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Making Research Data FAIR. Seriously? - Reflections on Research Data Management in the Computational Literary Studies
Making Research Data FAIR. Seriously? - Reflections on Research Data Management in the Computational Literary Studies
Computational Literary Studies (CLS) are an evolving, interdisciplinary field of research combining research questions from the traditional field of Literary Studies with methods and technologies from Computer Sciences and Computational Linguistics. In this paper we present our experience in RDM within the CLS. We will illustrate both pragmatic RDM solutions and major barriers in making research data FAIR. We will show that these barriers are intrinsic in the discipline itself. DFG Schwerpunktprogramm SPP 2207 "Computational Literary Studies" Online: https://gepris.dfg.de/gepris/projekt/402743989 https://dfg-spp-cls.github.io/ Teilprojekt: "Zentralprojekt des SPP CLS" Online: https://gepris.dfg.de/gepris/projekt/424212012 https://dfg-spp-cls.github.io/about.html
FAIR Principles, CLS, SPP CLS, RDM, Research Data Management, Computational Literary Studies, SPP 2207, FAIR
FAIR Principles, CLS, SPP CLS, RDM, Research Data Management, Computational Literary Studies, SPP 2207, FAIR
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!Computational Literary Studies (CLS) are an evolving, interdisciplinary field of research combining research questions from the traditional field of Literary Studies with methods and technologies from Computer Sciences and Computational Linguistics. In this paper we present our experience in RDM within the CLS. We will illustrate both pragmatic RDM solutions and major barriers in making research data FAIR. We will show that these barriers are intrinsic in the discipline itself. DFG Schwerpunktprogramm SPP 2207 "Computational Literary Studies" Online: https://gepris.dfg.de/gepris/projekt/402743989 https://dfg-spp-cls.github.io/ Teilprojekt: "Zentralprojekt des SPP CLS" Online: https://gepris.dfg.de/gepris/projekt/424212012 https://dfg-spp-cls.github.io/about.html