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A pragmatic approach to concept-based annotation of scientific names in biodiversity and environmental research data

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dc.contributor.authorKohlbecker,Andreas
dc.contributor.authorGüntsch, Anton
dc.contributor.authorKilian, Norbert
dc.contributor.authorKusber, Wolf-Henning
dc.contributor.authorLuther, Katja
dc.contributor.authorMüller, Andreas
dc.contributor.authorvon Raab-Straube, Eckhard
dc.contributor.authorBerendsohn, Walter
dc.date.accessioned2021-12-14T10:57:27Z
dc.date.available2021-12-14T10:57:27Z
dc.date.issued2021
dc.description.abstractWith the increasing amount of interdisciplinary and international networks dedicated to long-term persistence and interoperability of research data, the demand for semantic linking of environmental research data has grown. Data related to organisms frequently inherit a major obstacle. Organisms often are ambiguously identified by using only the scientific name, which is not a precise identifier for the taxonomic concept that is implicitly being used. Here we describe a robust taxon concept definition that allows deducing a set of rules for semi-automatically managing concepts. These rules define specific taxonomic operations as transition points at which new taxon concepts emerge from former concepts. Implemented into the business logic of taxon management systems, these rules can assure the stability of taxon concepts so that environmental data sets can be reliably annotated with the corresponding persistent identifier. Our approach limits the risk that referenced taxon concepts are modified unnoticed.en
dc.identifier.doi10.18420/informatik2021-041
dc.identifier.isbn978-3-88579-708-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37706
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2021
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-314
dc.subjectAnnotation
dc.subjectbiodiversity
dc.subjectenvironmental data
dc.subjectidentifier
dc.subjectlinked open data
dc.subjectscientific name
dc.subjectsemantics
dc.subjecttaxonomy
dc.subjecttaxonomic concept
dc.titleA pragmatic approach to concept-based annotation of scientific names in biodiversity and environmental research dataen
gi.citation.endPage546
gi.citation.startPage539
gi.conference.date27. September - 1. Oktober 2021
gi.conference.locationBerlin
gi.conference.sessiontitleWorkshop: Computer Science for Biodiversity (CS4BIODiversity)

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P314 - INFORMATIK 2021 - Computer Science & Sustainability