The International Center for the Study of Research (ICSR) has announced the launch of ICSR Lab. With this new resource, ICSR provides researchers with a powerful cloud-based platform which enables them to analyse large structured metadata datasets. The new service contributes towards ICSR's goal to further the study of research and thus to contribute to the evidence base supporting the practice of research strategy, evaluation and policy.
ICSR Lab allows researchers to access and perform computation on research metadata including those that power Elsevier solutions such as Scopus and PlumX. Throughout 2020, ICSR will focus on providing additional data sources, such as abstracts, funding data and SciVal Topics of Prominence. In addition, a pilot study will assess how ICSR Lab is used with the aim of further improving the platform and datasets therein to meet the needs of informetrics researchers and librarians.
Whether for exploratory projects, replication studies or developing new research metrics and indicators, ICSR Lab will enable researchers to conduct impactful studies on topics of relevance to ICSR's research themes, supported by Elsevier datasets. The platform is available at no cost for researchers for the duration of their project. To get started, researchers can now apply for access by submitting a short proposal which will be subject to peer review by members of the ICSR Advisory Board. Applications from researchers of any career stage or experience level are encouraged and prior experience with these data sources is not necessarily required.
By allowing the sharing of summary results alongside publications without a license the ICSR demonstrates its support of open research and open science. ICSR Lab also explicitly supports replication studies. ICSR Lab is powered by the platform Databricks in which analyses are coded in Python or SQL, allowing researchers complete control over their calculations.
Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting & Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment & Entity Extraction.
Click here to read the original press release.
