The Library as Research Partner

As I typed the title for this post, I couldn’t help but think “Well, yeah. What else would the library be?” Instead of changing the title, however, I want to actually unpack what we mean when we say “research partner,” especially in the context of research data management support. In the most traditional sense, libraries provide materials and space that support the research endeavor, whether it be in the physical form (books, special collections materials, study carrels) or the virtual (digital collections, online exhibits, electronic resources). Moreover, librarians are frequently involved in aiding researchers as they navigate those spaces and materials. This aid is often at the information seeking stage, when researchers have difficulty tracking down references, or need expert help formulating search strategies. Libraries and librarians have less often been involved at the most upstream point in the research process: the start of the experimental design or research question. As one considers the role of the Library in the scholarly life-cycle, one should consider the ways in which the Library can be a partner with other stakeholders in that life-cycle. With respect to research data management, what is the appropriate role for the Library?

In order to achieve effective research data management (RDM), planning for the life-cycle of the data should occur before any data are actually collected. In circumstances where there is a grant application requirement that triggers a call to the Library for data management plan (DMP) assistance, this may be possible. But why are researchers calling the Library? Ostensibly, it is because the Library has marketed itself (read: its people) as an expert in the domain of data management. It has most likely done this in coordination with the Research Office on campus. Even more likely, it did this because no one else was. It may have done this as a response to the National Science Foundation (NSF) DMP requirement in 2011, or it may have just started doing this because of perceived need on campus, or because it seems like the thing to do (which can lead to poorly executed hiring practices). But unlike monographic collecting or electronic resource acquisition, comprehensive RDM requires much more coordination with partners outside the Library.

Steven Van Tuyl has written about the common coordination model of the Library, the Research Office, and Central Computing with respect to RDM services. The Research Office has expertise in compliance and Central Computing can provide technical infrastructure, but he posits that there could be more effective partners in the RDM game than the Library. That perhaps the Library is only there because no one else was stepping up when DMP mandates came down. Perhaps enough time has passed, and RDM and data services have evolved enough that the Library doesn’t have to fill that void any longer. Perhaps the Library is actually the *wrong* partner in the model. If we acknowledge that communities of practice drive change, and intentional RDM is a change for many of the researchers, then wouldn’t ceding this work to the communities of practice be the most effective way to stimulate long lasting change? The Library has planted some starter seeds within departments and now the departments could go forth and carry the practice forward, right?

Well, yes. That would be ideal for many aspects of RDM. I personally would very much like to see the intentional planning for, and management of, research data more seamlessly integrated into standard experimental methodology. But I don’t think that by accomplishing that, the Library should be removed as a research partner in the data services model. I say this for two reasons:

  1. The data/information landscape is still changing. In addition to the fact that more funders are requiring DMPs, more research can benefit from using openly available (and well described – please make it understandable) data. While researchers are experts in their domain, the Library is still the expert in the information game. At its simplest, data sources are another information source. The Library has always been there to help researchers find sources; this is another facet of that aid. More holistically, the Library is increasingly positioning itself to be an advocate for effective scholarly communication at all points of the scholarship life-cycle. This is a logical move as the products of scholarship take on more diverse and “nontraditional” forms.

Some may propose that librarians who have cultivated RDM expertise can still provide data seeking services, but perhaps they should not reside in the Library. Would it not be better to have them collocated with the researchers in the college or department? Truly embedded in the local environment? I think this is a very interesting model that I have heard some large institutions may want to explore more fully. But I think my second point is a reason to explore this option with some caution:

2. Preservation and access. Libraries are the experts in the preservation and access of materials. Central Computing is a critical institutional partner in terms of infrastructure and determining institutional needs for storage, porting, computing power, and bandwidth but – in my experience – are happy to let the long-term preservation and access service fall to another entity. Libraries (and archives) have been leading the development of digital preservation best practices for some time now, with keen attention to complex objects. While not all institutions can provide repository services for research data, the Library perspective and expertise is important to have at the table. Moreover, because the Library is a discipline-agnostic entity, librarians may be able to more easily imagine diverse interest in research data than the data producer. This can increase the potential vehicles for data sharing, depending on the discipline.

Yes, RDM and data services are reaching a place of maturity in academic institutions where many Libraries are evaluating, or re-evaluating, their role as a research partner. While many researchers and departments may be taking a more proactive or interested position with RDM, it is not appropriate for Libraries to be removed from the coordinated work that is required. Libraries should assert their expertise, while recognizing the expertise of other partners, in order to determine effective outreach strategies and resource needs. Above all, Libraries must set scope for this work. Do not be deterred by the increased interest from other campus entities to join in this work. Rather, embrace that interest and determine how we all can support and strengthen the partnerships that facilitate the innovative and exciting research and scholarship at an institution.

Data, data everywhere…but do we want to drink?

The role of data, digital curation, and scholarly communication in academic libraries.

Ask around and you’ll hear that data is the new bacon (or turkey bacon, in my case. Sorry, vegetarians). It’s the hot thing that everyone wants a piece of. It is another medium with which we interact and derive meaning from. It is information[1]; potentially valuable and abundant. But much like [turkey] bacon, un-moderated gorging, without balance or diversity of content, can raise blood pressure and give you a heart attack. To understand how best to interact with the data landscape, it is important to look beyond it.

What do academic libraries need to know about data? A lot, but in order to separate the signal from the noise, it is imperative to look at the entire environment. To do this, one can look to job postings as a measure of engagement. The data curation positions, research data services departments, and data management specializations focus almost exclusively on digital data. However, these positions, which are often catch-alls for many other things do not place the data management and curation activities within the larger frame of digital curation, let alone scholarly communication. Missing from job descriptions is an awareness of digital preservation or archival theory as it relates to data management or curation. In some cases, this omission could be because a fully staffed digital collections department has purview over these areas. Nonetheless, it is important to articulate the need to communicate with those stakeholders in the job description. It may be said that if the job ad discusses data curation, digital preservation should be an assumed skill, yet given the tendencies to have these positions “do-all-the-things” it is negligent not to explicitly mention it.

Digital curation is an area that has wide appeal for those working in academic and research libraries. The ACRL Digital Curation Interest Group (DCIG) has one of the largest memberships within ACRL, with 1075 members as of March 2015. The interest group was intentionally named “digital curation” rather than “data curation” because the founders (Patricia Hswe and Marisa Ramirez) understood the interconnectivity of the domains and that the work in one area, like archives, could influence the work in another, like data management. For example, the work from Digital POWRR can help inform digital collection platform decisions or workflows, including data repository concerns. This Big Tent philosophy can help frame the data conversations within libraries in a holistic, unified manner, where the various library stakeholders work collaboratively to meet the needs of the community.

The absence of a holistic approach to data can result in the propensity to separate data from the corpus of information for which librarians already provide stewardship. Academic libraries may recognize the need to provide leadership in the area of data management, but balk when asked to consider data a special collection or to ingest data into the institutional repository. While librarians should be working to help the campus community become critical users and responsible producers of data, the library institution must empower that work by recognizing this as an extension of the scholarly communication guidance currently in place. This means that academic libraries must incorporate the work of data information literacy into their existing information literacy and scholarly communication missions, else risk excluding these data librarian positions from the natural cohort of colleagues doing that work, or risk overextending the work of the library.

This overextension is most obvious in the positions that seek a librarian to do instruction in data management, reference, and outreach, and also provide expertise in all areas of data analysis, statistics, visualization, and other data manipulation. There are some academic libraries where this level of support is reasonable, given the mission, focus, and resourcing of the specific institution. However, considering the diversity of scope across academic libraries, I am skeptical that the prevalence of job ads that describe this suite of services is justified. Most “general” science librarians would scoff if a job ad asked for experience with interpreting spectra. The science librarian should know where to direct the person who needs help with reading the spectra, or finding comparative spectra, but it should not be a core competency to have expertise in that domain. Yet experience with SPSS, R, Python, statistics and statistical literacy, and/or data visualization software find their way into librarian position descriptions, some more specialized than others.

For some institutions this is not an overextension, but just an extension of the suite of specialized services offered, and that is well and good. My concern is that academic libraries, feeling the rush of an approved line for all things data, begin to think this is a normal role for a librarian. Do not mistake me, I do not write from the perspective that libraries should not evolve services or that librarians should not develop specialized areas of expertise. Rather, I raise a concern that too often these extensions are made without the strategic planning and commitment from the institution to fully support the work that this would entail.

Framing data management and curation within the construct of scholarly communication, and its intersections with information literacy, allows for the opportunity to build more of this content delivery across the organization, enfranchising all librarians in the conversation. A team approach can help with sustainability and message penetration, and moves the organization away from the single-position skill and knowledge-sink trap. Subject expertise is critical in the fast-moving realm of data management and curation, but it is an expertise that can be shared and that must be strategically supported. For example, with sufficient cross-training liaison librarians can work with their constituents to advise on meeting federal data sharing requirements, without requiring an immediate punt to the “data person” in the library (if such a person exists). In cases where there is no data point person, creating a data working group is a good approach to distribute across the organization both the knowledge and the responsibility for seeking out additional information.

Data specialization cuts across disciplinary bounds and concerns both public services and technical services. It is no easy task, but I posit that institutions must take a simultaneously expansive yet well-scoped approach to data engagement – mindful of the larger context of digital curation and scholarly communication, while limiting responsibilities to those most appropriate for a particular institution.

[1] Lest the “data-information-knowledge-wisdom” hierarchy (DIKW) torpedo the rest of this post, let me encourage readers to allow for an expansive definition of data. One that allows for the discrete bits of data that have no meaning without context, such as a series of numbers in a .csv file, and the data that is described and organized, such as those exact same numbers in a .csv file, but with column and row descriptors and perhaps an associated data dictionary file. Undoubtedly, the second .csv file is more useful and could be classified as information, but most people will continue to call it data.

Yasmeen Shorish is assistant professor and Physical & Life Sciences librarian at James Madison University. She is a past-convener for the ACRL Digital Curation Interest Group and her research focus is in the areas of data information literacy and scholarly communication.

A Forray into Publishing Open Data on GitHub

While we’ve written about using GitHub for publishing before, in this post I will explore publishing data on GitHub, as opposed to a presentation or academic paper. There are a few services where one can publish research data—FigShare comes to mind—but I wanted to try GitHub because I’m already familiar with the service, it seems suitable for publishing data alongside the scripts used to obtain and process it, and its focus on version control makes it particularly apt for publishing a work in progress. However, even with free services like GitHub available, open data still has hurdles to overcome. How can I, a lowly librarian with no grant funding or experience in this area, publish an open data set such that others can locate and reuse it? Let’s find out.


As Lauren introduced in her last post, we here at ACRL Tech Connect are performing research into coding in libraries; how people learn to code, what learning resources they use, what languages they use. As part of this research, I wanted to compare what our survey respondents reported with a bulk analysis of GitHub repositories under library organizations. The Code4Lib wiki has an excellent page listing many library GitHub accounts, and GitHub has a nice API that reports, among many other things, the various languages used in a project. Those two sources of information seemed like a perfect match, so I wrote a few scripts to mash them together.

Publishing scripts that extract and analyze data is important. One cannot trust the results of a single scientific experiment or a poor sample set. Providing the programs used to collect data aims to allow reproducibility so future researchers can verify or build upon prior results. While we perhaps think of science as being quite established by now, data and reproducibility are major issues in most fields. Ask any data librarian and they’ll tell you; managing the preservation and distribution of research data is not a solved or simple problem. Furthermore, every so often another meta-research study will show that only some dismal percentage of experiments can be replicated.1

My own data is not so valuable. No cure for a debilitating disease rests on the number of bytes of Standard ML in your university’s GitHub account. But on principle I want to let my results be repeatable and, what’s more, if someone does find an error in my scripts or data I want it corrected. Even if my initial conclusions are off, someone might be able to construct a stronger study from their basis.

Step #1: Obtain a DOI

As the first step of publishing my data, I wanted to obtain a Digital Object Identifier. Sure, putting my work up on GitHub gives me a URL I can reference, but leaving it at that adds a lot of uncertainty. What if I change my GitHub username, which is contained in the URL? What if I transfer the repository to a new owner? What if GitHub goes out of business? While none of these are likely scenarios, they’re still worth guarding against. DOI providers essentially stick to a pact that their identifiers will continue to work for perpetuity. While that’s not always the case, I feel like grabbing a DOI is still The Right Thing To Do for pubishers at the present moment.

We can use Zenodo to secure a DOI. GitHub already has a fine guide named Making Your Code Citable, but I’ll lightly outline the process here.

First, we create a Zenodo account reusing our GitHub credentials. Zenodo will list out our repositories and we can click the On button next to one to ready it for publishing. This button establishes a “web hook” between events happening in that GitHub repository and Zenodo; when we go to publish a release, Zenodo will be aware of it.

This was the only step that tripped me up a bit. GitHub’s “releases” are not a part of the git version control system, they’re an added feature of the hosting environment. But in my mind they’re identical to git’s “tags” that one uses to label particular points in a repository’s history. Indeed, when we push a tag up to GitHub, it’ll show up on our repository’s releases page. But it appears tags are not technically releases, or don’t trigger the right web hook, because when I pushed a typical “v1.0.0” tag to GitHub, Zenodo didn’t notice. Instead, I had to go to my releases page, Draft a new release, and then Choose an existing tag to associate the version tag with a GitHub release. The title and description entered at this stage are available later in Zenodo.

The final step is back in Zenodo, where we can mint a DOI and describe our project further. We have a powerful set of fields for describing our project in Zenodo, including type (e.g. data set, software, presentation, publication), publication date, list of authors, open-ended description, list of keywords, access rights, license, funding agency, alternative identifiers (e.g. PubMed ID), and more. Zenodo also has a “communities” feature where we can deposit our research in a collection with a disciplinary focus; I put my data in the “Library and Information Science” group.

Step #2: Document the Data’s Schema

Obtaining a DOI is fine and all, but I also wanted to document my data more thoroughly. While it’s not a complicated data set, I’m familiar with the challenges that an unknown data schema presents for end users. All too often at work, I’m forced to revise data processing routines because a new outlier appears. There’ll be a string of text where I’m expecting only integers, a blank entry in what I thought was a required field, or an ID that doesn’t conform to the anticipated pattern (punctuation appears in a barcode! a random letter prefixes an otherwise numeric ID!).

To make our data’s structure clear, we can use the Data Package standard from the Open Knowledge Foundation (OKFN), specifically the Tabular Data Package subset which was designed for the CSV (comma-separated values) format.2 Documenting our data is straightforward with these standards; we place a “datapackage.json” file alongside our data files and fill in a few fields. Here’s an example:

    "name": "libs-github-api", // must be URL-friendly, e.g. no spaces 
    "description": "library GitHub projects",
    "license": "CC0 Public Domain",
    "keywords": ["libraries", "programming languages"],
    "resources": [ // list of files 
            "name": "summary",
            "path": "data/summary.csv", // UNIX-style path relative to datapackage.json 
            "format": "csv",
            "mediatype": "text/csv",
            "schema": { // outline of fields within this file 
                "fields": [
                        "name": "language",
                        "type": "string", /* from a controlled list of data types
                        could also be integer, number, date, etc. */
                        "description": "name of the programming language",
                        "constraints": {
                            "required": true,
                            "unique": true
                    // our schema would list a few more fields here… 

Note that the comments above aren’t valid in JSON, I include them simply to provide some inline explanation.

While it requires a little reading to figure out how to fill out datapackage.json fields, many are self-evident. The appeal of the standard becomes evident in the schema section; we can tell consumers what types to expect from our data and other particularities of a given CSV column. Does a column contain empty values? Then required will be absent or explicitly set to false. Does a column contain both integers and text? Then the type “string” warns consumers not to anticipate only numeric values. What’s more, we can provide a regular expression in the pattern constraint which specifies exactly how a field may be formatted. Even strange barcodes with surprise punctuation could be documented precisely.

I would say there’s a lot more to the Data Package standards, but the truth is they’re elegant and concise. One can read all three (Data Package, Tabular Data Package, and JSON Table Schema) in a matter of minutes, look at an instructive example or two, and be ready to reveal their data’s structure in a standardized way. There is great depth available in the way one describes individual resources and their data schema.

Why spend all this time with a data package when we’ve already done something similar with Zenodo? The data package documentation solves a couple problems. First of all, packaging up our CSV alongside structured data about its nature addresses findability. There’s tons of open data out there, the issue is it can be scattered and difficult to find. If someone is looking for statistics on programming language usage, how would they go about finding my data? Searching GitHub will be challenging; the keywords one uses (“programming language”, the ambiguous “libraries”, etc.) will likely retrieve many repositories which don’t contain open data, and GitHub, while it does have a decent advanced search form, doesn’t have the facets to make retrieving a particular data set straightforward. One cannot, for instance, filter search results by a repository’s license or the format (CSV, JSON) of the data contained therein.

Data packages address the issue of findability by providing for the possibility of a registry that aggregates all the data sets it knows about. Once a datapackage.json appears, suddenly information like whether the format is CSV or JSON, what the license is, who created it, and what subject keywords are related to a repository become clear. The Open Knowledge Foundation already has a strong proof-of-concept registry, albeit one that lists only around a hundred data sets.

Since Data Package is an open standard, any third-party can easily parse its metadata and provide search facets based on the fields that are present. This is how the standard addresses a second issue; machine readability. Documenting data sets is good, necessary even, but it often only helps humans. I can write a five-page paper meticulously detailing my data’s collection methodology and structure, but that’s asking researchers to do a lot of reading. Now consider that their research might be on a grand scale; imagine if they needed to read a hundred five page papers describing ad hoc data schemas!

Instead, creating a machine readable description lets my data be processed quickly by a specially designed program. As a somewhat trivial example, I already used the OKFN’s Data Package Validator to ensure my schema documentation met their standard. As a more interesting use case, the OKFN also defines an optional “views” section of the data package standard which allows applications to automatically create charts from our data.


While I’m glad that tools like Zenodo and standards like Data Package exist for publishing data, there’s still a lot of work to be done in this arena. Every time I make a new release on GitHub, which arguably should happen with even minor changes to my data or scripts, I have to refill the extensive Zenodo form. Zenodo also doesn’t detect the GitHub repository’s license, which is hardly blameworthy given that that information isn’t present as structured data but mere text in a readme file. However, when publishing a new version of the same underlying data, it doesn’t fill in the license or other information from its own previous items.

There’s a ton of efficiency left on the table in the data publishing process this post describes. Specifically, an integration between Zenodo and the datapackage.json metadata would alleviate a number of problems. Rather than repeatedly filling out a form in Zenodo, one could simply ensure changes were reflected in the datapackage.json and publish a new version on GitHub. Many fields between the two are redundant, though each also has its unique value; Zenodo asks for typical academic publishing information (e.g. publication type, links to prior versions) while Data Package asks for a data schema.

As a final area of concern, the open-ended “license” field is going to eventually limit the utility of the machine readable information in a Data Package.3 Perhaps this is my inner librarian unnecessarily freaking out here, but uncontrolled fields which affect resource reuse are bad news. Defaulting to authors specifying an arbitrary string of text as a license is precisely the problem that the Digital Public Library of America and other large digital libraries are facing, as their corpuses contain thousands of different rights statements.4 Zenodo provides a substantial list of licenses to choose from, but then does a poor job of automatically detecting one even if hints are available via GitHub or a previous incarnation of the publication. GitHub itself should probably make licenses for repositories required and controlled as I could see that being a vital facet in their advanced search as well as interesting data to expose to researchers via their API.

  1. I read something about this a month or two ago, but wasn’t able to relocate the source. Scouring the web, there’s a Washington Post article from January on the phenomenon of irreproducible research, which in turn points to a PLoS Med article from 2005 “Why Most Published Research Findings Are False“. Other studies along these lines are “A Survey on Data Reproducibility in Cancer Research Provides Insights into Our Limited Ability to Translate Findings from the Laboratory to the Clinic” in PLoS ONE and “Drug development: Raise standards for preclinical cancer research” in Nature.
  2. I might have been able to explore another intriguing project, Research Objects, which has the apt tagline “enabling reproducible, transparent research.” However, the Data Package standards were so easy to find and follow conceptually that I chose them.
  3. And to be fair, I did see one example where the licenses JSON property was specified as an array of objects containing a license name and URL, which might be easier to consume in script depending on what’s available at the URL.
  4. Aside: I don’t mean to argue that arbitrary license strings should be prohibited, because no controlled vocabulary is going to enumerate all possible choices. But there’s a lot of good work being done to make licenses easier to specify—think of Creative Commons with their composable, versioned licenses which can be referred to by URL. Defaulting to a controlled list of license types or at least pointing to a preferred vocabulary would help here.

Educating Your Campus about Predatory Publishers

The recent publication of Monica Berger and Jill Cirasella’s piece in College and Research Libraries News “Beyond Beall’s List: Better understanding predatory publishers” is a reminder that the issue of “predatory publishers” continues to require focus for those working in scholarly communication. Berger and Cirasella have done a exemplary job of laying out some of the issues with Beall’s list, and called on librarians to be able “to describe the beast, its implications, and its limitations—neither understating nor overstating its size and danger.”

At my institution academic deans have identified “predatory” journals as an area of concern, and I am sure similar conversations are happening at other institutions. Here’s how I’ve “described the beast” at my institution, and models for services we all can provide, whether subject librarian or scholarly communication librarian.

What is a Predatory Publisher? And Why Does the Dean Care?

The concept of predatory publishers became much more widely known in 2013 with a publication of an open access sting by John Bohannon in Science, which I covered in this post. As a recap, Bohannon created a fake but initially believable poor quality scientific article, and submitted it to open access journals. He found that the majority of journals accepted the poor quality paper, 45% of which were included in the Directory of Open Access Journals. At the time of publication in October 2013 the response to this article was explosive in the scholarly communications world. It seems that more than a year later the reaction continues to spread. Late in the fall semester of 2014, library administration asked me to prepare a guide about predatory publishers, due to concern among the deans that unscrupulous publishers might be taking advantage of faculty. This was a topic I’d been educating faculty about on an ad hoc basis for years, but I never realized we needed to address it more systematically. That all has changed, with senior library administration now doing regular presentations about predatory publishers to faculty.

If we are to be advocates of open access, we need to focus on the positive impact that open access has rather than dwell for too long on the bad sides of it. We also need faculty to be clear on their own goals for making their work open access so that they may make more informed choices. Librarians have limited faculty bandwidth on the topic, and so focusing on education about self-archiving articles (otherwise known as green open access) or choosing no-fee (also known as gold) open access journals is a better way to achieve advocacy goals than suggesting faculty choose only a certain set of gold open access journals. Unless we are offering money for paying article fees, we also don’t have much say about where faculty choose to publish. Education about how to choose a journal and a license responsibly is what we should focus on, even if it diverges from certain ideals (see Meredith Farkas on choosing creative commons licenses.)

Understanding the Needs and Preparing the Material

As I mentioned, my library administration asked for a guide that that they could use in presentations and share with faculty. In preparing this guide, I worked with our library’s Scholarly Communications committee (of which I am co-chair) to determine the format and content.

We decided that adding this material to our existing Open Access research guide would be the best move, since it was already up and we shared the URL widely already. We have a robust series of Open Access Week events (which I wrote about last fall) and this seemed to ideal place to continue engaging people. That said, we determined that the guide needed an overhaul to make it more clear that open access was an on-going area of concern, not a once a year event. Since faculty are not always immediately thinking of making work open access but of the mechanics of publishing, I preferred to start with the title “Publishing Your Own Work”.

To describe its features a bit more, I wanted to start from the mindset of self-archiving work to make it open access with a description of our repository and Peter Suber’s useful guide to making one’s own work open access. I then continued with an explanation of article publication fees, since I often get questions along those lines. They are not unique to open access journals, and don’t imply any fee to accept for publication, which was a fear that I heard more than once during Open Access Week last year. I only then discussed the concept of predatory journals, with the hope that a basic understanding of the process would allay fears. I then present a list of steps to research a journal. I thought these steps were more common sense than anything, but after conversations with faculty and administration, I realized that my intuition about what type of journal I am dealing with is obvious because I have daily practice and experience. For people new to the topic I tried to break down research into easy steps that help them to figure out where a journal is on the continuum from outright scams to legitimate but new or unusual journals. It was also important to me to emphasize self-archiving as a strategy no matter the journal publication model.

Lastly, while most academic libraries have a model of liaison librarians engaging in scholarly communications activities, the person who spends every day working on these issues is likely to be more versed in emerging trends. So it is important to work with liaisons to help them research journals and to identify quality open access journals in their disciplines. We plan to add this information to the guide in a future version.

Taking it on the Road

We felt that in-person instruction on these matters with faculty was a crucial next step, particularly for people who publish in traditional journals but want to make their work available. Traditional journals’ copyright transfer agreements can be predatory, even if we don’t think about it in those terms. Taking inspiration from the ACRL Scholarly Communications Roadshow I attended a few years ago, I decided to take the curriculum from that program and offer it to faculty and graduate students. We read through three publication agreements as a group, and then discussed how open the publishers were to reuse of material, or whether they mentioned it at all. We then included a section on addenda to contracts for negotiation about additional rights.

The first workshop received modest attendance, but included some thoughtful conversations, and we have promised to run it again. Some people may never have read their agreements closely, and never realized they were doing something illegal or not specifically allowed by, for instance, sharing an article they wrote with their students. That concrete realization is more likely to spur action than more abstract arguments about the benefits of open access.

Escaping the Predator Metaphor

If I could go back, I would get rid of the concept of “predator” attached to open access journals. Let’s call it instead unscrupulous entrants into an emerging business model. That’s not as catchy, but it explains why this has happened. I would argue, personally, that the hybrid gold journals by large publishers are just as predatory, as they capitalize on funding requirements to make articles open access with high fees. They too are trying new business models, and those may not be tenable either. As I said above, choosing a journal with eyes wide open and understanding all the ramifications of different publication models is the only way forward. To suggest that faculty are innocently waiting to be pounced on by predators is to deny their agency and their ability to make choices about their own work. There may be days where that metaphor seems apt, but I think overall this is a damaging mentality to librarians interested in promoting new models of scholarly communication. I hope we can provide better resources and programming to escape this, as well as to help administration to understand how to choose to fund open access initiatives.

In the comments I’d like to hear more suggestions about how to escape the “predator” metaphor, as well as your own techniques for educating faculty on your campus.

Making Open Access Everyone’s Business

Librarians should have a role in promoting open access content. The best methods and whether they are successful is a matter of heated debate. Take for an example a recent post by Micah Vandergrift on the ACRL Scholarly Communications mailing list, calling on librarians to stage a publishing walkout and only publish in open access library and information science journals. Many have already done so. Others, like myself, have published in traditional journals (only once in my case) but make a point of making their work available in institutional repositories. I personally would not publish in a journal that did not allow such use of my work, and I know many who feel the same way. 1 The point is, of course, to ensure that librarians are not be hypocritical in their own publishing and their use of repositories to provide open access–a long-standing problem pointed out by Dorothea Salo 2, among others3 We know that many of the reasons that faculty may hesitate to participate in open access publishing relate to promotion and tenure requirements, which generally are more flexible for academic librarians (though not in all cases–see Abigail Goben’s open access tenure experiment). I suspect that many of the reasons librarians aren’t participating more in open access has partly to do with more mundane reasons of forgetting to do so, or fearing that work is not good enough to make public.

But it shouldn’t be only staunch advocates of open access, open peer review, or new digital models for work and publishing who are participating. We have to find ways to advocate and educate in a gentle but vigorous manner, and reach out to new faculty and graduate students who need to start participating now if the future will be different. Enter Open Access Week, a now eight-year-old celebration of open access organized by SPARC. Just as Black Friday is the day that retailers hope to be in the black, Open Access Week has become an occasion to organize around and finally share our message with willing ears. Right?

It can be, but it requires a good deal of institutional dedication to make it happen. At my institution, Open Access Week is a big deal. I am co-chair of a new Scholarly Communications committee which is now responsible for planning the week (the committee used to just plan the week, but the scope has been extended). The committee has representation from Systems, Reference, Access Services, and the Information Commons, and so we are able to touch on all aspects of open access. Last year we had events five days out of five; this year we are having events four days out of five. Here are some of the approaches we are taking to creating successful conversations around open access.

    • Focus on the successes and the impact of your faculty, whether or not they are publishing in open access journals.

The annual Celebration of Faculty Scholarship takes place during Open Access Week, and brings together physical material published by all faculty at a cocktail reception. We obtain copies of articles and purchase books written by faculty, and set up laptops to display digital projects. This is a great opportunity to find out exactly what our faculty are working on, and get a sense of them as researchers that we may normally lack. It’s also a great opportunity to introduce the concept of open access and recruit participants to the institutional repository.

    • Highlight the particular achievements of faculty who are participating in open access.

We place stickers on materials at the Celebration that are included in the repository or are published in open access journals. This year we held a panel with faculty and graduate students who participate in open access publishing to discuss their experiences, both positive and negative.

  • Demonstrate the value the library adds to open access initiatives.

Recently bepress (which creates the Digital Commons repositories on which ours runs) introduced a real time map of repositories downloads that was a huge hit this year. It was a compelling visual illustration of the global impact of work in the repository. Faculty were thrilled to see their work being read across the world, and it helped to solve the problem of invisible impact. We also highlighted our impact with a new handout that lists key metrics around our repository, including hosting a new open access journal.

  • Talk about the hard issues in open access and the controversies surrounding it, for instance, CC-BY vs. CC-NC-ND licenses.

It’s important to not sugarcoat or spin challenging issues in open access. It’s important to include multiple perspectives and invite difficult conversations. Show scholars the evidence and let them draw their own conclusions, though make sure to step in and correct misunderstandings.

  • Educate about copyright and fair use, over and over again.

These issues are complicated even for people who work on them every day, and are constantly changing. Workshops, handouts, and consultation on copyright and fair use can help people feel more comfortable in the classroom and participating in open access.

  • Make it easy.

Examine what you are asking people to do to participate in open access. Rearrange workflows, cut red tape, and improve interfaces. Open Access Week is a good time to introduce new ideas, but this should be happening all year long.

We can’t expect revolutions in policy and and practice to happen overnight, or without some  sacrifice. Whether you choose to make your stand to only publish in open access journals or some other path, make your stand and help others who wish to do the same.

  1. Publishers have caught on to this tendency in librarians. For instance, Taylor and Francis has 12-18 month repository embargoes for all its journals except LIS journals. Whether this is because of the good work we have done in advocacy or a conciliatory gesture remains up for debate.
  2. Salo, Dorothea. “Innkeeper at the Roach Motel,” December 11, 2007.
  3. Xia, Jingfeng, Sara Kay Wilhoite, and Rebekah Lynette Myers. “A ‘librarian-LIS Faculty’ Divide in Open Access Practice.” Journal of Documentation 67, no. 5 (September 6, 2011): 791–805. doi:10.1108/00220411111164673.

Taking a Practical Look at the Google Books Case

Last month we got the long-awaited ruling in favor of Google in the Authors Guild vs. Google Books case, which by now has been analyzed extensively. Ultimately the judge in the case decided that Google’s digitization was transformative and thus constituted fair use. See InfoDocket for detailed coverage of the decision.

The Google Books project was part of the Google mission to index all the information available, and as such could never have taken place without libraries, which hold all those books. While most, if not all, the librarians I know use Google Books in their work, there has always been a sense that the project should not have been started by a commercial enterprise using the intellectual resources of libraries, but should have been started by libraries themselves working together.  Yet libraries are often forced to be more conservative about digitization than we might otherwise be due to rules designed to protect the college or university from litigation. This ruling has made it seem as though we could afford to be less cautious. As Eric Hellman points out, the decision seems to imply that with copyright the ends are the important part, not the means. “In Judge Chin’s analysis, copyright is concerned only with the ends, not the means. Copyright seems not to be concerned with what happens inside the black box.” 1 As long as the end use of the books was fair, which was deemed to be the case, the initial digitization was not a problem.

Looking at this from the perspective of repository manager, I want to address a few of the theoretical and logistical issues behind such a conclusion for libraries.

What does this mean for digitization at libraries?

At the beginning of 2013 I took over an ongoing digitization project, and as a first-time manager of a large-scale long-term project, I learned a lot about the processes involved in such a project. The project I work with is extremely small-scale compared with many such projects, but even at this scale the project is expensive and time-consuming. What makes it worth it is that long-buried works of scholarship are finally being used and read, sometimes for reasons we do not quite understand. That gets at the heart of the Google Books decision—digitizing books in library stacks and making them more widely available does contribute to education and useful arts.

There are many issues that we need to address, however. Some of the most important ones are what access can and should be provided to what works, and making mass digitization more available to smaller and international cultural heritage institutions. Google Books could succeed because it had the financial and computing resources of Google matched with the cultural resources of the participating research libraries. This problem is international in scope. I encourage you to read this essay by Amelia Sanz, in which she argues that digitization efforts so far have been inherently unequal and a reflection of colonialism. 2 But is there a practical way of approaching this desire to make books available to a wider audience?

Providing Access

There are several separate issues in providing access. Books that are in the public domain are unquestionably fine to digitize, though differences in international copyright law make it difficult to determine what can be provided to whom. As Amelia Sanz points out, Google can only digitize Spanish works prior to 1870 in Spain, but may digitize the complete work in the United States. The complete work is not available to Spanish researchers, but it is available in full to US researchers.

That aside, there are several reasons why it is useful to digitize works still unquestionably under copyright. One of the major reasons is textual corpus analysis–you need to have every word of many texts available to draw conclusions about use of words and phrases in those texts. Google Books ngram viewer is one such tool that comes out of mass digitization. Searching for phrases in Google and finding that phrase as a snippet in a book is an important way to find information in books that might otherwise be ignored in favor of online sources. Some argue that this means that those books will not be purchased when they might have otherwise been, but it is equally possible that this leads to greater discovery and more purchases, which research into music piracy suggests may be the case.

Another reason to digitize works still under copyright is to highlight the work of marginalized communities, though in that case it is imperative to work with those communities to ensure that the digitization is not exploitative. Many orphan works, for whom a rights-holder cannot be located, fall under this, and I know from some volunteer work that I have done that small cultural heritage institutions are eager to digitize material that represents the cultural and intellectual output of their communities.

In all the above cases, it is crucial to put into place mechanisms for ensuring that works under copyright are not abused. Google Books uses an algorithm that makes it impossible to read an entire book, which is probably beyond the abilities of most institutions. (If anyone has an idea for how to do this, I would love to hear it.) Simpler and more practical solutions to limiting access are to only make a chapter or sample of a book available for public use, which many publishers already allow. For instance, Oxford University Press allows up to 10% of a work (within certain limits) on personal websites or institutional repositories. (That is, of course, assuming you can get permission from the author). Many institutions maintain “dark archives“, which are digitized and (usually) indexed archives of material inaccessible to the public, whether institutional or research information. For instance, the US Department of Energy Office of Scientific and Technical Information maintains a dark archive index of technical reports comprising the equivalent of 6 million pages, which makes it possible to quickly find relevant information.

In any case where an institution makes the decision to digitize and make available the full text of in-copyright materials for reasons they determine are valid, there are a few additional steps that institutions should take. Institutions should research rights-holders or at least make it widely known to potential rights-holders that a project is taking place. The Orphan Works project at the University of Michigan is an example of such a project, though it has been fraught with controversy. Another important step is to have a very good policy for taking down material when a rights-holder asks–it should be clear to the rights-holder whether any copies of the work will be maintained and for what purposes (for instance archival or textual analysis purposes).

Digitizing, Curating, Storing, Oh My!

The above considerations are only useful when it is even possible for institutions without the resources of Google to start a digitization program. There are many examples of DIY digitization by individuals, for instance see Public Collectors, which is a listing of collections held by individuals open for public access–much of it digitized by passionate individuals. Marc Fischer, the curator of Public Collectors, also digitizes important and obscure works and posts them on his site, which he funds himself. Realistically, the entire internet contains examples of digitization of various kinds and various legal statuses. Most of this takes place on cheap and widely available equipment such as flatbed scanners. But it is possible to build an overhead book scanner for large-scale digitization with individual parts and at a reasonable cost. For instance, the DIY Book Scanning project provides instructions and free software for creating a book scanner. As they say on the site, all the process involves is to “[p]oint a camera at a book and take pictures of each page. You might build a special rig to do it. Process those pictures with our free programs. Enjoy reading on the device of your choice.”

“Processing the pictures” is a key problem to solve. Turning images into PDF documents is one thing, but providing high quality optical character recognition is extremely challenging. Free tools such as FreeOCR make it possible to do OCR from image or PDF files, but this takes processing power and results vary widely, particularly if the scan quality is lower. Even expensive tools like Adobe Acrobat or ABBYY FineReader have the same problems. Karen Coyle points out that uncorrected OCR text may be sufficient for searching and corpus analysis, but does not provide a faithful reproduction of the text and thus, for instance, provide access to visually impaired persons 3 This is a problem well known in the digital humanities world, and one solved by projects such as Project Gutenberg with the help of dedicated volunteer distributed proofreaders. Additionally, a great deal of material clearly in the public domain is in manuscript form or has text that modern OCR cannot recognize. In that case, crowdsourcing transcriptions is the only financially viable way for institutions to make text of the material available. 4 Examples of successful projects using volunteer transcriptors or proofreaders include Ancient Lives to transcribe ancient papyrus, What’s on the Menu at the New York Public Library, and DIYHistory at the University of Iowa libraries. (The latter has provided step by step instructions for building your own version using open source tools).

So now you’ve built your low-cost DIY book scanner, and put together a suite of open source tools to help you process your collections for free. Now what? The whole landscape of storing and preserving digital files is far beyond the scope of this post, but the cost of accomplishing this is probably the highest of anything other than staffing a digitization project, and it is here where Google clearly has the advantage. The Internet Archive is a potential solution to storing public domain texts (though they are not immune to disaster), but if you are making in-copyright works available in any capacity you will most likely have to take the risk on your own servers. I am not a lawyer, but I have never rented server space that would allow copyrighted materials to be posted.

Conclusion: Is it Worth It?

Obviously from this post I am in favor of taking on digitization projects of both public domain and copyrighted materials when the motivations are good and the policies are well thought out. From this perspective, I think the Google Books decision was a good thing for libraries and for providing greater access to library collections. Libraries should be smart about what types of materials to digitize, but there are more possibilities for large-scale digitization, and by providing more access, the research community can determine what is useful to them.

If you have managed a DIY book scanning project, please let me know in the comments, and I can add links to your project.

  1. Hellman, Eric. “Google Books and Black-Box Copyright Jurisprudence.” Go To Hellman, November 18, 2013.
  2. Sanz, Amelia. “Digital Humanities or Hypercolonial Studies?” Responsible Innovation in ICT (June 26, 2013).
  3. Coyle, Karen. “It’s FAIR!” Coyle’s InFormation, November 14, 2013.
  4. For more on this, see Ben Brumfield’s work on crowdsourced transcription, for example Brumfield, Ben W. “Collaborative Manuscript Transcription: ‘The Landscape of Crowdsourcing and Transcription’ at Duke University.” Collaborative Manuscript Transcription, November 23, 2013.

Responsibilities For Open Access

In honor of Open Access Week, I want to look at some troubling recent discussions about open access, and what academic librarians who work with technology can do. As the manager of an open access institutional repository, I strongly believe that providing greater access to academic research is a good worth pursuing. But I realize that this comes at a cost, and that we have a responsibility to ensure that open access also means integrity and quality.

On “stings” and quality

By now, the article by John Bohannon in Science has been thoroughly dissected in the blogosphere 1. This was not a study per se, but rather a piece of investigative journalism looking into the practices of open access journals. Bohannon submitted variations on an article written under African pseudonyms from fake universities that “any reviewer with more than a high-school knowledge of chemistry…should have spotted the paper’s short-comings immediately.” Over the course of 10 months, he submitted these articles to 304 open access journals whose names he drew from the Directory of Open Access Journals and Jeffrey Beall’s list of predatory open access publishers. Ultimately 157 of the journals accepted the article and 98 rejected it, when any real peer review would have meant that it was rejected in all cases. It is very worth noting that in an analysis of the raw data that Bohannon supplied some publishers on Beall’s list rejected the paper immediately, which is a good reminder to take all curative efforts with an appropriate amount of skepticism 2.

There are certainly many methodological flaws in this investigation, which Mike Taylor outlines in detail in his post 3, and which he concludes was specifically aimed at discrediting open access journals in favor of journals such as Science. As Michael Eisen outlinesScience has not been immune to publishing articles that should have been rejected after peer review–though Bohannon informed Eisen that he intended to look at a variety of journals but this was not practical, and this decision was not informed by editors at Science. Eisen’s conclusion is that “peer review is a joke” and that we need to stop regarding the publication of an article in any journal as evidence that the article is worthwhile 4. Phil Davis at the Scholarly Kitchen took issue with this conclusion (among others noted above), since despite the flaws, this did turn up incontrovertible evidence that “a large number of open access publishers are willfully deceiving readers and authors that articles published in their journals passed through a peer review process…” 5. His conclusion is that open access agencies such as OASPA and DOAJ should be better at policing themselves, and that on the other side Jeffrey Beall should be cautious about suggesting a potential for guilt without evidence. I think one of the more level-headed responses to this piece comes from outside the library and scholarly publishing world in Steven Novella’s post on Neurologica, a blog focused on science and skepticism written by an academic neurologist. He is a fan of open access and wider access to information, but makes the point familiar to all librarians that the internet creates many more opportunities to distribute both good and bad information. Open access journals are one response to the opportunities of the internet, and in particular author-pays journals like “all new ‘funding models’ have the potential of creating perverse incentives.” Traditional journals fall into the same trap when they rely on impact factor to drive subscriptions, which means they may end up publishing “sexy” studies of questionable validity or failing to publish replication studies which are the backbone of the scientific method–and in fact the only real way to establish results no matter what type of peer review has been done 6.

More “perverse incentives”

So far the criticisms of open access have revolved around one type of “gold” open access, wherein the author (or a funding agency) pays article publication fees. “Green” open access, in which a version of the article is posted in a repository is not susceptible to abuse in quite the same way. Yet a new analysis of embargo policies by Shan Sutton shows that some publishers are targeting green open access through new policies. Springer used to have a 12 month embargo for mandated deposit in repositories such as PubMed, but now has extended it to all institutional repositories. Emerald changed its policy so that any mandated deposit to a repository (whether by funder or institutional mandate) was subject to a 24 month embargo  7.

In both cases, paid immediate open access is available for $1,595 (Emerald) or $3,000 (Springer). It seems that the publishers are counting that a “mandate” means that funds are available for this sort of hyrbid gold open access, but that ignores the philosophy behind such mandates. While federal open access mandates do in theory have a financial incentive that the public should not have to pay twice for research, Sutton argues that open access “mandates” at institutions are actually voluntary initiatives by the faculty, and provide waivers without question 8. Additionally, while this type of open access does provide public access to the article, it does not address larger issues of reuse of the text or data in the true sense of open access.

What should a librarian do?

The issues above are complex, but there are a few trends that we can draw on to understand our responsibilities to open access. First, there is the issue of quality, both in terms of researcher experience in working with a journal, and that of being able to trust the validity of an individual article. Second, we have to be aware of the terms under which institutional policies may place authors. As with many such problems, the technological issues are relatively trivial. To actually address them meaningfully will not happen with technology alone, but with education, outreach, and network building.

The major thing we can take away from Bohannon’s work is that we have to help faculty authors to make good choices about where they submit articles. Anyone who works with faculty has stories of extremely questionable practices by journals of all types, both open access and traditional. Speaking up about those practices on an individual basis can result in lawsuits, as we saw earlier this year. Are there technical solutions that can help weed out predatory publishers and bad journals and articles? The Library Loon points out that many factors, some related to technology, have meant that both positive and negative indicators of journal quality have become less useful in recent years. The Loon suggests that “[c]reating a reporting mechanism where authors can rate and answer relatively simple questions about their experiences with various journals seems worthwhile.” 9

The comments to this post have some more suggestions, including open peer review and a forum backed by a strong editor that could be a Yelp-type site for academic publisher reputation. I wrote about open peer review earlier this year in the context of PeerJ, and participants in that system did indeed find the experience of publishing in a journal with quick turnarounds and open reviews pleasant. (Bohannon did not submit a fake article to PeerJ). This solution requires that journals have a more robust technical infrastructure as well as a new philosophy to peer review. More importantly, this is not a solution librarians can implement for our patrons–it is something that has to come from the journals.

The idea that seems to be catching on more is the “Yelp” for scholarly publishers. This seems like a good potential solution, albeit one that would require a great deal of coordinated effort to be truly useful. The technical parts of this type of solution would be relatively easy to carry out. But how to ensure that it is useful for its users? The Yelp analog may be particularly helpful here. When it launched in 2004, it asked users who were searching for some basic information about their question, and to provide the email addresses of additional people whom they would have traditionally asked for this information. Yelp then emailed those people as well as others with similar searches to get reviews of local businesses to build up its base of information. 10 Yelp took a risk in pursuing content in that way, since it could have been off-putting to potential users. But local business information was valuable enough to early users that they were willing to participate, and this seems like a perfect model to build up a base of information on journal publisher practices.

This helps address the problem of predatory publishers and shifting embargoes, but it doesn’t help as much with the issue of quality assurance for the article content. Librarians teach students how to find articles that claim to be peer reviewed, but long before Bohannon we knew that peer review quality varies greatly, and even when done well tells us nothing about the validity of the research findings. Education about the scholarly communication cycle, the scientific method, and critical thinking skills are the most essential tools to ensure that students are using appropriate articles, open access or not. However, those skills are difficult to bring to bear for even the most highly experienced researchers trying to keep up with a large volume of published research. There are a few technical solutions that may be of help here. Article level metrics, particularly alternative metrics, can aid in seeing how articles are being used. (For more on altmetrics, see this post from earlier this year).

One of the easiest options for article level metrics is the bookmarklet. This provides article level metrics for many articles with a DOI, or articles from PubMed and arXiv. offers an API with a free tier to develop your own app. An open source option for article level metrics is PLOS’s Article-Level Metrics, a Ruby on Rails application. These solutions do not guarantee article quality, of course, but hopefully help weed out more marginal articles.

No one needs to be afraid of open access

For those working with institutional repositories or other open access issues, it sometimes seems very natural for Open Access Week to fall so near Halloween. But it does not have to be frightening. Taking responsibility for thoughtful use of technical solutions and on-going outreach and education is essential, but can lead to important changes in attitudes to open access and changes in scholarly communication.



  1. Bohannon, John. “Who’s Afraid of Peer Review?” Science 342, no. 6154 (October 4, 2013): 60–65. doi:10.1126/science.342.6154.60.
  2. “Who Is Afraid of Peer Review: Sting Operation of The Science: Some Analysis of the Metadata.” Scholarlyoadisq, October 9, 2013.
  3. Taylor, Mike. “Anti-tutorial: How to Design and Execute a Really Bad Study.” Sauropod Vertebra Picture of the Week. Accessed October 17, 2013.
  4. Eisen, Michael. “I Confess, I Wrote the Arsenic DNA Paper to Expose Flaws in Peer-review at Subscription Based Journals.” It Is NOT Junk, October 3, 2013.
  5. Davis, Phil. “Open Access ‘Sting’ Reveals Deception, Missed Opportunities.” The Scholarly Kitchen. Accessed October 17, 2013.
  6. Novella, Steven. “A Problem with Open Access Journals.” Neurologica Blog, October 7, 2013.
  7. Sutton, Shan C. “Open Access, Publisher Embargoes, and the Voluntary Nature of Scholarship: An Analysis.” College & Research Libraries News 74, no. 9 (October 1, 2013): 468–472.
  8. Ibid., 469
  9. Loon, Library. “A Veritable Sting.” Gavia Libraria, October 8, 2013.
  10. Cringely, Robert. “The Ears Have It.” I, Cringely, October 14, 2004.

An Experiment with Publishing on GitHub

Scholarly publishing, if you haven’t noticed, is nearing a crisis. Authors are questioning the value added by publishers. Open Access publications are growing in number and popularity. Peer review is being criticized and re-invented. Libraries are unable to pay price increases for subscription journals. Traditional measures of scholarly impact and journal rankings are being questioned while new ones are developed. Fresh business models or publishing platforms appear to spring up daily.1

I personally am a little frustrated with scholarly publishing, albeit for reasons not entirely related to the above. I find that most journals haven’t adapted to the digital age yet and thus are still employing editorial workflows and yielding final products suited to print.

How come I have yet to see a journal article PDF with clickable hyperlinks? For that matter, why is PDF still the dominant file format? What advantage does a fixed-width format hold over flexible, fluid-width HTML?2 Why are raw data not published alongside research papers? Why are software tools not published alongside research papers? How come I’m still submitting black-and-white charts to publications which are primarily read online? Why are digital-only publications still bound to regular publication schedules when they could publish like blogs, as soon as the material is ready? To be fair, some journals have answered some of these questions, but the issues are still all too frequent.

So, as a bit of an experiment, I recently published a short research study entirely on GitHub.3 I included the scripts used to generate data, the data, and an article-like summary of the whole process.

What makes it possible

Unfortunately, I wouldn’t recommend my little experiment for most scholars, except perhaps for pre- or post-prints of work published elsewhere. Why? The primary reason people publish research is for tenure review, for enhancing a CV. I won’t list my study—though, arguably, I should be able to—simply because it didn’t go through the usual scholarly publishing gauntlet. It wasn’t peer-reviewed, it didn’t appear in a journal, and it wouldn’t count for much in the eyes of traditional faculty members.

However, I’m at a community college. Research and publication are not among my position’s requirements. I’m judged on my teaching and various library responsibilities, while publications are an unnecessary bonus. Would it help to have another journal article on my CV? Yes, probably. But there’s little pressure and personally I’m more interested in experimentation than in lengthening my list of publications.

Other researchers might also worry about someone stealing their ideas or data if they begin publishing an incomplete project. For me, again, publication isn’t really a competitive field. I would be happy to see someone reuse my project, even if they didn’t give proper attribution back. Openness is an advantage, not a vulnerability.

It’s ironic that being at a non-research institution frees me up to do research. It’s done mostly in my free-time, which isn’t great, but the lack of pressure means I can play with modes of publication, or not worry about the popularity of journals I submit to. To some degree, this is indicative of structural problems with scholarly publishing: there’s inertia in that, in order to stay in the game and make a name for yourself, you can’t do anything too wild. You need to publish, and publish in the recognized titles. Only tenured faculty, who after all owe at least some of their success to the current system, can risk dabbling with new publishing models and systems of peer-review.

What’s really good

GitHub, and the web more generally, are great mediums for scholarship. They address several of my prior questions.

For one, the web is just as suited to publishing data as text. There’s no limit on file format or (practically) size. Even if I was analyzing millions of data points, I could make a compressed archive available for others to download, verify, and reuse in their own research. For my project, I used a Google Spreadsheet which allows others to download the data or simply view it on the web. The article itself can be published on GitHub Pages, which provides free hosting for static websites.

article on GitHub pages

Here’s how the final study looks when published on GitHub Pages.

While my study didn’t undergo any peer review, it is open for feedback via a pull request or the “issues” queue on GitHub. Typically, peer review is a closed process. It’s not apparent what criticisms were leveled at an article, or what the authors did to address them. Having peer review out in the open not only illuminates the history of a particular article but also makes it easier to see the value being added. Luckily, there are more and more journals with open peer review, such as PeerJ which we’ve written about previously. When I explain peer review to students, I often open up the “Peer Review history” section of a PeerJ article. Students can see that even articles written by professional researchers have flaws which the reviewing process is designed to identify and mitigate.

Another benefit of open peer review, present in publishing on GitHub too, is the ability to link to specific versions of an article. This has at least two uses. First of all, it has historical value in that one can trace the thought process of the researcher. Much like original manuscripts are a source of insight for literary analyses, merely being able to trace the evolution of a journal article enables new research projects in and of itself.

Secondly, as web content can be a moving target as it is revised over time, being able to link to specific versions aids those referencing a work. Linking to a git “commit” (think a particular point in time), possibly using or the Internet Archive to store a copy of the project as it existed then, is an elegant way of solving this problem. For instance, at one point I manually removed some data points which were inappropriate for the study I was performing. One can inspect the very commit where I did this, seeing which lines of text were deleted and possibly identifying any mistakes which were made.

I’ve also grown tired of typical academic writing. The tendency to value erudite over straightforward language, lengthy titles with the snarky half separated from the actually descriptive half by a colon, the anxiety about the particularities of citations and style manuals; all of these I could do without. Let’s write compelling, truthful content without fetishizing consistency and losing the uniqueness of our voice. I’m not saying my little study achieves much in this regard, but it was a relief to be free to write in whatever manner I found most suitable.

Finally, and most encouraging in my mind, the time to publication of a research project can be greatly reduced with new web-based means. I wrote a paper in graduate school which took almost two years to appear in a peer-reviewed journal; by the time I was given the pre-prints to review, I’d entirely forgotten about it. On GitHub, all delays were solely my fault. While it’s true (you can see so in the project’s history) that the seeds of this project were planted nearly a year ago, I started working in earnest just a few months ago and finished the writing in early October.

What’s really bad

GitHub, while a great company which has reduced the effort needed to use version control with its clean web interface and graphical applications, is not the most universally understood platform. I have little doubt that if I were to publish a study on my blog, I would receive more commentary. For one, GitHub requires an account which only coders or technologists would be likely to have already, while many comment platforms (like Disqus) build off of common social media accounts like Twitter and Facebook. Secondly, while GitHub’s “pull requests” are more powerful than comments in that they can propose changes to the actual content of a project, they’re doubtless less understood as well. Expecting scholarly publishing to suddenly embrace software development methodologies is naive at best.

As a corollary to GitHub’s rather niche appeal, my article hasn’t undergone any semblance of peer review. I put it out there; if someone spots an inaccuracy, I’ll make note of and address it, but no relevant parties will necessarily critique the work. While peer review has its problems—many intimate with the problems of scholarly publishing at large—I still believe in the value of the process. It’s hard to argue a publication has reached an objective conclusion when only a single pair of eyes have scrutinized it.

Researchers who are afraid of having their work stolen, or of publishing incomplete work which may contain errors, will struggle to accept open publishing models using tools like GitHub. Prof Hacker, in an excellent post on “Forking the Academy”, notes many cultural challenges to moving scholarly publishing towards an open source software model. Scholars may worry that forking a repository feels like plagiarism or goes against the tradition of valuing original work. To some extent, these fears may come more from misunderstandings than genuine problems. Using version control, it’s perfectly feasible to withhold publishing a project until it’s complete and to remove erroneous missteps taken in the middle of a work. Theft is just as possible under the current scholarly publishing model; increasing the transparency and speed of one’s publishing does not give license to others to take credit for it. Unless, of course, one uses a permissive license like the Public Domain.

Convincing academics that the fears above are unwarranted or can be overcome is a challenge that cannot be overstated. In all likelihood, GitHub as a platform will never be a major player in scholarly publishing. The learning curve, both technical and cultural, is simply too great. Rather, a good starting point would be to let the appealing aspects of GitHub—versioning, pull requests, issues, granular attribution of authorship at the commit level—inform the development of new, user-friendly platforms with final products that more closely resemble traditional journals. Prof Hacker, again, goes a long way towards developing this with a wish list for a powerful collaborative writing platform.

What about the IR?

The discoverability of web publications is problematic. While I’d like to think my research holds value for others’ literature reviews, it’s never going to show up while searching in a subscription database. It seems unreasonable to ask researchers, who already look in many places to compile complete bibliographies, to add GitHub to their list of commonly consulted sources. Further fracturing the scholarly publishing environment not only inconveniences researchers but it goes against the trend of discovery layers and aggregators (e.g. Google Scholar) which aim to provide a single search across multiple databases.

On the other hand, an increasing amount of research‐from faculty and students alike—is conducted through Google, where GitHub projects will appear alongside pre-prints in institutional repositories. Simply being able to tweet out a link to my study, which is readable on a smartphone and easily saved to any read-it-later service, likely increases its readership over stodgy PDFs sitting in subscription databases.

Institutional repositories solve some, but not all, of the deficiencies of publishing on GitHub. Discoverability is increased because researchers at your institution may search the IR just like they do subscription databases. Futhermore, thanks to the Open Archives Initiative and the OAI-PMH standard, content can be aggregated from multiple IRs into larger search engines like OCLC’s OAIster. However, none of the major IR software players support versioned publication. Showing work-in-progress, linking to specific points in time of a work, and allowing for easy reuse are all lost in the IR.

Every publication in its place

As I’ve stated, publishing independently on GitHub isn’t for everyone. It’s not going to show up on your CV and it’s not necessarily going to benefit from the peer review process. But plenty of librarians are already doing something similar, albeit a bit less formal: we’re writing blog posts with original research or performing quick studies at our respective institutions. It’s not a great leap to put these investigations under version control and then publish them on the web. GitHub could be a valuable compliment to more traditional venues, reducing the delay between when data is collected and when it’s available for public consumption. Furthermore, it’s not at all mutually exclusive with article submissions. One could gain both the immediate benefit of getting one’s conclusions out there, but also produce a draft of a journal article.

As scholarly publishing continues to evolve, I hope we’ll see a plethora of publishing models rather than one monolithic process replacing traditional print-based journals. Publications hosted on GitHub, or a similar platform, would sit nicely alongside open, web-based publications like PeerJ, scholarly blog/journal hybrids like In The Library with the Lead Pipe, deposits in Institutional Repositories, and numerous other sources of quality content.


  1. I think a lot of these statements are fairly well-recognized in the library community, but here’s some evidence: the recent Open Access “sting” operation (which we’ll cover more in-depth in a forthcoming post) that exposed flaws in some journals’ peer review process, altmetrics, PeerJ, other experiments with open peer review (e.g. by Shakespeare Quarterly), the serials crisis (which is well-known enough to have a Wikipedia entry), predictions that all scholarship will be OA in a decade or two, and increasing demands that scholarly journals allow text mining access all come to mind.
  2. I’m totally prejudiced in this matter because I read primarily through InstaPaper. A journal like Code4Lib, which publishes in HTML, is easy to send to read-it-later services, while PDFs aren’t. PDFs also are hard to read on smartphones, but they can preserve details like layout, tables, images, and font choices better than HTML. A nice solution is services which offer a variety of formats for the same content, such as Open Journal Systems with its ability to provide HTML, PDF, and ePub versions of articles.
  3. For non-code uses of GitHub, see our prior Tech Connect post.

Digital Content: Who May Publish? Who May Sell? Who May Access?

No matter whether a small university press focusing on niche markets to the Big Six giants looking for the next massive bestseller, the publishing industry has been struggling to come to terms with the reality of new distribution models. Those models tends to favor cheaper and faster production with a much lower threshold for access, which generally has been good news for consumers. Several recent rulings and  statements have brought the issues to the forefront of conversation and perhaps indicated some common themes in publishing which are relevant to all libraries and their ability to purchase and/or provide digital content.

Academic Publishing: Dissertation == Monograph?

On July 22 the American Historical Association issued a “Statement on Policies Regarding the Embargoing of Completed History PhD Dissertations”. In this statement, the American Historical Association recommended that all libraries and graduate programs allow dissertations to be embargoed for up to six years. This is, in theory, to allow junior scholars enough time to publish a monograph based on the dissertation in order to receive tenure. This would be under the assumption that academic publishers would not publish a book based on a dissertation freely available online. Reactions to this statement prompted the AHA to release a Q & A page to clarify and support their position, including pointing out that publishers’ positions are too unclear to be sure there is no risk to an open access dissertation, and “like it or not”, junior faculty must produce a monograph to get tenure. They claim that in some cases that this benefits junior scholars to give them more time to revise their work before publication–while this is true, it indicates that a dissertation is not equivalent to a published scholarly monograph. The argument from the publisher’s side appears to be that libraries (who are the main purchasers of scholarly monographs) will not purchase books based on revised dissertations freely available online, the truth of which has been debated widely. Libraries do purchase print copies of titles (both monographs and serials) which are freely available online.

From my personal experience as an institutional repository manager, I know the attitude to embargoing dissertations varies widely by advisor and department. Like most people making an argument about this topic, I do not have much more than anecdotes to provide. I checked the most commonly downloaded dissertations from the past year, and it appeared the most frequently downloaded title (over 2000 over 2012-2013) is also the only one that has been published as a book that has been purchased by at least one library. Clearly this does not control for all variables and warrants further study, but it is a useful clue that open access availability does not always affect publication and later purchase. Further, from the point of view of open access creating more equal access to resources across the world, Google Analytics for that dissertation indicates that the sessions over the past year with the most engaged users came from, in order, the UK, the United States, Mauritius, and Sri Lanka.

What Should a Digital Book Cost?

In mid-July Denise Cote, the judge in the Apple e-book price fixing case, issued an opinion stating that Apple did collude with the publishers to set prices on ebooks. Reading the story of the negotiations in the opinion is a thrilling behind the scenes look at companies trying to get a handle on a fairly new market and trying to understand how they will make money. Below I summarize the 160 page opinion, which is well worth reading in its entirety.

The  problem with ebook pricing started with Amazon, which set a price of $9.99 for new releases that normally would have had list prices of $25-$30. This was frustrating to the major publishing houses, who worried (probably rightly so) that consumers would be unwilling to pay more than $10 for books after getting used to this low price point. Amazon would effectively price everyone else out of the market. Even after publishers raised the wholesale price of new releases, Amazon would sell them at loss to preserve the $9.99 price. The publishers spent 2009 developing strategies to combat Amazon, but it wasn’t until late 2009 with the entry of Apple into the ebook market that they saw a real opportunity.

Apple agreed with the Big Six publishers that setting all books at $9.99 was too low, but was unwilling to enter into a market in which they could not compete with Amazon. To accomplish this, they wanted the publishers to agree to the same terms, which included lower wholesale prices for ebooks. The negotiations that followed over late 2009 and early 2010 started positively, but ended in dissatisfaction. Because Apple was unwilling to sell anything as a loss leader, they felt that a wholesale model would leave them too vulnerable to Amazon. To address that, they proposed to sell books with an agency model (which several publishers had suggested). With an agency model, Apple would collect a 30% commission on sales just as they did with the App Store. To ensure that publishers did not set unrealistically high prices, Apple would set pricing caps. The other crucial move that Apple made was to insist that publishers move all retailers of ebooks to the agency model in order to ensure Apple would be able to compete on price across the board. Amazon  had no interest in the agency model, and in early 2010 had a series of meeting with the publishers that made this clear. After all the agreements were signed with Apple (the only Big Six publisher who did not participate was Random House), the publishers needed to move Amazon to an agency model to fulfill the terms of their contract. Macmillan was the first publisher to set up a meeting with Amazon to discuss this requirement. The response to the meeting was for Amazon to remove the “buy” button from all Macmillan books, both print and Kindle editions. Amazon eventually had to capitulate to the publishers to move to an agency model, which was complete by mid-2010, but submitted a complaint to the Federal Trade Commission. Random House finally agreed to an agency model with Apple in early 2011, thanks to a spot of blackmail on Apple’s part (it wouldn’t allow any Random House apps without a agency deal).

Ultimately the court determined that Apple violated the Sherman Act by conspiring with the publishers to force all their retailers to sell books at the same prices and thus removing competition. A glance at Amazon’s Kindle store bestsellers today shows books priced from $1.99 to $13.99 for the newest Stephanie Plum mystery (the same price as it is in the Apple bookstore). For all titles priced higher than $9.99, Amazon notes that the “price is set by the publisher.” Whether this means anything to the average consumer is debatable. Compare these negotiations to the on-going struggle libraries have had with availability of ebooks for lending–publishers have a lot to learn about libraries in addition to new models for digital sales, some of which was covered at the series of talks with the Big Six publishers that Maureen Sullivan held in early 2012. Over recent months publishers have made more ebooks available to libraries. But some libraries, most notably the Douglas County, Colorado libraries, are setting their own terms for purchasing and lending ebooks.

What Can You Do With a Digital File?

The last ruling I want to address is about the music resale service ReDigi, about which Kevin Smith goes into detail. This was was a service that provided a way for people to re-sell purchased MP3s, but ultimately the judge ruled that it was impossible to transfer the original file and so this did not fit under the first sale doctrine. The first sale doctrine (17 USC § 109) holds that “the owner of a particular copy or phonorecord lawfully made … is entitled, without the authority of the copyright owner, to sell or otherwise dispose of the possession of that copy or phonorecord.” Another case that was decided in April by the Supreme Court, Kirtsaeng v. Wiley, upheld this in the case of international sales of physical items, which was an important decision for libraries. But digital materials are more complicated. First sale applies to computer programs on physical media (except in certain circumstances), but does not cover material that has been licensed rather than sold, which is how most digital files are distributed. (For how the US Attorney’s Office approaches this in criminal investigations, see this document.) So when you “buy” that Kindle book from Amazon or load a book onto your iPad you are licensing the product for limited use on a limited number of devices and no legal recourse for lending or getting rid of the content, even if you try hard to follow the law as ReDigi did. Librarians are well aware of this and its implications, and license quite a bit of content that we can loan and/or distribute under limited circumstances. Libraries are safest in the long term if they can own the content outright rather than licensing, as are consumers. But it will be a long time before there is clarity about the legal way to transfer owner of a digital file at the consumer level.


Librarians and publishers have a complicated relationship. We need each other if either is to succeed, but even if our ends are the ultimately the same, our means are very different. These recent events indicate that there is still much in flux and plenty of room for constructive dialog with content creators and publishers.

Citation Manager Roundup

In April of this year, the two most popular free citation managers–Mendeley and Zotero–both underwent some big changes. On April 8th, TechCrunch announced that Elsevier had purchased Mendeley, which had been surmised in January. 1 Just a few days later, Zotero announced the release of version 4, with a number of new features. 2 Just as with the sunsetting of Google Reader, this has prompted many to consider what citation managers they have been using and think about switching or changing practices. I will not address subscription or paid products like RefWorks and EndNote specifically, though there are certainly many reasons you might prefer one of those products.

Mendeley: a new Star Wars movie in the making?

The rhetoric surrounding Elsevier’s acquisition of Mendeley was generally alarmist in nature, and the hashtag “#mendelete” that popped up immediately after the announcement suggests that many people’s first instinct was to abandon Mendeley. Elsevier has been held up as a model of anti-open access, and Mendeley as a model for open access. Yet Mendeley has always been a for-profit company, and, like Google, benefits itself and its users (particularly the science community) by knowing what they are reading and sharing. After all, the social features of Mendeley wouldn’t have any value if there was no public sharing. Institutional Mendeley accounts allow librarians to see what their users in aggregate are reading and saving, which helps them make collection development decisions– a service beyond what the average institutional citation manager product accomplishes. Victor Henning promises on the Mendeley blog that nothing will change, and that this will give them more freedom to develop more features 3. As for Elsevier, Oliver Dumon promises that Mendeley will remain independent and allowed to follow their own course–and that bringing it together with ScienceDirect and Scopus will create a “central workflow and collaboration site for authors”.4

There are two questions to be answered in this. First, is it realistic to assume that the Mendeley team will have the creative freedom they say they will have? And second, are users comfortable with their data being available to Elsevier? For many, the answers to both these questions seem to be “no” and “no.” A more optimistic point of view is that if Elsevier must placate Mendeley users who are open access advocates, they will allow more openness than before.

It’s too early to say, but I remain hopeful that Mendeley can continue to create a more open spirit in academic publishing. Peter Hoyt (a former employee of Mendeley and founder of PeerJ) suggests that much of the work that he oversaw to open up Mendeley was being stymied by Elsevier specifically. For him, this went against his personal ethos and so he was unable to stay at Mendeley–but he is confident in the character and ability of the people remaining at Mendeley.  5. I have never been a heavy user of Mendeley, but I have maintained a free account for the past few years. I use it mainly to create a list of my publications on my personal website, using a WordPress plug-in that uses the Mendeley API.

What’s new with Zotero

Zotero is a very different product than Mendeley. First, it is open-source software, with lots of ways to participate in development. Zotero was developed by the Roy Rosenzweig Center for History and New Media at George Mason University, with foundation and user support. It was developed specifically to support the research work of humanists. Originally a Firefox plug-in, Zotero now works as a standalone piece of software that interacts with Firefox, Chrome, and Safari to recognize bibliographic data on websites and pull them into a database that can be synced across computers (and even some third party mobile software). The newest version of Zotero includes several improvements. The one I am most excited about is detailed download display, which tells you what folder you’re saving a reference into, which is crucial for my workflow. Zotero is the citation manager I use on a daily basis, and I rely on it for formatting the footnotes you see on ACRL TechConnect posts or other research articles I produce. Since much of my research is on the open web, books, or other non-journal article resources, I find the ability of Zotero to pick up library catalog records and similar metadata more useful than the Mendeley import bookmarklet.

Both Zotero and Mendeley offer free storage for metadata and PDFs, with a cost for storage above the free level. (It is also possible to use a WebDAV server for syncing Zotero files).

Zotero Mendeley
300 MB Free
2 GB $20 / year 2 GB Free
6 GB $60 / year 5 GB $55 / year
10 GB $100 / year 10 GB $110 / year
25 GB $240 / year Unlimited $165 / year
Some concluding thoughts

Several graduate students in science 6 have written blog posts about switching away from Mendeley to Zotero. But they aren’t the same thing at all, and given the backgrounds of their creators, Mendeley is more skewed to the sciences, and Zotero more to the humanities.

Nor, as I like to point out, must they be mutually exclusive. I use Zotero for my daily citation management since I much prefer it for grabbing citations online, but sync my Zotero library with Mendeley to use the social and API features in Mendeley. I can choose to do this as an individual, but consider carefully the implications of your choice if you are considering an institutional subscription or requiring students or members of a research group to use a particular service.

  1. Lunden, Ingrid. “Confirmed: Elsevier Has Bought Mendeley For $69M-$100M To Expand Its Open, Social Education Data Efforts.” TechCrunch, April 18, 2013.
  2. Takats, Sean. “Zotero 4.0 Launches.” Zotero, April 11, 2013.
  3. Henning, Victor. “Mendeley and Elsevier – Here’s More Info.” Mend, April 19, 2013.
  4. Dumon, Oliver. “Elsevier Welcomes Mendeley.” Elsevier Connect, April 8, 2013.
  5. Hoyt, Jason. “My Thoughts on Mendeley/Elsevier & Why I Left to Start PeerJ,” April 9, 2013.
  6. For one, see “Mendeley Sells Out; I’m Moving to Zotero.” LJ Villanueva’s Research Blog. Accessed May 20, 2013.