Creating Core Ontology for Social Sciences Empirical Data Integration

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборникерецензирование

Аннотация

There exist several dozens of metadata standards for empirical research data, making it difficult for users to choose and apply such standards. Consequently, the integration of datasets from similar empirical studies for further knowledge acquisition is highly constrained. To resolve this problem, an ontology for social science research data integration (Empirion-core) has been developed. The ontology reuses existing data integration schemas: DDI-RDF Discovery Vocabulary, Generic Statistical Information Model, Core Ontology for Scientific Research Activities, Data Catalog Vocabulary, and DCMI Metadata Terms. It consists of five subontologies that provide concepts for empirical datasets description: Information resource ontology, Research activity ontology, Research coverage ontology, Measurement ontology, and Sampling ontology.
Язык оригиналаанглийский
Название основной публикацииProceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K2020) - Volume 2: KEOD
Страницы267-274
СостояниеОпубликовано - 2020
Событие12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management -
Продолжительность: 2 ноя 2020 → …
Номер конференции: 12
http://www.keod.ic3k.org/?y=2020

конференция

конференция12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
Сокращенный заголовокKEOD
Период2/11/20 → …
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