RDFAdaptor:Efficient ETL Plugins for RDF Data Process

Purpose:The interdisciplinary nature and rapid development of the Semantic Web led to the mass publication of RDF data in a large number of widely accepted serialization formats,thus developing out the necessity for RDF data processing with specific purposes.The paper reports on an assessment of chief RDF data endpoint challenges and introduces the RDF Adaptor,a set of plugins for RDF data processing which covers the whole life-cycle with high efficiency.Design/methodology/approach:The RDFAdaptor is designed based on the prominent ETL tool—Pentaho Data Integration—which provides a user-friendly and intuitive interface and allows connect to various data sources and formats,and reuses the Java framework RDF4J as middleware that realizes access to data repositories,SPARQL endpoints and all leading RDF database solutions with SPARQL 1.1 support.It can support effortless services with various configuration templates in multi-scenario applications,and help extend data process tasks in other services or tools to complement missing functions.Findings:The proposed comprehensive RDF ETL solution—RDFAdaptor—provides an easy-to-use and intuitive interface,supports data integration and federation over multi-source heterogeneous repositories or endpoints,as well as manage linked data in hybrid storage mode.Research limitations:The plugin set can support several application scenarios of RDF data process,but error detection/check and interaction with other graph repositories remain to be improved.Practical implications:The plugin set can provide user interface and configuration templates which enable its usability in various applications of RDF data generation,multi-format data conversion,remote RDF data migration,and RDF graph update in semantic query process.Originality/value:This is the first attempt to develop components instead of systems that can include extract,consolidate,and store RDF data on the basis of an ecologically mature data warehousing environment.

Construction of a domain knowledge service system based on the STKOS

Purpose: The study was carried out to construct a domain knowledge service system based on the Scientific & Technological Knowledge Organization Systems(STKOS). Design/methodology/approach: The framework of a domain knowledge service system is designed on the basis of the STKOS, and the STKOS science and technology vocabularies, category systems, and ontology networks are applied to realize the knowledge organization and semantic linking of the scientific and technological information resources. Meanwhile, related knowledge-mining analysis algorithms and models are improved, and some tools such as Solr and D3 are used for developing the system. This system integrates various knowledge service modules, including unified search of domain information resources and knowledge-linked navigation, domain hotspot and burst topics monitoring analysis, knowledge structure and evolution analysis, literature citation network, and research agents’ cooperative relationship network analysis. Findings: The system can help to refine descriptions, knowledge organization, and the semantic linking of various kinds of information resources closely related to science and technology. Such resources include domain literature, institutions, scientists, projects, and more. Research limitations: Trial assessment and performance improvement should be carried out for the knowledge service application on the basis of more types of and larger quantities of domain information resources.Practical implications: The domain knowledge service system provides an integrated knowledge discovery tool, as well as several kinds of knowledge mining analysis services for researchers.Originality/value: Our practice can be used as a valuable guide for libraries and information institutions that plan to provide deep domain knowledge services.