Future Generation Computer Systems 23 (2007) 348–358 www.elsevier.com/locate/fgcs Grid organizational memory—provision of a high-level Grid abstraction layer supported by ontology alignment Bartosz Kryza a , Renata Slota b , Marta Majewska b,∗ , Jan Pieczykolan a , Jacek Kitowski a,b a Academic Computer Center CYFRONET-AGH, Nawojki 11, 30-950 Cracow, Poland b Institute of Computer Science, AGH University of Science and Technology, Mickiewicza 30, 30-059 Cracow, Poland Received 20 December 2005; received in revised form 30 June 2006; accepted 3 July 2006 Available online 30 August 2006 Abstract In this paper the problem of managing ontological descriptions for a dynamically-changing Grid environment is addressed. The focus of the research is on unification of semantic descriptions for Grid services and resources through ontologies. The Grid Organizational Memory (GOM) has been designed and implemented to enable storing and accessing Grid metadata, kept in the form of ontologies. In GOM, ontology storage and management are designed to support the natural evolution process both in the knowledge structure and knowledge management services. An important element of the GOM framework is the ontology separation schema, specifying the internal vertical and horizontal dependencies according to the Virtual Organization thematic domains, efficiency of knowledge retrieval and ontology development support. The separation schema is applied in the knowledge base distribution model on the Grid. An ontology alignment-based approach is proposed to minimize user commitment on the Grid ontological metadata, to support ontology usage and development. In particular the ontology similarity based approach is presented as support for ontology updates, e.g. extension with new facts from external ontologies and environments, as well as a more efficient and complete, less implementation-bounded querying process. This paper presents research on semantic description of the Grid environment within the scope of the K-Wf Grid project that addresses knowledge-based semiautomatic workflow construction for applications on the Grid. c  2006 Elsevier B.V. All rights reserved. Keywords: Semantic grid; Metadata management; Ontology similarity; Ontology store 1. Introduction The Grid community has recently been pursuing the idea of the invisible Grid. This concept brings hope for popularization of the Grid in the Information Society. It seems that success will be achieved when, from the end-user’s point of view, the whole complexity of the Grid becomes invisible and its power and various capabilities can be accessed with ease. In order to conceal all Grid details from users, and facilitate as much work as possible for Grid experts, it is necessary to search for powerful, all-inclusive approaches. One of the most important aspects here is the exploitation of knowledge management supported by other crucial methodologies. The idea of using such technologies for various Grid operations has been present in many incarnations of the Semantic Grid ∗ Corresponding author. Tel.: +48 126173520; fax: +48 126339406. E-mail address: mmajew@icsr.agh.edu.pl (M. Majewska). or Knowledge Grid concepts. However, the magnitude of requirements for the development of Semantic Grids leads to solutions based on the semantic descriptions of the Grid. Their number and variety grow over time, as a result of work carried out by the Semantic Grid community, new standards enforcement initiatives, emergence of new user requirements and possibilities offered by new technologies. The Semantic Grid approach is one of the elements of a future interconnection environment which will assist people in solving complex problems [1]. In order to make this environment more versatile, support from knowledge and knowledge management is necessary, resulting in the forthcoming Knowledge Grid methodology [1,2] which makes use of intelligence to enable people or services to take advantage of Grid resources. The K-Wf Grid project [3–5] extends the trend of hiding the complexity of heterogeneous and distributed environments as well as the complexity of applications and data from the user, making intelligent use of the gathered 0167-739X/$ - see front matter c  2006 Elsevier B.V. All rights reserved. doi:10.1016/j.future.2006.07.001