ArchivAnalyzing Self-citations in Web of Science (GESIS)
As the h-index becomes the gold standard for measuring scholarly impact, the risk for gaming the system grows. This has spurred the proposal for reporting a self-citation index (s-index), which aims to add much needed context to calculated h scores. It also is expected to promote good citation habits. A necessary step towards using the metric is validation. Here we propose to use the s-index to measure how self-citation patterns vary according to different fields, academic ages, countries, and institutions.
The restricted access to published, peer-reviewed documents is enforced via a legal framework, which is predominately based upon copyright laws. In the publication process authors transfer the copyright (or solely the exclusive reproduction rights) to a publisher and the publisher uses these rights as a legal instrument to restrict access to an audience which is willing to pay for obtaining the right to access the content. Given this perspective any identification of OA publications must therefore also be based upon legal information, which defines the access character of the publication as imposed by the copyright holder, i.e. the publisher.
Inspired by the Hybrid OA Dashboard (Jahn, 2017) we therefore propose to apply licensing information supplied by publishers to the publisher association Crossref to identify OA publication. In detail, we propose to obtain the respective licenses of Web of Science (or Scopus) indexed publications and compare them with a whitelist of established OA licenses and annotate the thereby defined OA status of the publications in the KB infrastructure.
Im Projekt "Effizientes Retrieval auf Web of Science-Daten mit Elasticsearch" ist geplant, die umfangreichen XML-Daten des Web of Science (WoS), die aktuell in einer SQL-Datenbank vorliegen, in einen performanten Elasticsearch Index3 zu überführen. Dadurch werden diese Daten effizienter recherchierbar und leichter zugänglich.