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fluidOps in Newprot Peter Haase , Michael Schmidt, Andreas Schwarte fluid Operations AG

fluidOps in Newprot Peter Haase , Michael Schmidt, Andreas Schwarte fluid Operations AG. fluidOps NewProt Team. Peter Haase Lead Architect R&D PhD in Computer Science from University of Karlsruhe Long experience in national and EU research projects

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fluidOps in Newprot Peter Haase , Michael Schmidt, Andreas Schwarte fluid Operations AG

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  1. fluidOps in NewprotPeter Haase, Michael Schmidt, Andreas Schwartefluid Operations AG

  2. fluidOpsNewProt Team • Peter Haase • Lead Architect R&D • PhD in Computer Science from University of Karlsruhe • Long experience in national and EU researchprojects • Expertise in semantictechnologies, knowledgerepresentation, ontologiesandcloudcomputing • Co-authorofthe W3C OWL 2 standard • Michael Schmidt • Senior Architect R&D • PhD in Computer Science from University of Freiburg • Expertise in databases, queryoptimization, semantictechnologiesandcloudcomputing • Andreas Schwarte • Development Engineer R&D • MScfrom University of Saarbrücken • Expertise in datafederation, self-service portals

  3. fluidOperations (fluidOps) • Software company founded Q1/2008 by team of serial entrepreneurs, privately held, VC funded • Headquarters in Walldorf / Germany, SAP Partner Port • Currently 40 employees • eCloudManagerProduct Suite introduced in Feb 2009 • Information Workbench introduced in Jan 2010 • Start of CollabCloud project together with German Ministry of Research Nov 2009 • Chosen by the German Ministry of Research • to supply standard interface and self-service cloud portal for German D-Gride-Science backbone initiative Jun 2010 • Named “Cool Vendor for SAP 2010” by Gartner Mar 2010 • Global reseller agreement with EMC focus large enterprise customers Apr 2010 • Chosen NetApp Advantage Alliance Partner Oct 2010

  4. Cloud Computing - Everything as a Service • Abstractfromphysicalimplementationdetailsandlocationofresources • 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 Data asa Service Software as a Service Platform as a Service Infrastructureas a Service

  5. Enterprise Clouds – theeCloud Vision • All 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

  6. eCloudManager in a Nutshell Semantic Integration • Unified API • Access to heterogeneous resources • Unified monitoring of resources • Extendable provider architecture Automation • Automated, on-demand provisioning • Policy engine for error-tracking • Availability monitoring • Orchestration workflows Service Definition • Template Library • Zone definition • SLA definition • Resource reservation and management Analytics Historical data management • Search and exploration • Collaborative documentation • Dashboardsand reporting Self-Service Portal • Multi-user architecture • One-click provisioning • Utilization and (Service-) Availability monitoring • Metering and billing Security User management Role concept • Utilization monitoring • Error- and Failure detection and handling • Audit Log and Jobs Physical Compute Enterprise Application Landscapes Virtual Compute Enterprise Storage Network

  7. Linked Data and Semantic Technologies • Linked Data • Set of standards, principles for publishing, sharing and interrelating structured knowledge • From data silos to a Web of Data • RDF as graph based data model • Ontologies to describe the semantics • Benefits of Linked Data • 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 • Improved user experience: Leveragesemantictechnologiesforbettersearchandpresentation, addressmore expressive informationneeds

  8. Linked Open Data Cloud

  9. Information Workbench - Linked Data Platform • 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

  10. Semantic Wiki + Widgets as Self-service Linked Data Frontend • Semantic Wiki for linking of unstructured and structured data • 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 Wiki Page in Edit Mode … … and Displayed Result Page

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

  12. fluidOps Customers • Won Customers

  13. Example: Linked Data in Pharma • Main Use Cases • Integratedatafromcompany-internaldatasilos • Augment company-internaldatawithLinked Open Data • Collaborative knowledgemanagement • Support ofinternalprocesses (drugdevelopment) Integ Search, Interrogate andReason Visualize, AnalyzeandExplore Capture and Augment Knowledge Integrated datagraphover all datasources Private Data Sources Public Data Sources

  14. Information Workbench for Dynamic Semantic Publishing at BBC 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 • 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

  15. RoleoffluidOps in NewProt, Expectations • Development of a Self Service Portal • Based on Information WorkbenchandeCloudManagertechnologystack(See also presentation on theportalthisafternoon) • Gainexperience in thelifesciencedomain • Potential commercializationoftheportal

  16. CONTACT:fluid OperationsAltrottstr. 31Walldorf, GermanyEmail: peter.haase@fluidops.comwebsite: www.fluidops.comTel.: +49 6227 3846-527

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