The Information Workbench - Linked Data and Semantic Wikis in the Enterprise


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The Information Workbench is a platform for Linked Data applications in the enterprise. Targeting the full life-cycle of Linked Data applications, it facilitates the integration and processing of Linked Data following a Data-as-a-Service paradigm.
In this talk we present how we use Semantic Wiki technologies in the Information Workbench for the development of user interfaces for interacting with the Linked Data. The user interface can be easily customized using a large set of widgets for data integration, interactive visualization, exploration and analytics, as well as the collaborative acquisition and authoring of Linked Data. The talk will feature a live demo illustrating an example application, a Conference Explorer integrating data about the SMWCon conference, publications and social media.
We will also present solutions and applications of the Information Workbench in a variety of other domains, including the Life Sciences and Data Center Management.

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The Information Workbench - Linked Data and Semantic Wikis in the Enterprise

  2. 2. fluid Operations (fluidOps)Linked Data & Semantic Technologies Enterprise Cloud ComputingSoftware company founded Q1/2008 by team of serial entrepreneurs, privatelyheld, VC fundedHeadquarters in Walldorf / Germany, SAP Partner PortCurrently 45 employeesNamed “Cool Vendor” by Gartner March 2010Global reseller agreement with EMC focus largeenterprise customers Apr 2010NetApp Advantage Alliance Partner Oct 2010
  3. 3. The RDF Data Model predicate object subject
  4. 4. Who am I and Why am I Here?A Linked Data Perspective presenterAt
  5. 5. Who am I and Why am I Here?A Linked Data Perspective foaf:friend affiliation affiliation develops foaf:friend affiliation develops extends extends owl:sameAs develops generalChair affiliation develops
  6. 6. Who am I and Why am I Here?A Linked Data Perspective foaf:friend affiliation develops foaf:friend
  7. 7. Wikis, the Web, Data and Semantics Collboration (on the Web) Structured Data
  8. 8. The Potential of Linked DataLinked 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 semanticsBenefits of Linked Data in the Enterprise• Enterprise Data Integration: Semantically integrate and interlink data scattered among different information systems• Collaborative Knowledge Management and Analytics: Enable cross-organization analysis, interactive analytics, and reporting, resulting in better business decisions• 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
  9. 9. Information WorkbenchLinked Data and Semantic Wikis in the Enterprise• Supports the whole process of interacting with Linked Data • Data integration • Visualization & exploration • Collaborative knowledge management• Open standards and technologies • Semantic Wiki based frontend (Using SMW Syntax) • Supporting W3C standards (OWL, RDF, SPARQL) • Community Edition (Open Source) + Enterprise Edition (Commercial)• Platform for Linked Data Application Development • Base functionality to build applications without programming • SDK for easy extensions • Implementation in Java, very flexible AJAX frontend
  10. 10. Information Workbench - Linked Data Platform  Intelligent Data Access and Analytics  Flexible self-service UI  Visualization, exploration, dashboarding, and reporting  Semantic search  Collaboration and knowledge management  Curation & authoring  Collaborative workflows  Semantics- & Linked Data-based integration of private and public data sources based on data providers  Generic and specific providers for various data formats and sources  Supports established mapping frameworks (e.g. R2RML, SILK, …) Semantic Web Data  Named graphs for managing contexts and provenance 10
  11. 11. Linked Data Integration ApproachesCentralized Integration Virtualized Integration• Following a data warehousing approach • Autonomous, distributed data sources linked through a federation layer• Data providers periodically gather data from sources and lift it to semantic data • No central integration required formats • Data sources can be added ad hoc,• Graph-based data format enables pay-as- on demand you-go integration of legacy data sources • Federation mediator for query processing• Information Workbench comes with (routing sub queries to relevant sources) predefined providers for various formats and data sources (Spreadsheets, XML, …) Query Centralized Query Store Data Provider Federation Mediator
  12. 12. Enabling Data Composition & Integration:Federation of Virtualized Data Sources Application LayerVirtualization Layer Data Layer SPARQL SPARQL SPARQL SPARQL Endpoint Endpoint Endpoint Endpoint Metadata Registry Data Source Data Source Data Source Data SourceSee also: FedX: Optimization Techniques for Federated Query Processing on Linked Data (ISWC2011)
  13. 13. Self-service Linked Data Frontend driven bySemantic Wiki + Rich Widgets• Ontology-driven template mechanism• Declarative specification of the UI based on available pool of widgets and declarative wiki-based syntax• Widgets have direct access to the DB• Ad hoc data exploration, visualization, analytics, dashb oards, ... Wiki Page in Edit Mode … … and Displayed Result Page
  14. 14. Rich Pool of Available Widgets for Interacting with the Integrated DataVisualization and Exploration Analytics and Reporting Authoring and Content Creation Mashups with Social Media All widgets can be integrated into the UI using an intuitive, Wiki-style declarative syntax.
  15. 15. Widget-based Visualization and QueryConstruction
  16. 16. Example Templates
  17. 17. Example: Conference Explorer• „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 Features • Conference Metadata (Linked Data) • Conference • Public bibliographic meta data schedule, timelines, hot topics • Social Networks: • Statistics and reports • Twitter • Background information about • Facebook authors and publications • LinkedIn • Link to social network profiles and • LinkedGeoData statistics 17
  18. 18. Some Notes on Relationship with SMWand WikiData• “People are scared of Wiki markup” • Semantic links for creating structured data is not something that people use • Need for form-based approaches • Wiki editing at most for unstructured documentation• “We need to support diversity” • WikiData: Statements that reify claims • Our approach: Named graphs • Actually: In enterprise settings, we try to fight diversity (aka inconsistency, redundancies, mismatches -> c.f. Semantic Master Data Management)
  19. 19. Information WorkbenchEnterprise Application AreasKnowledge Management in theLife SciencesDigital Libraries, Media andContent ManagementIntelligent Data CenterManagement
  20. 20. BBC Web Site – Powered by Semantic Technologies
  21. 21. Open Sport Ontology
  22. 22. Dynamic Semantic Publishing with the BBCOlympics 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 journalistsDynamic Semantic Publishing (DSP) architecture to automatecontent aggregation 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
  23. 23. Information Workbench DSP Architecture Web-Frontend (Browser) Journalist, Data Architect, ... Authoring Collaboration Visualization Search and Analytics Extensible Widget Pool Visualization Navigation Collaboratio Social Netw. Widgets Widgets n Widgets Widgets Information Data Management Interlinking Extraction Publishing Data Querying Modules and and Workflows Access and Search Enrichment Integration Unpublished Data Published Data Data Layer SPARQL/RDF HTTP Staging Live Database Database
  24. 24. User Roles and Editorial Workflow• Journalist • Media Manager Edit instance data View Instance Data Approve/reject instance data edits • Data Architect• Subeditor Edit instance data and ontology data Edit instance data edits Publish instance data Edit Approve Publish Draft Approved Published Reject Rejected
  25. 25. Demo Dynamic Semantic Publishing
  26. 26. Enterprise Clouds VisionAll resources of an adaptive, cloud-enabled IT environment can be set up, monitored, and maintained from a single, unified, and intuitive management console: Internal and external IT resources accessible across stack without vendor lock-in High degree of automation and IT provisioning at click of button on the level of enterprise landscapes Internal portal of private/public IT services with e.g. pay-as-you-go cost models
  27. 27. Intelligent Data Center Management Problem Solution  Administration silos: compute infrastructure,  Semantic, resource-centric view on data: link storage, application, … business data with data center resources and  Business data not interlinked with technical interrogate heterogeneous resources in a data unified way  CXOs struggle to have an integrated view on  User-defined dashboards, queries, historical the resources employed in the data center data management for analytics and reporting purposes
  28. 28. Integrated View On The Data Center Integration of different software and hardware components, storage systems, compute infrastructures, applications, CRM systems, ticket systems, project catalogs Automatic correlation of data retrieved from various systems Unified view on data and metadata across the border of company units Exploration, analysis, and actions based on the entire data corpus
  29. 29. Data Center Management• 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 29
  30. 30. Link Business Data To Data CenterResources E.g.: link your customers to their Virtual Landscapes using semantic annotations; visually explore the connections between the business information and the data center resources on-demand Use Case: Root Cause Analysis and Error Handling  Identify which customer‘s SAP systems and system landscapes are affected when an error on the storage level occurs  Determine where errors on the application level are coming from  Relate events to each other  Document and compare solutions for events   allows fast reaction for error handling and ensures SLA enforcement Semantic Link in Wiki Page Visual Data Exploration
  31. 31. Share Knowledge Within Your CompanyCollaborative Acquisition and Augmentation of Knowledge withSemantic Wiki Technology Use Case: Technical Documentation and Responsibility Management  Use Wiki to collaboratively maintain technical documentation and best practices  Categorize documentation  Interlink hardware resources with documentation in a central place  Assign responsibilities directly to technical resource Wiki Page in Edit Mode … … and Displayed Result Page
  32. 32. Collaboration and Workflows At data management level – collaborative creation of structured and unstructured documentation directly through the Wiki page of each resource (e.g. using edit-form widgets embedded in the wiki) At process/workflow level – formalize and execute workflows in an automated way Ontology-based edit form for adding missing information Example workflow for a state-based ticketing system
  33. 33. Ticketing Support Integrated tickets and statistics built on top Tickets are directly linked to the personal profile page
  34. 34. Analytics and ReportingEmbed dynamic, user-defined charts directly into Semantic Wikipages E.g.: create tabular summaries of your data and existing connections; specify user- defined charts and dashboards; generate reports based on historical dataUse case: Performance Monitoring and Capacity Planning Monitor the performance & usage of your infrastructure over time using historical data Forecast when new infrastructure resources need to be ordered Analysis of the impact of new hardware options on utilization ratesUse case: Cost and Demand Forecasting Keep track of infrastructure costs for each customer / project Determine what infrastructure resources will be needed when and for which project Compare various infrastructure options in terms of cost Example: Employed VMs over Time grouped by Power Status
  35. 35. Data Integration with the InformationWorkbenchPhase 1 – Integration: Data integration in a central repository via data providers Lift existing data sources to RDF RDF data integration into a central repository Data alignment using a global ontologyPhase 2 – Logical Mapping: Bring together entities from different sources Generate a logical view and map data items Identify and align equal data across different data sources A logical mapping layer derives IDs spanning different data sources
  36. 36. Benefits of the Semantic Master DataManagement in the Data Center Domain Seamless integration creates transparency Improve data quality Reuse data Discover redundancies and inconsistencies Ad hoc analysis Reduce time and effort for search, query and report generation
  37. 37. Conclusion Semantic technologies offer great potential to overcome the challenges of today’s enterprise data management challenges (Semantic) Wikis to support collaboration in the enterprise: knowledge management, publishing, collaborative operations Semantic Wiki + Rich Widgets for self-service Linked Data frontends Plenty of application areas Get started with the Information Workbench:
  38. 38. CONTACT:fluid OperationsAltrottstr. 31Walldorf, GermanyEmail: peter.haase@fluidops.comwebsite: www.fluidops.comTel.: +49 6227 3846-527