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Title:

HOMER - HPMC tool for Ontology-based Metadata Extraction and Re-use.

Document type:
Forschungsdaten
Publication date:
06.02.2025
Responsible:
Farnbacher, Benjamin
Authors:
Hoppe, Nils; Chiapparino, Giuseppe; Ulrich, Friedrich; Jiao, Yu; Farnbacher, Benjamin; Ralev, Radoslav; Fang, Donghao; Rosche, Eric; Wunderlich, Florian; Sosa Rodriguez, Angel; Stemmer, Christian
Author affiliation:
TUM
Publisher:
TUM
Identifier:
doi:10.14459/2022mp1694401.002
Concept DOI:
doi:10.14459/2022mp1694401
End date of data production:
20.01.2025
Subject area:
DAT Datenverarbeitung, Informatik; MAS Maschinenbau; MTA Technische Mechanik, Technische Thermodynamik, Technische Akustik
Other subject areas:
Research Data Management, High Performance Computing
Resource type:
Logfiles und Nutzungsdaten / log files and usage data
Other resource types:
Python code + documentation
Data type:
Programme und Anwendungen / software and applications
Description:
HOMER is a python-written metadata crawler that allows to automatically retrieve relevant research metadata from script-based workflows on HPC systems. The tool offers a flexible approach to metadata collection, as the metadata scheme can be read out from an ontology file.
Method of data assessment:
Versioned entity of the research software developed by the Chair of Aerodynamics and Fluid Mechanics at Technical University of Munich. Updates are continuously released at https://gitlab.lrz.de/nfdi4ing/crawler
Links:
Updates are continuously released at https://gitlab.lrz.de/nfdi4ing/crawler
The corresponding article can be found here: https://www.inggrid.org/article/id/3983/
Key words:
Research Data Management, Metadata, HPMC, Ontology
Technical remarks:
View and download (5.9 MB total, 112 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1694401.002):
rsync rsync://m1694401.002@dataserv.ub.tum.de/m1694401.002/
Language:
en
Other rights:
GNU GPLv3 (or newer)
Text: CC-BY-SA (4.0)
Note:
The authors would like to thank the Federal Government and the Heads of Government of the Länder, as well as the Joint Science Conference (GWK), for their funding and support within the framework of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) project number 442146713.
The authors would also thank the Competence Network for Scientific High Performance Computing in Bavaria (KONWIHR) for their funding and support within a short term project.
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