Publications in peer-reviewed Scientific Journals are seen as a performance indicator reflecting the productivity of a research-based pharmaceutical company focused on innovation and new therapeutic concepts for unmet medical needs. A new corporate publication tracking system serves Boehringer Ingelheim employees and the Research leadership team as an important benchmark and tracking tool for “Boehringer Ingelheim Papers” published in the global scientific community. Our semantic approach comprises the results of automated literature database alerts and manually curated & enriched data for tracking, storing and visually analysing published articles in peer-reviewed scientific journals, based on semantic analysis of publications coming from Boehringer Ingelheim authors.
Using semantic technologies to analyse and track publication data in a manner that facilitates the subsequent reuse of both the metadata and the manually curated data. The raw analysed data are displayed graphically in a generic RDF web browser using interactive SVG tools to browse and filter the analysed data. This approach demonstrates that semantic technology is an appropriate technology to record and track scientific publications, using flexible analysis procedures to interpret xml and manually added metadata.
Senior information scientist
Boehringer Ingelheim Pharma GmbH & Co. KG
http://www.boehringer-ingelheim.com
Aleksandar Kapisoda is an experienced data scientist with a degree in information and knowledge management from the University of Applied Sciences in Stuttgart, Germany. He is part of the "Senior information scientist" team in the Scientific Information Center (S.I.C.) at Boehringer Ingelheim Pharma GmbH & Co. KG in Biberach, Germany.
