Progress of Self-Archiving Within the DML Corpus, with a View Toward Community Dynamics

• Published in: Intelligent Computer Mathematics Vol. 9791; pp. 63 - 74
• Main Authors: Müller, Fabian, Teschke, Olaf
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2016; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Artificial intelligence; Community behavior; Corpus analysis; Green Open Access; Self-archiving
• ISBN: 9783319425467; 3319425463
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-42547-4_5

Self-archiving has developed as a key component to realize Open Access within the DML framework, with the arXiv being by far the most widely used platform. Important features like full-text formula search are facilitated by the openly available sources. However, despite the obvious growth of the arXiv corpus, it is not clear what share of the published mathematical literature is already openly accessible in this way, and whether it might eventually converge to full coverage. We present the methodology of the matching procedure of the zbMATH corpus (comprising most of the published math literature since 1868) to the arXiv, and derive from the granular zbMATH data a detailed analysis of the progress of self-archiving within the different mathematical communities, taking into account subject specifics, publication delays, peer review policies, and author networks, among other things. On this basis we give some projections of future developments.