Papers: Metadata as Linked Data and Knowledge Graph

Starts at
04 Oct 22 15:30 UTC
Finishes at
04 Oct 22 17:00 UTC
Virtual Conference Room A
Brian Dobreski


  • Brian Dobreski

    University of Tennessee, Knoxville

    Brian Dobreski is an Assistant Professor in the School of Information Sciences at University of Tennessee-Knoxville. His research focuses on the social implications of metadata, classification, resource description, and other knowledge organization practices, as well as the concepts of personhood and personal identity in information. Brian received his Ph.D. in information science from Syracuse University.


China Art in the Museums Overseas': Metadata Aggregation of Chinese Digital Collections Images

Authors: Xilong Hou, Xiaoguang Wang, Hua Jian

In the World Wide Web, a very large number of online cultural heritage (CH) resources is made available through digital museums websites. They display collections images and share collection metadata, which makes opportunities for aggregating. 'China Art in the Museums Overseas' platform aggregated China digital collections from overseas institutions. This paper introduces the metadata aggregation workflow of this project, especially a unified data model used to solve the metadata standards heterogeneity. Besides, this platform is not simply a database, but also provides search, images semantic annotation, knowledge graph serves, linked open data interface and so on. Our work is an effort to resolve multi-source data aggregation and it is valuable. It improves the availability and discoverability of digital collections, and spread Chinese culture to the public more widely.

  • Xilong Hou

    Qufu normal university

    I’m Xilong Hou, an associate professor at School of Communication, Qufu Normal University. I finished my post-doctoral at School of Information Resources, Wuhan University, supervised by Professor Xiaoguang Wang. I received PhD degree of management from Central China Normal University. My research interests include knowledge organization systems, linked data, digital humanities and cultural heritage.

Metadata and Ontology Design for Protection and Utilization of Great Sites

Authors: Jing Zhou, Li Si

In the process of rapid urbanization in China, the protection and utilization of great sites are facing unprecedented pressure. The effective knowledge organization of great sites is a prerequisite for their protection and utilization. Ontology provides realization paths for organizing knowledge of great sites. In this paper, firstly, CIDOC- CRM and Time ontology are reused to build the top-level ontology with the results of user interviews. Secondly, top-down concept extraction and bottom-up concept expansion are adopted to gain the knowledge concepts and instances of great sites. Finally, data properties and object properties are defined. The designed ontology can provide the knowledge modeling and representation of great sites, laying the foundation for knowledge sharing.

  • Jing Zhou

    School of Information Management, Wuhan University

    Jing Zhou is a doctoral student in School of Information Management, Wuhan University, China. Her research interests include knowledge organization, knowledge management, semantic web and digital humanities. She participates in research projects on metadata, evaluation of collections, database construction, information retrieval and research data management, and she is the author of several publications.

Application Profile Driven Data Acquisition for Knowledge Graph and Linked Data Generation in Crowdsourced Data Journalism

Authors: Nishad Thalhath, Mitsuharu Nagamori, Tetsuo Sakaguchi

Application Profiles are a collection of vocabularies mixed and matched from different namespaces and customized for the local application. Application Profiles act as a constrainer as well as an explainer of the metadata for every dataset. Linking data and generating knowledge graphs are the general challenges that information processing communities are trying to address constructively. Application Profiles can act as a means of linking data and generating knowledge graphs. The authors propose application profile driven questionnaire creation for data linking in the perspective of crowdsourced data acquisition; especially where there are challenges in adapting a single vocabulary or a limited number of adaptable domain-specific vocabularies. This paper presents a proof of concept study based on the proposed approach by adapting existing standards and tools, with the notion that similar methods are applicable in related use-cases.

  • Nishad Thalhath

    University of Tsukuba

    Nishad Thalhath is a doctoral student in Information Studies at Tsukuba University, Japan, specializing in metadata standards, knowledge graphs, and data interoperability.