The Linked Data Value Chain Model: A Methodology for Information Integration and Orchestration
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1 Na/onal Research University Higher School of Economics The Linked Data Value Chain Model: A Methodology for Information Integration and Orchestration Daniel Hladky Semantic Web Lab at HSE/W3C 28 November 2013
2 About Me Background Computer Science and Economics SAP AG, ixos (OpenText), Ontos NRU HSE / W3C Russia Slavyanskaya Sq. 4 Bldg Moscow, Russia E: dhladky@hse.ru E: dhladky@w3c.org.ru Research Interest Linked (Open) Data for Government & Enterprises NLP, Seman/c Web, Business Impact of Linked Data Ac3vi3es Researcher EU FP7 GeoKnow (within Ontos), LOD Russia KESW 2012 (Lecture Linked Enterprise Data), KESW 13 (Co- Chair) PC member at ISWC/WoLE (2012, 2013), MLW Rome (2013) W3C Russia office hosted by NRU HSE Moderator Open Data at RIAN Co- organising Skolkovo CREI proposal with KAIST, ICSI Berkley, EIS Bonn 2
3 1. Introduction to Research project The Linked Data Value Chain Model: A Methodology for Information Integration and Orchestration Equipment and assets Finance Sales & Marketing Equipment & Assets Enterprise-Wide Reusable Information Finance Sales & Marketing 3
4 2. Topic in the research community Organization Data (Intranet) News & Social Media Linked Open Data Semantic Knowledge Base Firewall Structured Data - ERP, CRM, RDBMS Public Data (External) Unstructured Data Semi-Structured Data - Papers, Legacy documents - Wikis, Calendars, CMS s, Blogs References (excerpt) D. Wood Linking Enterprise Data T. Heath, C. Bizer Linked Data B. Hu, G. Svensson A case study of linked enterprise data FP. Servant Linking Enterprise Data P. Frischmuth, S. Auer Linked Data in Enterprises Sources that talk about this are ISWC LDOW WWW Semantic-Web-Journal EU funded projects 4
5 4. Research Tasks and Objectives Harvest Normalize Semantize Enrich Build Expose 1. Can we develop a simple and suitable model that captures the Linked Data paradigm in relation to the value chain? 2. Does the Linked Data model support the understanding of information integration using Linked Data technologies? 3. Can we define a model for measuring and quantifying the value of Linked Data information integration along the value chain? 5
6 4. Research Tasks and Objectives Criteria 1 Model A model to capture the Linked Data Value Chain. Criteria 2 Value Algorithm and method to measure the value by comparing the metrics from the manual and the tool supported process. Criteria 3 Prototype A software prototype that will demonstrate how the automation of the Linked Data stack can be orchestrated. 6
7 5. Importance Information Integration ROI Valuation LD Orchestration Database Integration - taxonomies, schemas Fusion and Linking - Across heterogeneous data Web Services - REST, SOA, API etc Tools - MDM, BI, Portals Justifying Investment - Model to evaluate investment ROI Adoption - Extend existing models to the new Linked Data Paradigm Ease of Use - Simplifying process for non expert users Workbench / Platform - Integration of tools Flexibility - Configuration and adoption to new needs 7
8 6. New Research Area 1. A New Model 1. Linked Data Value Chain Model 2. ROI algorithm to valuate the model 2. Linked Data Framework 1. Orchestrating the LD Process 2. Simplifying the information integration 3. Proof of Concept to measure impact 8
9 6.1 Research Area Linked Data Value Chain Model Types of Data Raw Data Linked Data Human- Readable Data provides Linked Data Roles Raw Data Provider Linked Data Provider Linked Data Applica/on Provider End User can act as can act as Participating Entities En/ty 9
10 6.2 Linked Data Orchestration Framework LDP Orchestra3on Framework Download Ontologies Meta Information Database Open Data Set - 2 WWW Ontologies Ontology to RDB mappings LOD Discovery Results Open Data Set - n Create and modify Ontologies Ontology Editor Instance Editor Ontology to RDB Mapper D2RQ / R2RML Automa3c Link Discovery Manual Edi3ng and Correc3on Link RDF Database Objects to Open Data Set Objects Open Data Set -1 Miner / MiniDix Ontology mapper Object Link Discovery Edit RDF Objects External Rela3onal Database Map Ontology to RDB and generate RDF dataset SPARQL endpoint RDF Database OntoQuad plays role of the central Storage for the collected triplified RDF data OntoQuad 10
11 7. Experimental results 11
12 7.1 Experimental results Task comparison (simplified) Task Avg. 3me before Avg. 3me with LD 12
13 8. Comparison ROI using the LDVCM 13
14 9. Conclusions Criteria 1 Model A new Linked Data Value Chain Model is developed and captures the Linked Data Paradigm for Informa/on Integra/on. Criteria 2 Value The LD Value Chain ROI Algorithm is suitable to measure the impact and efficiency. A significant impact is shown using the Linked Data Orchestra/on Framework. Criteria 3 Prototype A Linked Data Orchestra/on Framework is developed and tested using the CRM example, LOD Russia and GeoKnow. 14
15 10. Research Summary Practical implementations LOD Russia Ministry of Education and Science Russia, Contract of October 20, 2011 GeoKnow Generator EU FP7 funded project, Grant Agreement No DoW Linked Data Orchestration Workbench Swiss CTI funded project Papers (excerpt) Hladky D., Maltseva S.V., Linked Data Paradigm for Enterprises: Informa/on Integra/on and Value Chain, Business Informa/cs Journal No 24/2013 Hladky D., Drobyazko G., Klintsov V., Enabling Russian Na/onal Knowledge with Linked Open Data, In Proc. of ISWC/WoLE2012, Boston, 11 November 2012 Hladky D., LOD Russia Enabling Russian Na/onal Knowledge with scien/fic Open Data, In Proc. of PMOD Using Open Data, Brussels, Belgium, June 2012 Hladky D., Sustainable Advantage for the Investor Rela/ons Team through Seman/c Content, Book Chapter for Seman/c Web, ISBN , Publisher In- Tech, DOI: /7307, 2010 Efimenko I., Hladky D., Khoroshevsky V.F., Klintsov V., Seman/c Technologies and Informa/on Integra/on: Seman/c Wine in Media Wine- skin, In Proc. of the 2nd European Seman/c Technology Conference (ESTC2008), Vienna,
16 Q&A Thank You 16
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