The National Information Standards Organization (NISO) seeks comments on a new draft Recommended Practice, KBART Automation: Automated Retrieval of Customer Electronic Holdings. KBART Automation is an enhancement to KBART, Knowledge Bases and Related Tools, the NISO initiative which provides a format for content providers to use to transfer journal and book metadata to link resolver knowledge bases and other library software. This new draft recommended practice provides instructions to support automated feeds customised to include the holdings available at a particular institution, making it much easier for libraries to know their knowledge bases are up to date with their current subscriptions.
The purpose of the KBART Automation initiative is to facilitate the retrieval of KBART Holdings Reports, which are customized files representing an institution's holdings at a given time, typically maintained by the content provider in any case, notes Oliver Pesch, Chief Product Strategist at EBSCO Information Services and co-chair of the KBART Automation Working Group. Besides providing focus on specific KBART fields to be transmitted automatically, the draft Recommended Practice describes elements of an Application Programming Interface (API) the content provider would support to enable interaction with the knowledge base provider.
The NISO KBART Standing Committee will be considering the input from the KBART Automation Working Group, among other information, as it moves forward to keep KBART up-to-date. In the meantime the KBART Automation Recommended Practice will be published separately, after the Working Group addresses the comments received.
The NISO KBART Automation: Automated Retrieval of Customer Electronic Holdings Recommended Practice is available for public comment from November 2 to December 3, 2018. To download the draft document or submit comments, interested parties may visit the NISO project page at https://www.niso.org/standards-committees/kbart/kbart-automation.
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.