Poster Open Access

Computational Literary Studies Infrastructure (CLSINFRA): a H2020 Research Infrastructure Project that aids to connect researchers, data, and methods

Birkholz, Julie M.; Börner, Ingo; Chambers, Sally; Cinková, Silvie; van Dalen-Oskam, Karina; Dejaeghere, Tess; Dudar, Julia; Eder, Maciej; Edmond, Jennifer; Garnett, Vicky; Kren, Michal; Mrugalski, Michal; Murphy, Ciara L.; Odebrecht, Carolin; Papaki, Eliza; Raciti, Marco; van Rossum, Lisanne; Schöch, Christof; Šela, Artjoms; Sharma, Srishti; Tonra, Justin; Tóth-Czifra, Erzsébet; Trilcke, Peer

The aim of this poster is to provide an overview of the principal objectives of the newly started H2020
Computational Literary Studies (CLS) project- https://www.clsinfra.io. CLS is a infrastructure project
works to develop and bring together resources of high-quality data, tools and knowledge to aid new
approaches to studying literature in the digital age. Conducting computational literary studies has a
number of challenges and opportunities from multilingual and bringing together distributing
information. At present, the landscape of literary data is diverse and fragmented. Even though many
resources are currently available in digital libraries, archives, repositories, websites or catalogues, a lack
of standardisation hinders how they are constructed, accessed and the extent to which they are reusable
(Ciotti 2014). CLS project aims to federate these resources, with the tools needed to interrogate them,
and with a widened base of users, in the spirit of the FAIR and CARE principles (Wilkinson et al. 2016).
The resulting improvements will benefit researchers by bridging gaps between greater- and lesser-
resourced communities in computational literary studies and beyond, ultimately offering opportunities
to create new research and insight into our shared and varied European cultural heritage.
Rather than building entirely new resources for literary studies, the project is committed to exploiting
and connecting the already-existing efforts and initiatives, in order to acknowledge and utilize the
immense human labour that has already been undertaken. Therefore, the project builds on recently-
compiled high-quality literary corpora, such as DraCor and ELTeC (Fischer et al. 2019, Burnard et al. 2021,
Schöch et al. in press), integrates existing tools for text analysis, e.g. TXM, stylo, multilingual NLP
pipelines (Heiden 2010, Eder et al. 2016), and takes advantage of deep integration with two other
infrastructural projects, namely the CLARIN and DARIAH ERICs. Consequently, the project aims at
building a coherent ecosystem to foster the technical and intellectual findability and accessibility of
relevant data. The ecosystem consists of (1) resources, i.e. text collections for drama, poetry and prose in
several languages, (2) tools, (3) methodological and theoretical considerations, (4) a network of CLS
scholars based at different European institutions, (5) a system of short-term research stays for both early
career researchers and seasoned scholars, (6) a repository for training materials, as well as (7) an
efficient dissemination strategy. This is achieved through a collaboration between participating
institutions: Institute of Polish Language at the Polish Academy of Sciences, Poland; University of
Potsdam, Germany; Austrian Academy of Sciences, Austria; National University of Distance Education,
Spain; École Normale Supérieure de Lyon, France; Humboldt University of Berlin, German; Charles
University, Czech Republic; Digital Research Infrastructure for the Arts and Humanities, France; Ghent
Centre for Digital Humanities, Ghent University, Belgium; Belgrade Centre for Digital Humanities, Serbia;
Huygens Institute for the History of the Netherlands (Royal Netherlands Academy of Arts and Sciences),
Netherlands; Trier Center for Digital Humanities, Trier University, Germany; Moore Institute, National
University of Ireland Galway, Ireland;

 

This project has received funding from the European Union’s Horizon 2020 research and innovation
programme under grant agreement No 101004984.

References
Ciotti, Fabio. 2014. „Digital literary and cultural studies: the state of the art and
perspectives“.Between4/8, 1-17.https://doi.org/10.13125/2039-6597/1392.
Borgman, Christine. 2010. Scholarship in the Digital Age : Information, Infrastructure, andthe Internet.
Cambridge, Mass & London: MIT Press. See https://www.dariah.euandhttps://www.clarin.eu.
Burnard, Lou, Christof Schöch, and Carolin Odebrecht. 2021. „In search of comity: TEI fordistant
reading“.Journal of the Text Encoding Initiative. https://doi.org/10.4000/jtei.3500.
Eder, M., Rybicki, J. and Kestemont, M. 2016. Stylometry with R: a package forcomputational text
analysis.R Journal, 8(1): 107-21.https://journal.r-project.org/archive/2016/RJ-2016-007/index.html
Fischer, Frank, Ingo Börner, Matthias Göbel, Andrea Hechtl, Christopher Kittel, P. Miling, andPeer Trilcke.
2019. „Programmable Corpora: Introducing DraCor, an Infrastructure for theResearch on European
Drama“. InBook of Abstractsof the Digital Humanities Conference2019. Utrecht: ADHO.
Heiden, Serge. 2010. The TXM Platform: Building Open-Source Textual Analysis SoftwareCompatible with
the TEI Encoding Scheme. In24th PacificAsia Conference on Language,Information and Computation(pp.
10 p.). Sendai, Japon.Retrieved
fromhttp://halshs.archivesouvertes.fr/docs/00/54/97/64/PDF/paclic24_sheiden.pdf
Schöch, Christof, Tomaz Erjavec, Roxana Patras, and Diana Santos (in press). „Creatingthe European
Literary Text Collection (ELTeC): Challenges and Perspectives”.ModernLanguages Open.
Wilkinson, Mark D., Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, MylesAxton, Arie
Baak, Niklas Blomberg. 2016. „The FAIR Guiding Principles for Scientific DataManagement and
Stewardship“.Scientific Data 3(1).https://doi.org/10.1038/sdata.2016.18.

Files (239.6 kB)
Name Size
20220523_CLS_poster_DHB2022.pdf
md5:8bab8a277189cec02ec49030d3f148bb
239.6 kB Download
105
51
views
downloads
All versions This version
Views 105105
Downloads 5151
Data volume 12.2 MB12.2 MB
Unique views 9191
Unique downloads 4747

Share

Cite as