=Paper=
{{Paper
|id=Vol-3724/short6
|storemode=property
|title=FAIR Paper: Applying FAIR to Academic Publishing
|pdfUrl=https://ceur-ws.org/Vol-3724/short6.pdf
|volume=Vol-3724
|authors=Wouter Beek,Rick Maurits,Auke Rijpma
}}
==FAIR Paper: Applying FAIR to Academic Publishing==
https://ceur-ws.org/Vol-3724/short6.pdf
FAIR Paper: Applying FAIR to Academic Publishing
Wouter Beek1,*,† , Rick Mourits2,† and Auke Rijpma3,†
1
Triply B.V.
2
International Institute for Social History
3
Universiteit Utrecht
Abstract
The FAIR principles have a significant and lasting impact on the way in which research is performed in
the Digital Humanities. However, the FAIR principles have not yet significantly impacted the way in
which research papers are published and disseminated. This paper describes a new approach towards
academic publishing called ‘FAIR Paper’. A FAIR Paper is an academic publication that lives on the
Web, uses open standards, and is completely reproducible. We report on our findings based on an early
Proof-of-Concept implementation of the FAIR Paper concept.
Keywords
Linked Data, FAIR Principles, Academic Publishing
1. Introduction
The FAIR principles have a significant and lasting impact on the way in which research is
performed in the Digital Humanities. However, the FAIR principles have not yet significantly
impacted the way in which research papers are published and disseminated.
The Common Lab Research Infrastructure for the Arts and Humanities (Clariah) project1
makes extensive use of linked data principles and techniques. Within the Clariah context,
insights are often communicated between researchers in so-called Data Stories: online publica-
tions that contain interactive query visualizations. The ability to communicate research insights
in a visual and meaningful way, is essential for a project like Clariah, where many users have a
less technical background.
With the appearance of an increasing number of elaborate Data Stories, the need arose to
give these stories a more academic and professional appeal. The rest of this article details the
results of this exploration, resulting in a Proof-of-Concept (PoC) implementation of our FAIR
Paper approach.
SemDH 2024: First International Workshop of Semantic Digital Humanities co-located with ESWC 2024, Hersonissos,
Greece
*
Corresponding author.
†
These authors contributed equally.
$ wouter@triply.cc (W. Beek); rick.mourits@iisg.nl (R. Mourits); auke.rijpma@gmail.com (A. Rijpma)
0000-0003-0250-9655 (W. Beek); 0000-0002-2267-1679 (R. Mourits); 20000-0002-8950-8227 (A. Rijpma)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
1
See https://www.clariah.nl
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
2. Related work
The RASH Framework for academic publishing was introduced in [1, 2]. It introduces a new
publication approach that relies on open web standards like HTML and CSS instead of PDF
and Word. In addition, RASH publications can include RDF for metadata annotations. The
RASH Framework has been successful in changing the practice of academic publishing in the
Semantic Web research domain, where the main conferences now accept submissions in that
format. In [3], the RASH approach was extended for non-textual entities like complex formulas
and figures.
Kuhn et al. [4] observe that the vast majority of work under the heading of ‘semantic
publishing’ has focused on adding semantic layers on top of existing academic publication
approaches. They argue that ‘genuine semantic publishing’ must be more radical, and requires
changes to the actual process of constructing and disseminating academic publications. Our
FAIR Paper approach implements some, but not all requirements that Kuhn et al. enumerate
under the heading of ‘genuine semantic publishing’. Specifically, a FAIR Paper can still be
viewed and regarded as a traditional, narrative-based publication.
There are several attempts at creating academic publications that can be reproduced by
rerunning – and thereby reproducing – the work of the original authors. An early attempt
at this approach is [5]. Other approaches make use of an online notebook system, such as
Jupyter Notebooks2 , where Python or R code case be executed on a web server. However, none
of these approaches makes exclusive use of web standards, and relies on complex execution
environments like virtual machines or servers that perform the heavy lifting.
The FAIR Principles were introduced in [6]. They have not yet had a lasting impact on the
dissemination of academic papers.
3. The FAIR Paper approach
FAIR Papers make use of the following technology stack:
• One or more RDF triple stores, where research data is published according to shared data
models.
• One or more data models, expressed in SKOS, RDFS, OWL, and/or SHACL.
• One or more SPARQL endpoints, through which data can be retrieved.
• Multiple SPARQL queries, in which research data is retrieved, processed, integrated,
aggregated, computed, and visualized.
• One HTML page, that contains the structural and textual/narrative content of the academic
publication.
• One CSS style sheet that implements the academic style of the venue for which the
academic publication is prepared. This must include a web style and a print style.
• A modern web browser with a generic print feature.
2
https://jupyter.org
Notice that the technology stack for FAIR Paper only uses open web standards and readily
available software components. It does not require an arbitrary execution environment, as with
notebooks or virtual machines. All computation is performed through standardized web APIs
like SPARQL. This also means that FAIR Papers cannot do everything that a notebook or virtual
machine can do. For example, a statistical test that cannot be implemented in contemporary
linked data standards like SPARQL/SHACL/OWL, cannot be utilized.
The following subsections explain details of our FAIR Paper PoC implementation.
3.1. Data, queries, and stories
For storing data, the Clariah linked data environment is used3 . This linked data environment
currently contains 139 public datasets.
Besides data, the Clariah triple store also allows SPARQL queries to be stored. The ability to
store SPARQL queries is not (yet) part of the SPARQL standard. In an earlier Clariah project, a
metadata language for disclosing SPARQL queries was developed under the name GRLC. This
approach is published in [7] and was implemented in the Clariah linked data environment4 .
The Clariah environment currently contains 453 publicly accessible saved queries.
In addition to data and queries, the Clariah linked data environment also allows Data Stories
to be written. Data Stories are online publications that contain interactive query visualizations.
The Clariah environment currently contains 39 public Data Stories.
3.2. Styling
In the FAIR Paper PoC, it is possible to apply academic styling in the web browser. We were able
to re-implement a CSS version of the Lecture Notes in Computer Science (LNCS) style. This style
is used by many journals and conferences in the computer science domain, and a CSS version
was previously devised for RASH Papers as well. We were not able to implement academic
styling for a venue in the (digital) humanities yet, since academic styles are not typically made
available in a CSS format. This makes the creation of a CSS implementation labor-intensive or
otherwise complex.
When this CSS style is applied to a FAIR Paper in the web browser, it is visually indistinguish-
able from a traditional LNCS publication that is created in LATEX, see Figure 1. This exercise
makes it likely that other academic styles, at least to a very large extent, can also be expressed
by using open web standards.
3.3. Printing
In the FAIR Paper PoC, it is possible to print papers from popular web browsers. This is
implemented with CSS, where print styling is specified that deviates from web styling. This is
crucial, since web content is not typically split across multiple pages, which is a requirement
for print.
3
The environment can be found at https://druid.datalegend.net and makes use of the TriplyDB triple store.
4
See https://triply.cc/blog/2023-06-grlc for a blog post on this topic.
Figure 1: An example of the first page of a FAIR Paper in the web browser, that uses the LNCS style.
The result is shown in Figure 2, where the print and print preview features of regular web
browsers are used. Our PoC was tested in recent versions of Chrome, Edge, Firefox, and Safari.
It is possible to print to a PDF file and/or to physical paper.
3.4. Paper structure and metadata
Academic papers contain several structural and metadata elements that are unique to publishing,
and that cannot be specified in a regular Data Story. Support for the following structural and
metadata elements was added in the FAIR Paper PoC:
• List of authors, ORCID IDs, and affiliations
Figure 2: A FAIR Paper that is printed by using the standard print functionality in the web browser.
• Abstract
• Keywords
• Code blocks
• Figures, including live generated galleries, 2D/3D maps, timelines, chars, class diagrams,
flow charts, or network visualizations, based on a SPARQL query.
• Tables, including live generated tables based on a SPARQL query.
The following structural and metadata elements were not added in the FAIR Paper PoC, due
to a lack of time:
• References from running text to figures, tables, and code blocks.
• Bibliographic references.
• Footnotes and/or end notes.
• Bibliography styles such as APA or MLA.
• Captions for figures, tables, and code blocks.
In theory, some of the missing elements can be manually written with HTML tags, but in
practice authors prefer an easier specification format for such elements.
4. User group test
During the FAIR Paper PoC, a user group of 5 domain experts in Clariah was formed. These
experts have used several intermediate versions of the FAIR Paper PoC implementation. The
domain experts are historians who work at the following research institutes: International Insti-
tute for Social History5 , Cultural Heritage Agency6 , University of Antwerp7 , Leiden University8 ,
and Utrecht University9 . These domain experts all had prior experience with linked data, FAIR
data, and/or data handling in general.
These technologically predisposed domain experts were asked to provide feedback and reflect
critically on the FAIR Paper PoC. This resulted in many improvements that were incorporated
during the PoC, in addition to several ideas for continued development. Furthermore, the
domain expert were able to perform the following tasks with the final PoC version:
• Read an existing FAIR Paper.
• Modify an existing FAIR Paper.
• Create a new FAIR Paper from scratch.
This small user group test, with a limited and carefully selected group of users, indicates that
FAIR Papers are already usable for domain experts with prior experience with Linked Data.
Since the current implementation did not specifically optimize for user-friendliness, we hope
that a future version of FAIR Paper will be accessible to a wide group of researchers in the
humanities.
5. Conclusion and future work
Based on the results of this PoC, we conclude that it is possible to create dynamic and online
academic publications that have the same professional features as static and offline publications.
The technologies of the web (HTML, CSS, RDF, SPARQL) are strong enough to support such
dynamic and online behavior. FAIR Papers have the benefit that they are published together
with the data and queries. The tables and figures in a FAIR Paper can be recreated online, and/or
can be adjusted by the reader to obtain different results over the same data. This gives readers
of a FAIR Paper the opportunity to reproduce the research, and interact with the underlying
data directly, so that publications can become truly FAIR.
Even though FAIR Papers can do many things that traditional papers cannot do, they are still
consistent with the current practice of static and offline publishing. For example, they allow
printing to PDF and/or physical paper.
Concrete examples of FAIR Papers can be found at https://druid.datalegend.net/
fair-paper-project. This includes a tutorial that explains how users can create their own FAIR
Papers.
5
https://iisg.amsterdam
6
https://english.cultureelerfgoed.nl
7
https://www.uantwerpen.be/en
8
https://www.universiteitleiden.nl/en
9
https://www.uu.nl/en
Acknowledgments
We thank Clariah Work Packages 4 for funding the development of the FAIR Paper approach, and
Work Package 5 for collaborating on the Data Stories and FAIR Paper concepts. We thank the
domain experts that were part of the user test group. We thank the Triply software developers
and data scientists who worked on this project.
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