Research data in different disciplinary fields vary greatly in structure, format, and size. Although metadata standards for research data in major disciplinary fields have been established, it is common that metadata models and knowledge organization structures have to be developed for individual disciplines to meet the special needs and requirements of research data management in different domains. Computationally intensive research, for example, relies heavily on writing programming code in the research lifecycle for data collection, processing, analysis, and management. Ecosystem research data encompass a wide variety formats and types of data that often mixed with unstructured notes or annotations. Humanities research data are often in text format and unstructured. Proper organization and management of research data is necessary not only for their ongoing management and use but also for long-term preservation and access.
This half-day workshop will provide a forum for reporting projects and practices in modeling metadata and representing knowledge for research data management and use/reuse. There will be a brief overview of metadata modeling and knowledge representation for research data as the opening presentation for the workshop, which will take about 30 minutes. We will contact potential speakers who have done projects relevant to the focus of this workshop from science, social sciences, and humanities disciplines. This part of the workshop may have 4~6 speakers in two separate panels, with one hour for each panel. Each panel will have 30 minutes afterwards for interactive discussion. A moderator will lead each interactive discussion after the panel presentations. Finally, the workshop will use 15 minutes to summarize the presentation and discussion to highlight future research topics.
Librarians, information professionals, and graduate students who are interested in learning about metadata modeling and knowledge representation for research data will learn about the important concepts, methods, practices, and current developments through the overview and panel presentations. Researchers and practitioner will be able to share and exchange information and discuss issues in metadata modeling and knowledge representation through questions and answers between presenters and participants. This will also be a great opportunity for educators who teach courses in information organization and other related areas to stay in touch with new developments.
Jian Qin, Syracuse University, Syracuse, New York, USA
Marcia Zeng, Kent State University, Kent, OH, USA
Shigeo Sugimoto, University of Tsukuba, Tsukuba, Ibaraki, Japan
Xia Lin, Drexel University, Philadelphia, PA, USA
Rich semantics supports detailed information organization for the contents of documents, across documents, and even across resources in different modalities. In its strongest form, rich semantics provides highly-structured direct representations. This workshop welcomes papers on new directions for frameworks using such rich information organization. Rich semantics goes beyond simple models for linked data such as those using RDF-based triples and beyond ad hoc ontologies. Rather, rich semantic frameworks may include complex entities, dynamic models, schemas, systems, and descriptive programs. Interdisciplinary work which combines approaches from areas such as LIS, linguistics, programming languages, philosophy, jurisprudence, sociology, discourse, and system analysis, and intelligent agents is particularly welcome. Examples of services based on these high-level structures are also welcome. In addition, the workshop will consider descriptions of rich semantic information organization in specific areas including biology, law, medicine, history, and biography. Work on upper ontologies should go beyond existing frameworks or show how they can be applied to especially complex scenarios. Work on text mining should emphasize significant, novel, and general semantic structures.
The primary goal of the workshop is the exchange of ideas among researchers who are actively working on this topic. However, everyone who is interested (especially including students) is encouraged to attend.
Robert B. ALLEN, Yonsei University (Workshop Organizer)
Thomas BITTNER, University of Buffalo
Marten DURING, University of Luxemburg
Antske FOKKENS, University of Amsterdam
Eero HYVONEN, Aalto University
Chris KHOO, Nanyang Technological University
Jin-Dong KIM, Database Center for Life Science (Japan)
Xia LIN, Drexel University
Daniel V. PITTI, University of Virginia
Laura SLAUGHTER, Oslo University Hospital and University of Oslo
Karin VERSPOOR, University of Melbourne
YeJun WU, Louisiana State University and University of Hong Kong
Marcia ZENG, Kent State University