Relations between concepts (and/or entities, events, and other things) vary depending on the criteria by which relations are defined or viewed. In the domain of research data management, different types of research generate different types of data and terminologies vary between practitioners and basic science researchers even within the same disciplinary domain. Interactions between datasets, between datasets and documentation, and between datasets and computing code can result in different types of relations. This paper employs a framework of analysis to study concept relation types in the research data management domain. By using two cases – one is the GenBank annotation records and the other is the data and artifact collection from a gravitational wave search, this paper demonstrates the types of relations existing in and between datasets, publications, computing codes, and workflows. The analysis and generalization of these relations references the research in AI’s knowledge representation and knowledge organization systems (KOS), including both ad hoc subject categories and formal KOS, because in the next AI era, relations as one of the key components of AI applications will be required to function not only as part of KOS for indexing data and publications, but more importantly, to function as codifiable knowledge for machine consumption.
|Original language||English (US)|
|Number of pages||7|
|State||Published - 2018|
|Event||Fifteenth International Society of Knowledge Organization Conference - Porto, Portugal|
Duration: Jul 10 2018 → Jul 12 2018
Conference number: 15
|Conference||Fifteenth International Society of Knowledge Organization Conference|
|Period||7/10/18 → 7/12/18|
Qin, J. (2018). A relation typology in knowledge organization systems: Case studies in the research data management domain. . Paper presented at Fifteenth International Society of Knowledge Organization Conference, Porto, Portugal.