Performance Evaluation of the Metadata-driven MASi Research Data Management Repository Service

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review



Research data is increasingly important in order to gain insights from scientific data. To optimally foster this, the management of research data is required to be usable, customizable and fast. We enable this by building up the MASi research data management repository service, based on the KIT DM framework. The aim is on utilizing a single repository instance to serve multiple arbitrary community use cases. Due to their diverse data characteristics the performance of the MASi service has to be fitting across the different cases. We evaluate the performance along three initial heterogeneous use cases. Various aspects are investigated; First, the object insertion and query performance of the database along the object fill level. Second and third, the ingest and download performance of digital objects using real-life data sets. Highly favorable performance characteristics are shown.


Original languageEnglish
Title of host publication26nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2018)
Place of PublicationCambridge, UK
Number of pages5
Publication statusPublished - 1 Mar 2018

External IDs

Bibtex grunzke:2018:a
Scopus 85048800929



  • bandwidth, Bars, data handling, Databases, diverse data characteristics, download performance, highly favorable performance characteristics, information retrieval systems, ingest performance, KIT DM framework, MASi service, meta data, Metadata, metadata-driven MASi research data management repository service, multiple arbitrary community use cases, object insertion, Performance, performance evaluation, query performance, query processing, real-life data sets, Repository, Research data management, scientific data, single repository instance, Standards, XML