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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.

Report: Track­ing self-citations in acade­m­ic publishing

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.

Report: Apply­ing Cross­ref and Unpay­wall infor­ma­tion to identi­fy gold, hidden gold, hybrid and delayed Open Access publi­ca­tions in the KB publi­ca­tion corpus

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.

Abschluss­bericht: Effzientes Retrieval auf Web of Science-Daten mit Elasticsearch