{"id":8044,"date":"2017-05-08T07:17:24","date_gmt":"2017-05-08T05:17:24","guid":{"rendered":"https:\/\/www.uni.lu\/c2dh-en\/articles\/the-limitations-of-data\/"},"modified":"2025-03-26T10:13:20","modified_gmt":"2025-03-26T09:13:20","slug":"the-limitations-of-data","status":"publish","type":"articles","link":"https:\/\/www.uni.lu\/c2dh-en\/articles\/the-limitations-of-data\/","title":{"rendered":"The limitations of data"},"content":{"rendered":"\n
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Data are not the same as sources and datasets need rigidly defined categories of information which does not allow for deviation and reinforces binary oppositions such as male and female.<\/strong><\/p>\n\n\n\n

\nThe limitations of data<\/h2>\n\n\n\n

My current research on Gender in Computer Science in the twentieth Century can be seen as an extension, or better, a prelude, to my research on the gender balance in computer science conferences and the digital humanities conference between 2000 and 2015 during my Master of Digital Humanities at KU Leuven. In my dissertation I mainly studied the links between co-authors who collaborated on conference papers. In order to study the gender balance and connections between co-authors for the computer science conferences, I used a dataset created by Agarwal et al. in 2016 which is available on Mendeley.[1]<\/sup><\/a><\/p>\n\n\n\n

<\/span>Bibliographies aid researchers in browsing through collections of books, articles, journals and proceedings. Before the advent of the digital age, these massive volumes of titles and authors per research field, country or language mostly served researchers and librarians. When these collections were transformed into online databases, the bibliography suddenly offered insights into academia when processed correctly. Apart from the author and title, entries also contain venue or publisher, and the type and year of publication. Furthermore, online versions sometimes provide full-text and bibliometrics in addition to abstracts and tables of content. Several tools gratefully employ this data to uncover research area evolutions and communities that show current trends in scientific inquiry, as well as academic social networks in the form of undirected collaboration networks or directed dispute networks[2]<\/sup><\/a>. The conference data obtained from bibliographic databases contain authorship demographics which allow a general comparison of different conferences, including factors such as age, authorship position, career position, gender and affiliation. Furthermore, this data also provides the basis for the creation of co-authorship networks.<\/p>\n\n\n\n

<\/span>Since online bibliographic data offers a lot of information on co-authorship and citations, it can provide invaluable insights into academia. The creators of the dataset I used concluded in Women in Computer Science Research <\/em>that research participation and collaboration of female authors increased by less than 0.1% per year between 2000 and 2015, and male researchers represent 79% of actively publishing members in computer science conferences. The dataset which formed the foundation of this research is derived from a snapshot of the DBLP bibliography database in September 2015.[3]<\/sup><\/a> The \u201cData Bases and Logic Programming\u201d (DBLP) Digital Library started as a formatted HTML collection of Tables of Contents created by Michael Ley for his PhD.[4]<\/sup><\/a> Research has shown biases in the DBLP bibliography in the coverage of computer science since it promotes conferences on Databases, Information Retrieval, Digital Libraries and Data Mining, and on Programming Languages.[5]<\/sup><\/a><\/p>\n\n\n\n

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