Authors: Alvares Freire, Fernanda / Ferger, Anne / Henny-Krahmer, Ulrike / Jettka, Daniel
ABSTRACT
Appropriate citation of software plays an important role in academic publications to make research results reproducible and reusable. There are several recommendations and guidelines on how to deal with research software (Anzt et al. 2021; Smith et al. 2016; Lamprecht et al. 2020) and how to cite software that is used in the research process (Jackson n.d.; Chue Hong et al. 2019a, 2019b; Druskat 2021a, 2021b).
To find out if these recommendations (e.g. consistent versioning, persistent identification, appropriate credit to developers) are actually reflected in practice, we examined conference abstracts of the DHd (Henny-Krahmer/Jettka 2022) and ADHO conferences (Jettka et al., to appear). Apparently, there is great potential (and need) for improving the current situation. In our software citation studies, an annotation model was formulated in the form of a TEI taxonomy. Initially, a document-centered approach was pursued, i.e., software mentions were semi-automatically identified and directly annotated with citation information that could be located somewhere else in the document, for instance, in the bibliographies of the abstracts.
We now propose a revised TEI annotation model, which aims at a more precise annotation to differentiate between pure software mentions (names) and other parts of citation information (such as URLs, developers, or bibliography entries) and linking these parts together. In our new approach, we use pointers () to an externally defined list of software entities and reference these pointers from the annotation instances of corresponding citation information. Thus we still aim at examining the current situation of software citation (this time in articles of the Journal of the Text Encoding Initiative), but at the same time, we provide and use a model and create a data basis of software mentions and citations which could be used for training of automatic methods to identify software mentions and corresponding citation information in academic texts.
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