LIFE - Linked Data for eScience Services
|Zeitraum:||k.A. bis k.A.|
|Beteiligt:||Münster Semantic Interoperability Lab (MUSIL)|
Institut für Geoinformatik der Universität Münster>
|gefördert von:||Deutsche Forschungsgemeinschaft (DFG)|
The overall goal of the project is to improve interdisciplinary collaboration in research and education through the sharing of scientific data organized in space, time and semantics. The project addresses various kinds of resources, ranging from project- and user-generated data, through articles and books to historic maps. Exposed as Linked Data, these resources feed eScience services to discover, access, and enrich them and to use them in scientific and other knowledge infrastructures. The project aims at overcoming the information silos that dominate libraries and research respositories. It builds on standards, such as those of the Open Geospatial Consortium (OGC), and extends them by Linked Data interfaces, targeting a better integration of bibliographic, scientific and administrative contents. This approach enables a retrieval of contents through spatio-temporal and semantic queries.
LIFE is a two-year project funded by the German Research Foundation, jointly carried out by the Semantic Interoperability Lab (MUSIL) at Institute for Geoinformatics and the University Library at University of Münster (ULB). It is the first externally funded project in the context of LODUM (Linked Open Data University of Münster). The overall goal of the project is to facilitate sharing of spatio-temporal information and thus improve interdisciplinary collaboration in science and education. This approach addresses all kinds of resources, ranging from articles and books over maps to raw data. The Linked Data approach will be used as a basis for the university library’s eScience services to seamlessly integrate their offerings into both the scientific and the global information infrastructure. These eScience services will enable researchers and students to systematically navigate the dynamic and heterogeneous global network of spatio-temporal information (discovery) and to create the relevant views (access) meeting their information needs. The project particularly aims at overcoming the information silos that have been created both in libraries and in the geospatial domain. We will build on existing standards and extend them with Linked Data interfaces, focusing on a tight integration of bibliographic contents. This will allow for novel user interfaces for retrieving contents through spatio-temporal queries (e.g., “books about medieval Westphalia”). In LIFE, all developments will focus on linked spatio-temporal data, especially on maps. We develop integration and annotation workflows and tools (including ETL processes and annotation tools), eScience services which offer linked data for standard clients (including service for spatial data), as well as specific retrieval interfaces for researchers and students. Developments are focused on three scenarios and will be tested with corresponding partners on the Campus Münster: 1. Spatio-temporal library information. In this central scenario, we enhance existing library information processes by linked spatial-temporal data. This includes: a. Developing historic map and document annotation and retrieval tools for the ULB as well as the Institute for comparative urban history1. b. Developing a Biographical Thesaurus for North Rhine Westphalia (NRW) based on the Nordrhein-Westfälischen Bibliographie 2 . It allows searching human biographies and lifelines over time and space. 2. Campus navigation. In this scenario, we develop technology that allows localizing and finding resources on the campus. Development includes mobile technology such as the Campusplan App3 which allows finding campus resources based on linked data. 3. Spatio-temporal explorer for cancer research. In this scenario, we develop a spatial recommender system together with the Institut für Epidemiologie und Sozialmedizin4 . It assists researchers in exploring cause-effect relationships of significant incidence elevations of selected cancer types in a predefined geographic region.