Data Papers are Witness to Trusted Resources in Grey Literature: Driving Access to Data thru Public Awareness
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Farace, Dominic
Frantzen, Jerry
Smith, Plato L.
In 2011, GreyNet embarked on an Enhanced Publications Project with DANS, Data Archiving and Networked Services in an effort to circumvent the data versus document camps entrenched in grey literature communities. The results of that two year project served to incorporate in GreyNet’s workflow the acquisition, indexing, and linking of research data with their full-text and accompanying metadata. Recently, GreyNet discussed with a data management librarian from UFL, University of Florida a proposed follow-up project dealing with data papers – a new document type within grey literature. Data papers are defined as scholarly publications of a searchable metadata document describing a particular online accessible dataset or a group of datasets published in accordance to standard academic practices. As such, data papers represent a scholarly communication approach to data sharing. The outcome of that discussion has led to the formation of a project team with the twofold purpose of producing and publishing a set of data papers originating in the field of grey literature, and in so doing raise awareness to this new document type by demonstrating its value for library and information science. The method of approach includes the construction of an online standardized template that encompasses a data paper, defining the population asked to complete the template, instruction and further contact with the authors/researchers during the course of the project, along with an analysis of the results. While there are no direct costs associated with this project, each of the partners is committed to allocate human and material resources needed to carry out their related tasks. The anticipated outcome of the project would provide a tested template that could be used by other grey literature communities in the production of data papers. It would demonstrate how OA, DSA and FAIR principles are implemented and reinforced via data papers. And, it would further provide examples of how data citations can generate trusted bibliographic references.
 Thank you very much. Interesting, the first two speakers exposing great literature to wider audiences and one through a means of training and education and another with automation. And I have another way of exposing great literature to wider audiences, hopefully. A few years ago, I heard about the term data papers. And as with all developments in the field of information, I began to think how are data papers related to great literature and how is an organization incorporate them in and among its own resources. What sparked my initiative or initial initiative was that data papers were a new document type of great literature. And that they had a place within Green Nets on-going enhanced publications project, which was dated back to 2011. So in early April of this year, I had the opportunity to attend a meeting in Barcelona where Peter Dorn, director of the Don's Data Archive in the Netherlands, presented a presentation on fair data principles. I hadn't heard of the term before. But there was a moment of inspiration for myself. I made a hypothesis that data papers were one of the most tangible means of finding the fair data principles. And with that, I then returned quickly back to Amsterdam, very excited about the prospects, and I phoned Plato Smith. And Plato is a data management librarian at the University of Florida who was at last year's conference, GL18 in New York. I knew I could always talk on Jerry, there he is, for the technical support needed as well as the on-going support by the Don's Data Archive, where Green Nets data collection has been housed and is housed. However, the insight and expertise of a data management librarian such as Plato was imperative in this project, Stands or Falls. Within a week and just under the wire of closing the GL19 call for papers, I held to that myself, our proposal was written up and submitted to the GL19 program committee. My presentation on behalf of our project team is quite straightforward. In other words, a long introduction, but the remainder of the presentation will be straightforward. It reflects on the work over the past six months, or should I say, the first six months of Green Nets data papers project. The presentation briefly looks at a definition of data papers, the background of the project, developments of Green Nets data collection, the instrument of a data paper template, the population of this project in terms of data sets, the review process of data papers, the publication of Green Nets data papers, some early project results, and a spin-off, a little extra, in New Orleans they call it Lanyap. Something extra was from the initial data papers project, something unexpected. The final will be what is the follow-up to this project. Great. Okay. A definition that I pulled out was from WikiP. The scholarly publications of a searchable metadata document describing a particular online accessible data set or group of data sets published in accordance to standard academic practices. The background of this particular, as I mentioned in the introduction, was that we had an enhanced publications project going, it was ongoing. The project of data papers is added or comes within the enhanced publications project. And that project, that is the definition described by the driver, is that a publication that is enhanced with three categories of information, materials, and post-publication data. Further, it combines textual resources, that is documents intended to be read by human beings, which contain an interpretation or analysis of primary data, and enhanced publications inherently contribute to the review process of great literature, as well as the replication of research and improved visibility of research results in the scholarly communication chain. So it was, for me, the data paper project fit as a glove within the enhanced publications project. In 2011, again with Don's data archive, we had a survey. The survey was a number of questions using a survey monkey. We asked, we had a population of our authors, researchers within the great net community, going back to 1993, of that there were 95 of the 300 or more authors that were selected for this population. And the 50 of the 95 answered the questionnaire. And it was basically, are you prepared, what are your attitudes, are you prepared to share your research data? We're talking about 2011. So, I mean, that was pretty good. The response was positive. At least 50% of those who were surveyed were willing to share their data, whether they were willing to share it within the Don's data archive, or within one of their own national data archives, that was something to be further discussed. But what we did immediately the next year, in 2012, we said, okay, let's move on to the data acquisition, the publication of the data sets in the Don's data archive, and incorporate this into a workflow, great net workflow, and that is the workflow actually of the GL conference series. The results being also that we wanted to link the data to existing records that were not only in the Don's data archive, but were also in the Open Grade archive, which you're very familiar with, where all of great net content is made accessible. From 2012 on, we have been, it's in the workflow, and we have now accomplished in by 2017, 30 data sets, 30 sets of data that are in and published in the Don's data archive. It doesn't sound like a lot, but it certainly was for us representative, and it was the inspiration for this leg of the Enhanced Publications Project, the Data Papers Project. The next step, or should I say one of the first steps, was a tool, an instrument in which the data papers could be, we didn't want to develop the wheel for data papers because it's been around for a number of years, but we wanted to streamline it for the great literature community, and for great net community. So we went out, found three templates that would, you can find many more, but we took three, the research data journal from, which is in the Netherlands, the Journal of Open Humanities data, and the Journal of Open Psychology data. And we looked at those templates, and then we took from them much, but we thought it was important that when you're asking a researcher or an author, certainly one who has had done a data set, created a data set five years prior, and you're asking them retrospectively to create a data paper, which you need to do is to make sure that the note fields that are in the template in this instrument, that they are sufficient and clear, and they also give examples that can be used so that it facilitates the implementation of and creation of the data template. The data template is not the end, the template is actually the model that is used in order to create the final data paper. Now, we have this, as I mentioned, we had a population of 30 sets of data, and from this we were able to constitute that 15 authors or researchers were first authors or sole authors to the data that was in the Don's, the great net's collection in Don's. So what we did was we sent out then the data template, we sent out the hour, that is our team, our data papers team, our example of what we created a data paper, and we asked them their willingness, these 15 authors, researchers, their willingness to write a data paper. So unexpectedly, 24 hours after the first request, we got Daniela Aloya and Aouton from New York Academy of Medicine immediately came back and said, yes, we're going to submit a data paper. And then we came, and so actually what happened was in a very short period of time we had, and I think, oh no no no no, you're right, you're right, okay. And I said it was going to be straightforward, but I'm not, I just lied, okay. So what we did was we have now five data papers were on the way, and I do want to mention that there is a review process, all great literature, whether it's data or whether it's full text or whether it's bibliographic, metadata has to be in some way reviewed, and we have a review process. There will be a paper on this explanation, a data paper that is submitted and published first in the Don's data archive is something which you can call a preprint, and when, and it is scheduled once it is accepted by our data management library, it is then eligible for publication as a data article in the Great Journal. Promotion, Great Journal, two data articles in the autumn issue of the Great Journal, and we're very happy that this could happen prior to this conference today. The results of that paper project, the template has been compiled, edited, the six authors have indicated interest, I already told you that there was eight, five have been published. The data papers is now a term as a document type within the Gray Source Index, and you would say, well, the Gray Source Index, what is that? It's a web page on GrayNet's website, and it gives 100 document types of great literature, but it is the most trafficked web page that GrayNet has. It's unbelievable, and it's a very simplest one, but it's the most trafficked one. And of course, data papers is one of the 15 points of the PISA Declaration on, it supports the PISA Declaration on Policy for Great Literature. Spin off, I think I have a minute, spin off is that in the Great Journal, the GL Conference Series, and the GL Conference Series, this was the population for the data sets, but there are other articles that are coming into the Great Journal that were never in the series. So we went to those that were not in GL, and we asked, are they willing, and already to have acknowledged that they are starting to work on the data paper. So it's, for us, great. And then the final spin off is that seeing if we're going to go further with this, and certainly within the workflow, we have to have perhaps a workshop, a training on the creation of data papers. And we are going to have a test, a pilot of this workshop at the University of Florida. They will be hosting this. Follow up to the project, we're just getting started, it's only six months. It's got to be implemented in the workflow, not only of the conference series, but also of the journal, the Great Journal. We have to get user statistics, we have to have a see how data citations, examinations, and references to the data to itself, and offer feedback. Thank you.
 Thank you very much.  Interesting, the first two speakers exposing great literature to wider audiences and one through a means of training and education and another with automation.  And I have another way of exposing great literature to wider audiences, hopefully.  A few years ago, I heard about the term data papers.  And as with all developments in the field of information, I began to think how are data papers related to great literature and how is an organization incorporate them in and among its own resources.  What sparked my initiative or initial initiative was that data papers were a new document type of great literature.  And that they had a place within Green Nets on-going enhanced publications project, which was dated back to 2011.  So in early April of this year, I had the opportunity to attend a meeting in Barcelona where Peter Dorn, director of the Don's Data Archive in the Netherlands,  presented a presentation on fair data principles. I hadn't heard of the term before.  But there was a moment of inspiration for myself.  I made a hypothesis that data papers were one of the most tangible means of finding the fair data principles.  And with that, I then returned quickly back to Amsterdam, very excited about the prospects, and I phoned Plato Smith.  And Plato is a data management librarian at the University of Florida who was at last year's conference, GL18 in New York.  I knew I could always talk on Jerry, there he is, for the technical support needed as well as the on-going support by the Don's Data Archive,  where Green Nets data collection has been housed and is housed.  However, the insight and expertise of a data management librarian such as Plato was imperative in this project, Stands or Falls.  Within a week and just under the wire of closing the GL19 call for papers, I held to that myself, our proposal was written up and submitted to the GL19 program committee.  My presentation on behalf of our project team is quite straightforward.  In other words, a long introduction, but the remainder of the presentation will be straightforward.  It reflects on the work over the past six months, or should I say, the first six months of Green Nets data papers project.  The presentation briefly looks at a definition of data papers, the background of the project, developments of Green Nets data collection,  the instrument of a data paper template, the population of this project in terms of data sets, the review process of data papers,  the publication of Green Nets data papers, some early project results, and a spin-off, a little extra, in New Orleans they call it Lanyap.  Something extra was from the initial data papers project, something unexpected.  The final will be what is the follow-up to this project.  Great.  Okay.  A definition that I pulled out was from WikiP.  The scholarly publications of a searchable metadata document describing a particular online accessible data set or group of data sets published in accordance to standard academic practices.  The background of this particular, as I mentioned in the introduction, was that we had an enhanced publications project going, it was ongoing.  The project of data papers is added or comes within the enhanced publications project.  And that project, that is the definition described by the driver, is that a publication that is enhanced with three categories of information,  materials, and post-publication data. Further, it combines textual resources, that is documents intended to be read by human beings, which contain an interpretation or analysis of primary data,  and enhanced publications inherently contribute to the review process of great literature, as well as the replication of research and improved visibility of research results in the scholarly communication chain.  So it was, for me, the data paper project fit as a glove within the enhanced publications project.  In 2011, again with Don's data archive, we had a survey. The survey was a number of questions using a survey monkey.  We asked, we had a population of our authors, researchers within the great net community, going back to 1993, of that there were 95 of the 300 or more authors that were selected for this population.  And the 50 of the 95 answered the questionnaire. And it was basically, are you prepared, what are your attitudes, are you prepared to share your research data?  We're talking about 2011. So, I mean, that was pretty good.  The response was positive. At least 50% of those who were surveyed were willing to share their data, whether they were willing to share it within the Don's data archive, or within one of their own national data archives, that was something to be further discussed.  But what we did immediately the next year, in 2012, we said, okay, let's move on to the data acquisition, the publication of the data sets in the Don's data archive, and incorporate this into a workflow, great net workflow, and that is the workflow actually of the GL conference series.  The results being also that we wanted to link the data to existing records that were not only in the Don's data archive, but were also in the Open Grade archive, which you're very familiar with, where all of great net content is made accessible.  From 2012 on, we have been, it's in the workflow, and we have now accomplished in by 2017, 30 data sets, 30 sets of data that are in and published in the Don's data archive.  It doesn't sound like a lot, but it certainly was for us representative, and it was the inspiration for this leg of the Enhanced Publications Project, the Data Papers Project.  The next step, or should I say one of the first steps, was a tool, an instrument in which the data papers could be, we didn't want to develop the wheel for data papers because it's been around for a number of years, but we wanted to streamline it for the great literature community, and for great net community.  So we went out, found three templates that would, you can find many more, but we took three, the research data journal from, which is in the Netherlands, the Journal of Open Humanities data, and the Journal of Open Psychology data.  And we looked at those templates, and then we took from them much, but we thought it was important that when you're asking a researcher or an author, certainly one who has had done a data set, created a data set five years prior,  and you're asking them retrospectively to create a data paper, which you need to do is to make sure that the note fields that are in the template in this instrument, that they are sufficient and clear, and they also give examples that can be used so that it facilitates the implementation of and creation of the data template.  The data template is not the end, the template is actually the model that is used in order to create the final data paper.  Now, we have this, as I mentioned, we had a population of 30 sets of data, and from this we were able to constitute that 15 authors or researchers were first authors or sole authors to the data that was in the Don's, the great net's collection in Don's.  So what we did was we sent out then the data template, we sent out the hour, that is our team, our data papers team, our example of what we created a data paper, and we asked them their willingness, these 15 authors, researchers, their willingness to write a data paper.  So unexpectedly, 24 hours after the first request, we got Daniela Aloya and Aouton from New York Academy of Medicine immediately came back and said, yes, we're going to submit a data paper.  And then we came, and so actually what happened was in a very short period of time we had, and I think, oh no no no no, you're right, you're right, okay.  And I said it was going to be straightforward, but I'm not, I just lied, okay. So what we did was we have now five data papers were on the way, and I do want to mention that there is a review process, all great literature,  whether it's data or whether it's full text or whether it's bibliographic, metadata has to be in some way reviewed, and we have a review process.  There will be a paper on this explanation, a data paper that is submitted and published first in the Don's data archive is something which you can call a preprint,  and when, and it is scheduled once it is accepted by our data management library, it is then eligible for publication as a data article in the Great Journal.  Promotion, Great Journal, two data articles in the autumn issue of the Great Journal, and we're very happy that this could happen prior to this conference today.  The results of that paper project, the template has been compiled, edited, the six authors have indicated interest, I already told you that there was eight, five have been published.  The data papers is now a term as a document type within the Gray Source Index, and you would say, well, the Gray Source Index, what is that? It's a web page on GrayNet's website, and it gives 100 document types of great literature,  but it is the most trafficked web page that GrayNet has. It's unbelievable, and it's a very simplest one, but it's the most trafficked one.  And of course, data papers is one of the 15 points of the PISA Declaration on, it supports the PISA Declaration on Policy for Great Literature.  Spin off, I think I have a minute, spin off is that in the Great Journal, the GL Conference Series, and the GL Conference Series, this was the population for the data sets,  but there are other articles that are coming into the Great Journal that were never in the series.  So we went to those that were not in GL, and we asked, are they willing, and already to have acknowledged that they are starting to work on the data paper.  So it's, for us, great. And then the final spin off is that seeing if we're going to go further with this, and certainly within the workflow, we have to have perhaps a workshop, a training on the creation of data papers.  And we are going to have a test, a pilot of this workshop at the University of Florida. They will be hosting this.  Follow up to the project, we're just getting started, it's only six months. It's got to be implemented in the workflow, not only of the conference series, but also of the journal, the Great Journal.  We have to get user statistics, we have to have a see how data citations, examinations, and references to the data to itself, and offer feedback.  Thank you.
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