]> CWI will be primarily involved in WP2 and work together with OpenLink on improving RDF data management with state-of-the-art database research approaches. CWI will be involved with a minor stake in WP5 in order to evaluate and adapt browsing and navigation in large-scale knowledge bases. The Stichting Centrum voor Wiskunde en Informatica (CWI) is the Dutch national research institute for mathematics and computer science. It is a private, non-profit organization located at the Science Park Amsterdam. CWI’s mission is twofold: To perform frontier research in mathematics and computer science, and to transfer new knowledge in these fields to society. This is realized by several means. In addition to the standard ways of disseminating scientific knowledge, CWI actively pursues joint projects with external partners, provides consulting services, and stimulates the creation of spin-off companies. Special efforts are made to make research results known to non-specialist circles, ranging from researchers in other disciplines to the public at large. CWI also manages the Benelux Office of the W3C and hosts both the Semantic Web Activity Lead and the chair of the XHTML and XForms Working Group. CWI has always been very successful in participating in European research programmes (e.g. VITALAS, K-SPACE, QAP, CREDO, MUSCLE, and others) and large-scale national research programmes (e.g., programmes BRICKS, MultimediaN, and VL-e; NWO Veni, Vidi, Vici grants). It has extensive experience in managing these collaborative research efforts. CWI is also strongly embedded in Dutch university research: about twenty-five of its permanent senior researchers hold part-time positions as professors at universities and many projects are carried out in cooperation with university research groups. CWI receives a basic funding from the Netherlands Organization for Scientific Research (NWO), amounting to about two third of the institute’s total income. The remaining third is obtained through national research programmes, international programmes, and contract research commissioned by industry. CWI hosts a staff of 235 full time employees, 50 permanent scientific staff, 135 temporary scientific staff, and 50 support staff. The Information Systems (INS) group led by Prof. Dr. Martin Kersten is participating in the LOD2 proposal. 2 2012-02-29 2013-04-30 D12.2.2 – IPR plan D12.2.2 – Intermediate Project Reports 2011-02-28 D2.1.2 – State-of-the-Art and LOD2 Laboratory 2011-08-31 D2.3 – Integration of OpenLink Virtuoso and MonetDB The results of T2.5 are involve cutting-edge database research, yet will be available in an open-source release of CWI’s open source database system MonetDB. Where useful, OpenLink will incorporate such features in a later Virtuoso release as well and make them available to the LOD2 Stack via its virtual database feature (effectively embedding MonetDB into Virtuoso). 2012-08-31 D2.5 – MonetDB release with optimized graph path processing 2012-02-29 D5.1.2 – Initial geo-benchmark definition 2013-08-31 NUIG will guarantee technical excellence in reliable large-scale data processing with the same practices which have been daily driving the works behind the Sindice and Sig.ma projects. NUIG will provide the relevance, feasibility and consensus of the initiative thanks to the continuous interaction between the Linked Data community and the Linked Data Research Centre, a cross institute initiative. National University of Ireland, Galway (NUI, Galway) - Digital Enterprise Research Institute (DERI) is one of the main actors in research and development of semantic technologies in the world. NUIG performs research in the Semantic Web, social networks, sensor network platforms and applies its research results to solve integration problems in various application-oriented projects in eLearning, eGovernment, eBusiness, and eHealth. NUIG develops advanced Semantic Web infrastructures, such as Semantically Interlinked Online Communities (SIOC), semantic search engines (SWSE, Sindice), and platforms for running large-scale, data-intensive experiments, which facilitate collaborative social working environments, scalable storage and reasoning engines, distributed computing, and ontology development. NUIG actively participates in and leads research funded by the EU FP7 program (FAST, Romulus, Okkam, CONET, PECES, iMP), the EU FP6 program (DIP, SUPER, SemanticGov, NEPOMUK, TripCom, RIDE), Science Foundation Ireland (LION) and Enterprise Ireland (SAOR, eLITE). National University of Ireland, Galway (NUI, Galway) - Digital Enterprise Research Institute (DERI) is one of the main actors in research and development of semantic technologies in the world. NUIG performs research in the Semantic Web, social networks, sensor network platforms and applies its research results to solve integration problems in various application-oriented projects in eLearning, eGovernment, eBusiness, and eHealth. NUIG develops advanced Semantic Web infrastructures, such as Semantically Interlinked Online Communities (SIOC), semantic search engines (SWSE, Sindice), and platforms for running large-scale, data-intensive experiments, which facilitate collaborative social working environments, scalable storage and reasoning engines, distributed computing, and ontology development. NUIG actively participates in and leads research funded by the EU FP7 program (FAST, Romulus, Okkam, CONET, PECES, iMP), the EU FP6 program (DIP, SUPER, SemanticGov, NEPOMUK, TripCom, RIDE), Science Foundation Ireland (LION) and Enterprise Ireland (SAOR, eLITE). 3 Project coordination; develop knowledge structuring and enrichment algorithms as well as browsing, visualization and authoring interfaces; collaborate with OKFN in order to employ LOD2 results in the PublicData.eu use case. Universität Leipzig is one of the oldest (founded 1409) and largest (30.000 students) universities in Germany and focuses on interdisciplinary research in the life sciences, cognitive sciences and linguistics as well as mathematics and computer science. The Institute for Applied Computer Science (InfAI) at Universität Leipzig hosts world class research groups in service sciences, knowledge engineering and management as well as natural language processing. The approximately 20 researchers of the Agile Knowledge Engineering and Semantic Web (AKSW) research group at InfAI are establishing theoretical results and scalable implementations for the field. Particular emphasis is given to areas such as ontology creation and manipulation, knowledge extraction, ontology learning and information & data integration on the Semantic Web. The implemented tools and services developed by the group enjoy considerable popularity, the open-source semantic web framework OntoWiki for example is downloaded more than 500 times each month and applied in usage scenarios ranging from the authoring of bio-medical ontologies to knowledge management for the enterprise. InfAI is leading several large-scale collaborative research projects on the national and EU levels such as OntoWiki (EU FP7), Internet Media Businesses (EU SMART), PreBIS (German BmbF) and Factory ServNet (Eureka) and participates in many more. 1 MonetDB is an open-source high-performance database system that allows to store relational, XML and RDF data, downloadable from monetdb.cwi.nl. While being well-known for its columnar architecture and CPU-cache optimizing algorithms, the crucial aspect leveraged in the scope of this project is its unique run-time query optimization framework which provides a unique environment to crack the recursive-correlated-self-join queries caused by semantic web queries to triple stores. MonetDB is an open-source high-performance database system that allows to store relational, XML and RDF data, downloadable from monetdb.cwi.nl. While being well-known for its columnar architecture and CPU-cache optimizing algorithms, the crucial aspect leveraged in the scope of this project is its unique run-time query optimization framework which provides a unique environment to crack the recursive-correlated-self-join queries caused by semantic web queries to triple stores. Objectives of this work package are: (1) to develop use case specifications and to collect user requirements by consulting the communities of practice relevant for the LOD2 use cases and additional prospective application scenarios, (2) to identify technical constraints as well as standards, (3) to produce the architecture and the LOD2 Stack design and (4) to produce an early prototype of the LOD2 Stack in the first year. 1 WP1 – Requirements, Design and LOD2 Stack Prototype The general aim of this work package is to establish a worldwide focal point for academic and industry parties interested in contributing to or taking advantage of the novel Linked Data methodologies and components, which will emerge in the project. 10 WP10 – Training, Dissemination, Community Building, Fertilization Realizing the vision of LOD2 together with the ones of the three use cases will have significant socio-economic impact. Standardization of such an architecture and exploitation of knowledge and technical results (and related IPR) is covered in this work package. 11 The project management will entail strategic, project-wide as well as day-to-day central management and coordination activities. The several different management boards which will be established in the consortium will be responsible for decisions and activities of different scope and level according to their function. 12 This work package implements the LOD2 knowledge store component needed for managing the Web of Linked Data as a vast database. The starting point is OpenLink Virtuoso and MonetDB on the database side and Sindice on the information retrieval side. The present data volumes handled are around 10 billion RDF triples and the target is over the 1 trillion triples. The approach is scale-out out (physical) complemented with significant scalability improvements in the RDF engine (logical): Physically, when data grows, servers can be added and data redistributed without interruption of service, ibid for server failure. Logically, there is no point answering questions nobody is asking. Therefore the base data is kept as RDF with text indexing and search ranking. Additional inference results or indices for caching joins are made as a by-product of querying; further exploitation of such (partially) materialized inferences through the graph at run-time is to exploit structural correlations in the graphs. This work package implements the LOD2 knowledge store component needed for managing the Web of Linked Data as a vast database. The starting point is OpenLink Virtuoso and MonetDB on the database side and Sindice on the information retrieval side. The present data volumes handled are around 10 billion RDF triples and the target is over the 1 trillion triples. The approach is scale-out out (physical) complemented with significant scalability improvements in the RDF engine (logical): Physically, when data grows, servers can be added and data redistributed without interruption of service, ibid for server failure. Logically, there is no point answering questions nobody is asking. Therefore the base data is kept as RDF with text indexing and search ranking. Additional inference results or indices for caching joins are made as a by-product of querying; further exploitation of such (partially) materialized inferences through the graph at run-time is to exploit structural correlations in the graphs. 40 40 1 1 2 2 WP2 – Storing and Querying Very Large Knowledge bases WP2 – Storing and Querying Very Large Knowledge bases The objectives of WP5 are to develop new browsing, visualization and authoring interfaces for LOD, which support a wide range of devices (from mobile phones to desktop PCs), which integrate heterogeneous information from various sources and support the evolution of both instance data as well as information structures over time. In order to achieve these objectives we will explore new browsing and visualization paradigms. 5 WP5 – Adaptive Linked Data Visualization, Browsing and Authoring