1. LINKED DATA AS A SERVICE WITH THE INFORMATION WORKBENCH SEMTECHBIZ San Francisco 2012 Peter Haase fluid Operations AG

2. fluid Operations (fluidOps) Linked Data & Semantic Technologies Enterprise Cloud Computing Software company founded Q1/2008 by team of serial entrepreneurs, privately held, VC funded Headquarters in Walldorf / Germany, SAP Partner Port Currently 45 employees Named “Cool Vendor for SAP 2010” by Gartner Mar 2010 Global reseller agreement with EMC focus large enterprise customers Apr 2010 NetApp Advantage Alliance Partner Oct 2010

3. The Potential of Linked Data Linked Data Set of standards, principles for publishing, sharing and interrelating structured knowledge From data silos to a Web of Data RDF as data model, SPARQL for querying Ontologies to describe the semantics Benefits of Linked Data in the Enterprise Enterprise Data Integration: Semantically integrate and interlink data scattered among different information systems Simplified publishing and sharing of data: Increase openness and accessibility of Enterprise Data Enrichment and contextualization through interlinking: Value add by linking to Linked Open Data

4. Everything as a Service Abstract from physical implementation details and location of resources Regardless of geographic or organizational separation of provider and consumer “In the cloud” Web based Virtualized On-demand Self-service Scalable Pay as you go Infrastructure as a Service Platform as a Service Software as a Service Data as a Service Next generation of XaaS is centered around the power of data.

5. Linked Data as a Service Data virtualization supported by Linked Data principles 1.Use URIs as names for things 2.Use HTTP URIs so that people can look up those names. 3.When someone looks up a URI, provide useful information, using the standards: RDF, SPARQL 4.Include links to other URIs, to discover more things. Linked Data as abstraction layer for virtualized data access across data spaces Enables data portability across current data silos Platform independent data access Basis for enabling automation of discovery, composition, and use of datasets 5 “Like all members of the "as a Service” family, DaaS is based on the concept that the product, data in this case, can be provided on demand to the user regardless of geographic or organizational separation of provider and consumer.” Source: Wikipedia

6. Data-as-a-Service – Beyond Data Access Data Markets: make it easy to find data from secondary data sources, consume or acquire the data in a usable – and often unified – format Online Visualization Services: allow users to upload data, make charts and visualizations and publish these to an online audience Data Publishing Solutions: allow data owners to publish their data collections and make them available to an online audience Data Aggregators: integrate, cleanse data from different sources to provide the aggregated data as a value added service BI / Analytics as a Service: provide higher level analytics functionality (statistical analysis), reporting, predictive analytics See also: http://blog.datamarket.com/2010/10/24/data-as-a-service-market-definitions/

7. Information Workbench - Linked Data Platform 7 Information Workbench:  Semantics- & Linked Data-based integration of private and public data sources  Intelligent Data Access and Analytics  Visual Exploration  Semantic Search  Dashboarding and Reporting  Collaboration and knowledge management platform  Wiki-based curation & authoring of data  Collaborative workflows Semantic Web Data

8. Enabling Data Discovery: Metadata about Data Sets Metadata about data sources essential for dynamic discovery Access to data registered at global registries, e.g. ckan.org, data.gov, … Based on metadata vocabularies (voID, DCAT) Sort/filter data sets by topic, license, size and many more facets to identify relevant data Visually explore data sets

9. Enabling Data Composition: Federation of Virtualized Data Sources Application Layer Virtualization Layer Data Layer Data Source SPARQL Endpoint Metadata Registry See also: FedX: Optimization Techniques for Federated Query Processing on Linked Data (ISWC2011)

10. Enabling On Demand Use: Self-service Linked Data Frontend Semantic Wiki as user frontend Declarative specification of the UI based on available pool of widgets and declarative wiki-based syntax Widgets have direct access to the DB Type-based template mechanism Ad hoc data exploration, visualization, analytics, dashboards,... Wiki Page in Edit Mode … … and Displayed Result Page

11. Information Workbench – Linked Data as a Service Application Areas Knowledge Management in the Life Sciences Digital Libraries, Media and Content Management Intelligent Data Center Management

12. Information Workbench: Data as a Service in a Cloud Platform Architecture Provisioning, Monitoring and Management Infrastructure Layer (IaaS) Virtualization Layer Network Computing Resources Netw.-Att. Stora ge Data Layer (DaaS) Open Data SourcesEnterprise Data Sources Application Layer (SaaS)

13. Self-service Deployment Data Discovery Self-service deployment of the Information Workbench in the cloud Pay-per-use Scalability on demand On demand access to private and public data sources Dynamic Discovery Data Integration & Federation Living UI, composed from semantics-aware widgets Ad hoc data exploration, visualization, analytics Self-service UI & Analytics Provisioning, Monitoring and Management Infrastructure Layer (IaaS) Virtualization Layer Network Computing Resources Netw.-Att. Stora ge Open Data SourcesEnterprise Data Sources Application Layer (SaaS) Data Layer (DaaS) Virtualized data access Dynamic integration & federation of data sources

14. Example: Conference Explorer 14 „Linked-Data-a-Thon“: build an application that makes use of conference metadata and contextualizes data with external data sources in two weeks Realized with the Information Workbench Data Sources Conference Metadata (Linked Data) Public bibliographic meta data Social Networks: Twitter Facebook LinkedIn LinkedGeoData Features Conference schedule, timelines, hot topics Statistics and reports Background information about authors and publications Link to social network profiles and statistics http://conference-explorer.fluidops.net/

15. Example: A Cloud Portal for Access to Open Data with the Information Workbench Goal Collect meta data from global data markets (LOD Cloud, WorldBank, CKAN, …) Allow integrated search and ad hoc integration of data sources from different repositories Link data with private/internal data sources, if desired Support semi-automated linking between data sets Provide visualization, exploration, and analytics functionality on top of integrated data sources Realization Currently running project with the Hasso Plattner Institute (Potsdam, Germany) Create local repository containing data market metadata Use self-service technology to make services publicly available + Information Workbench for analytics... using the fluid Operations Technology Stack

16. Example: Data Center Management 16 Support collaborative operations management in the data center Link business data to technical data Technical Documentation Analytics and Reporting Performance and Capacity Monitoring Responsibility Management Resource Management Change Management Technical Ticketing System

17. Example: Linked Data in Pharma Integ Public Data Sources Search, Interrogate and Reason Capture and Augment Knowledge Visualize, Analyze and Explore Integrated data graph over all data sources Private Data Sources Main Use Cases Integrate data from company-internal data silos Augment company- internal data with Linked Open Data Collaborative knowledge management Support of internal processes (drug development)

18. Example: Dynamic Semantic Publishing Information Workbench for DSP Collaborative authoring and linking of unstructured and structured semantic data Ontology and instance data management DSP editorial workflows Automation of content creation and enrichment Olympics 2012 requirements A lot of output... Page per Athlete [10,000+], Page per country [200+], Page per Discipline [400-500], Time coded, metadata annotated, on demand video, 58,000 hours of content Almost real time statistics and live event pages with too many web pages for too few journalists Dynamic Semantic Publishing (DSP) architecture to automate content aggregation

19. CONTACT: fluid Operations Altrottstr. 31 Walldorf, Germany Email: peter.haase@fluidops.com website: www.fluidops.com Tel.: +49 6227 3846-527 Visit us at booth 200! http://semtech2012.fluidops.net/