your data sources. And the provenance and licensing is really, really important.
ANDREW ROBINSON: And as you scale up from pilot to production, it's absolutely essential that you have the ability to connect to feed, and receive the updates, and know what you're dealing with, and have this traceability back to the original content. Pilot to production can be harder than it looks actually. When producing a pilot, you often ignore the hard stuff. And then when you go into production, actually you got to make that hard stuff work.
ANDREW ROBINSON: And finally, I'd say, remember the network. What we're talking about here is content within a network setting. And the more you can do to make this network effect work adds power to the content you're producing and aids the users and the consumption of it. And then, just to very quickly finish off, at CCC we produce Open Access everywhere as [INAUDIBLE]..
ANDREW ROBINSON: Open access is an example where publishers have to know their customers and experiment with technology to drive value and innovate. And writing scientific communications underpins the open access transactions supporting complex pricing policies and agreements and multiple business models and automated workflows. And with a RESTful API, we can integrate this into the OA ecosystem, enabling automation and transparency.
ANDREW ROBINSON: And a little bit of a rush there. But I think I'll finish, hopefully, on time.
JEFF FROUSTET: Great. Thank you so much Andrew. That was great. The challenge of knowing your customer, how they consume, and what they consume. I think we have a tendency to think of an article as kind of this start to finish document, this product, that understandably, a lot of customers do want. But there are other customers, audiences, that value particular components of an article.
JEFF FROUSTET: To see it as not just a one thing but as a composite of other things. And so that there are entire business lines built around the consumption of the abstract, or references, or formula. And for our last speaker today, we'll go to now Dr. Chhavi Chauhan from the American Society for Investigative Pathology. Dr. Chauhan.
CHHAVI CHAUHAN: Thank you Jeff. Thanks, everyone. I'm honored to be in this company. And thank you SSP for the opportunity. Jeff gave a really nice introduction. But honestly, I am a passionate science nerd. I have been all my life. Almost a decade ago, I was introduced to scholarly publishing. And I became passionate about it and my journey with the scholarly publishing world began.
CHHAVI CHAUHAN: Around three years ago, I was introduced to artificial intelligence. And since then I have become passionate about AI ethics. So if my professional journey is any indication, no matter how technologically challenged you are, if you're passionate, you will succeed. So from my presentation, I really want you to take home two messages. And this has been discussed a lot by previous panelists as well.
CHHAVI CHAUHAN: First and foremost, just remember that change is the only constant. So instead of resisting change and holding on to our technology, I invite you to embrace change. Be aware of new technologies and integrate them in your workflows, to stay relevant and to stay current. And time and time again we hear this phrase, technology leads to disruption. So my second take home message for you is think of technology as an opportunity to innovate.
CHHAVI CHAUHAN: When technology leads to innovation, new avenues open up. And these are new opportunities for you to explore and take your career to new levels. So for the sake of simplicity, let's break down the scholarly publishing landscape into three. So this is content creation, content validation and curation, and content dissemination.
CHHAVI CHAUHAN: So you can imagine authors being in the content creation bucket, peer review systems and editorial offices or production staff being in the content validation and curation bucket. And then there are societies, publishers, libraries, now preprint servers, and also marketing, that helps with content dissemination. So I'm here today to talk about emerging technologies. So let's place some emerging technologies in the scholarly publishing landscape.
CHHAVI CHAUHAN: We have heard from other panelists about metadata. And we've been dealing with it for quite some time now. But in the recent past we have started seeing AI generated data. So for the ASIP flagship journal, The American Journal of Pathology, in 2019, we expanded the scope to include a topic category of AI and computational pathobiology. So I'll give you an example.
CHHAVI CHAUHAN: So we see content where authors have generated algorithms that do image analysis, for example, that can look at tumor sections to grade them. So we have published studies such as validating those algorithms. So it has been found that these algorithms perform better than in-training pathologists. But they're not as superior or as good or superior than a trained pathologist.
CHHAVI CHAUHAN: So now we're dealing with AI generated data. So we have to think our processes again how are we going to validate, and curate this content, and how we're going to disseminate it. And I'll come back to that in a little bit. In the editorial processes, lately we have seen a lot of integration of AI. But essentially it's at the level of robotic process automation.
CHHAVI CHAUHAN: So in the last six years in our own editorial office, we have switched three peer review platforms. We have a very dedicated and committed staff. And we are grateful for that to go through the motions with us. So essentially-- Now we are using Elsevier's or Aries' editorial management platform. So what robotic process automation is doing is freeing up the editorial staff from the mundane. For example, if they were sending-- editorial staff were sending out reminders to target reviewers, the robotic process is going to do it automatically to keep things on track.
CHHAVI CHAUHAN: I think Allison and also Andrew talked a little bit about this. And Jeff used it in his primer. In content dissemination one can focus on data driven marketing and data analytics. So when you're surfing Netflix, it gives you a recommendation about what you should see next. If you're buying on Amazon, it tells you, oh if you bought this, you may be interested in buying this. So similarly when you're browsing through some pages, looking at some content online, if you're looking at an article, you often get recommendations to similar related reading.
CHHAVI CHAUHAN: So that is data driven analytics and data driven marketing that's prompting you to look at this content. A lot of publishers are looking into this to expand their foothold. So organizations or publishers may have great foothold in one geography, so how they can now use very specific marketing techniques to maintain this customer base or to come up with new campaigns to explore new geographies.
CHHAVI CHAUHAN: A lot of publishers are looking into emerging areas. For example, a couple of years ago or last year, Springer came up with a title on AI ethics. So they saw a need for content to be published and an absence of a journal to showcase that content. There could be publishers who are seeking people to write on different avenues of different aspects of quantum computing, for example. So emerging technology is being used in content dissemination as well.
CHHAVI CHAUHAN: I'm giving here just a handful of examples. But there's so many. There's a whole industry that's been built upon these emerging technologies, where authors are being supported in how they can share the content with the publishers. They've been provided with services to check for English language, or grammar, or confront the needs of a particular publisher.
CHHAVI CHAUHAN: There are softwares and widgets available that show how content interacts with other published content and, of course, how this content can be disseminated. And each one of them use different aspects of AI. It could be natural language processing. It could be machine learning or just simple data regression models. As I mentioned earlier, I'm passionate about AI ethics. So time and time again, I think about the ethics of these emerging technologies and how they can be safely developed and safely deployed in the different aspects of scholarly publishing landscape.
CHHAVI CHAUHAN: So in content creation, especially I deal with medical journals. So I can give my own example. It has been-- Collaboration has been a challenge amongst folks to share their data. But now there are technologies such as blockchain that are available. Federated learning which essentially allows you to bring in the algorithm to your institute to do whatever you want to do with your data safely and privately, and then share the findings with your collaborators.
CHHAVI CHAUHAN: For content validation and curation, we have been using a lot of heuristic models, where an input is given to the machine to get to a particular output. And these algorithms work beautifully on training data sets. But often, these training data sets are not truly representative of the real world data. So there are algorithmic accountability teams in place to ensure that when these algorithms are used on real world data, they perform the way they are supposed to and then they are transparent and scalable.
CHHAVI CHAUHAN: And we're all familiar, especially in the COVID landscape, how much amount of misinformation that has been floating around. So as scholarly publishing professionals, as guardians of scholarly publishing, we have to contain the spread of this misinformation. So a lot of preprint servers have been using humans to analyze the articles that they're putting up on their preprint servers.
CHHAVI CHAUHAN: I know researchers are doing that. So people are not extrapolating the findings that are being disseminated prior to peer review. But activity has been checked on social media. And often, information is either labeled as challenging or to be challenged, or oftentimes taken off of social media. So with emerging technologies come emerging roles. So I would like you to focus a little bit on things that we may not have even been thinking about so far.
CHHAVI CHAUHAN: So we talked about AI generated data. And our journals are seeing that already. But in the near future, maybe in 5 or 10 years down the line, AI will be altering content where there could be poems. There could be articles. There could be books written by these machines. So how in the scholarly publishing landscape are we going to deal with that, data that is not authored by a human, but an AI.
CHHAVI CHAUHAN: A lot of ethics boards for algorithmic accountability need to be put into motion. So Elsevier has been on the forefront of putting an ethics board for algorithmic accountability. And these ethics boards are very, very diverse. So of course they need subject matter experts who may be data scientists or computer scientists. And scientists, they have knowledge of a particular language to design these algorithms.
CHHAVI CHAUHAN: But you also need other experts, subject matter experts, from the scholarly publishing landscape who understand what the processes are, what are the questions to be asked, what are the outcomes that need to be addressed. And of course, these ethics boards are a collection of diverse individuals from different data sets. So climbing up the scholarly publishing ladder is not that difficult. I invite you to pair a technology with a skill.
CHHAVI CHAUHAN: So focus on your strengths. And as it has been said already before, upskill constantly. And I would invite you to be hungry to look for new opportunities, not hold yourself back. And most importantly, just be present. So understand what your team does, what your contribution means to your team, how that fits into the goals and missions of your own company, and how that fits into the goals and missions of the whole landscape.
CHHAVI CHAUHAN: If you know those, you will be able to use any emerging technologies to benefit, and even think about the new technologies, how they can help you answer problems that have not even been answered by the currently available technologies. So I hope you all will embrace change and look at technology as a source of innovation. Thank you.
JEFF FROUSTET: Thank you Dr. Chauhan. That was great, the idea that change is a constant and we can't just relegate it as an afterthought, that we need to embrace it. There are market forces driving that change. And it's not just singular companies. No. It's entire industries dedicated to kind of driving that change. And I think now we'll have time for some Q&A. We're just about 3 minutes to the top of the hour.
JEFF FROUSTET:
REBECCA BENNER: Thanks Jeff. This is Rebecca Benner again. If any of our attendees would like to ask a question, the Q&A is open. While we wait for folks to ask a question, one thing I want to ask, we've had a lot of conversations in this hour about sort of continual learning and being hungry and just being curious. So could the panelists talk about how do you, as publishing professionals, stay ahead of new technologies, practically speaking.
REBECCA BENNER:
CHHAVI CHAUHAN: I could go first. And it's sort of building on what Allison had said before. So don't go explore technologies. Look at the problems at hand. So just be very aware of what are the questions that you're asking. And then just seek individuals. Like you may not be an expert in technology, but try to pair up with someone who understands the technology and understands your problem.
CHHAVI CHAUHAN: So you can collaborate with them to come have creative solutions.
ALLISON BELAN: I would echo that really. Mostly I come across new technologies very often, new standards or emerging standards, by recognizing a problem that's been existing in our workflow and thinking like there's got to be a solution to this and then just starting to Google. It's all very unmysterious just using common tools. But once I run across something I say, oh, what is that.
ALLISON BELAN: And then I can start diving in. I've also over the years-- I've really relied on webinars, and SSP conferences, and other industry conferences and offerings to jump start. So once I know something is something I should know more about, I try to find a resource where I can hear from experts in it, in addition to doing my own independent research and learning.
ALLISON BELAN: And then very often, it's coming from our technology partners, the vendors that supply our publishing platform or our peer review system. So those are some sources that I try to keep my ear to the ground with to guide sort of what is the next thing I need to know about.
ANDREW ROBINSON: I could have a go at trying to answer that question. It's a great question. I've never been ceased to be amazed at the amazing technology that's applied in publishing. It's awesome at times. I found myself once with one client-- I was talking about it because I'd understood very little about it. But the application of ontologies and mapping ontologies to people, places, events, and this organization was producing guidebooks.
ANDREW ROBINSON: And then how do we plug-in the guidebooks to connect to tube maps, to events, to what restaurants are nearby, and things like this. And then when you start to have these conversations, you think, yeah wouldn't it be great to do that. You then think how do we make that happen. How do you map? And what data do you surface within these? It's just incredible that the simple conversation, apparently simple conversations like that throw out some amazing tools, and technologies, and challenges, which are just fantastic.
ANDREW ROBINSON: And it just keeps happening. It's amazing.
MELISSA HARRISON: Yeah I don't have a huge amount to add from what everyone said. I agree with all those things. And I think also just kind of from what Andrew said as well, it's that idea of applying what you see going on elsewhere or how you think other things work to the day job, so to speak. And if you hear about something, Googling it, finding out more about it, and then kind of trying to apply that.
MELISSA HARRISON: I'd agree with that.
REBECCA BENNER: Great. Thanks everyone. A question from an attendee. How do you as publishing technologists push through the hype that comes with almost all new technologies? How to develop a sense of what any technology is capable of delivering versus the new loose ends, shifts in labor, potential new problems?
ALLISON BELAN: So I'll jump in. I think I-- there's a couple of immediate answers I have to this. One is that I am decidedly mid-career maybe. I don't know. Maybe even getting into later career. I'm not sure. So I have perspective. I've been through a lot of hype cycles at this point. So I've learned to recognize them or at least to recognize my reaction to a new technology of being like, oh this will solve everything, this is the Holy Grail.
ALLISON BELAN: So I've gained some healthy skepticism over the years. But probably I will also say that working in a resource constricted part of scholarly publishing-- So I'm at a university press that publishes books and journals in the humanities. We can't jump on every new technology that comes down the road. We don't have the human resources or the financial resources to really dive into AI in a serious way.
ALLISON BELAN: So there's a little bit of cooling off that naturally happens. And over time, it becomes-- So between that moment of like there's a new technology on the block and it's really exciting and let's go for it, and when we might actually be able to consider going for it. Some things have become clear, very often.
REBECCA BENNER: Thanks Allison. We have two other questions in the chat. So I'm going to-- The first one is, how do we get editors engage with new technologies and processes? I have some editors who aren't interested in online-only or using other measurement of quality, other than the impact factor. Who'd like to take that?
REBECCA BENNER:
CHHAVI CHAUHAN: I would say, if you find the answer let me know too. I think it's a constant battle we all face in the scholarly publishing world. But I think an engaged editorial board is important. And if you feel like your editors are not engaged enough and are not open to the new technology that can help them, or ease the burden on the authors who are the users, or make things available to our readers who are also the users or consumers, then there might be a need to include more engaged members in the editorial board.
CHHAVI CHAUHAN: Having said that, most publishers and most societies come up with resources that can help the editors get acquainted with new technology. I mentioned that we have gone over three peer review systems in the last six years or so. So that was a rough transition for our staff, as well as for our editors. But we tried to ease the pain for everyone by providing trainings and be open to answering their questions.
CHHAVI CHAUHAN: Be available from the staff side. And I'm sure-- They're volunteers and they would be happy to keep serving if they get the resources that they need to perform their responsibility.
REBECCA BENNER: Thank you so much. All right. And our final question for today is, just by sheer numbers, opportunities diminish as companies shift their resources to outsourcing and automation. What do you recommend for folks early in their career should or as opportunities diminish and competition increases?
ANDREW ROBINSON: I've-- Oh go on Melissa.
MELISSA HARRISON: Oh no. I was just going to say that like I understand that. Because the higher you go up the ladder, there are fewer opportunities, and like with outsourcing. But it's something that Allison mentioned early on, there were different threads. So you might not necessarily kind of be the technologist. But vendor management is a massive area. The more you outsource, you do need staff to manage those vendors.
MELISSA HARRISON: And so you can shift then. And there are different kind of opportunities there, when things like that happen. Sorry, Andrew. You go ahead.
ANDREW ROBINSON: No. I was going to say a similar thing. I think there's different opportunities. New opportunities apply. So whilst there is considerable automation, as somebody who puts automation in many places, the idea is that it frees people up to do higher value work. Sometimes we, as consultants say that, say things like that, and it doesn't always transpire. I realize that.
ANDREW ROBINSON: But it should create new opportunities. And as I was trying to say in my talk about added value, where can you add value, where can you add value. And I think that's a challenge. If you can find a way to add value to something, it makes it more worthwhile. And it benefits many more people and many more systems and ultimately is of use. There's always, always, always going to be an opportunity for those kinds of things.
ANDREW ROBINSON: I think.
CHHAVI CHAUHAN: Yeah. Continue to upskill as well. Because as new-- If there is outsourcing on automation, then that's your opportunity to learn something new.
ALLISON BELAN: Yeah. And I think that outsourcing puts an even greater demand on publishers to have in-house understanding of the technology. That doesn't necessarily mean you need to know how to code or you need to know how to write SQL. But you need to have some basic understanding, at the conceptual and infrastructural level, of what your contractors and vendors are doing in order to manage them, and in order to be sure that they're working in a way to achieve your goals.
ALLISON BELAN: So you still need those technical skills and that technical understanding. But it does move you more toward those disciplines that I mentioned, business analysis, project management, vendor management.
ANDREW ROBINSON: I'd like to add. Just, I think, critical thinking and being able to discern hype from reality is really an important skill. People can bring you things, and try to sell you things, and try to show you things. And you really need to try and see past some of the facades, and understand what's going on underneath and how you can make that work. Because it could be that somebody comes to you with an idea or an opportunity for something.
ANDREW ROBINSON: And you look at it and you go, well it doesn't work for me as you've described. But actually over here, it's a really good application that could really make a difference. And so I think the ability to assess, discern, apply, or reject is a critical skill, useful skill.
REBECCA BENNER: Wonderful. Well, thank you to our speakers for their time and engaging presentations. And thank you to our attendees for your participation in today's webinar. You will receive a webinar evaluation via email. And we encourage you to provide feedback and to help us determine topics for future webinars. Don't miss the next couple events on the SSP calendar, including Accessibility in Publishing on September 23rd, as well as our New Direction Seminar on October 6th and 7th.
REBECCA BENNER: Today's webinar was recorded. And all registrants will be sent a link to the recording when it is posted on the SSP website. This concludes our session today.
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