2. Andreas Eberhart, fluid Operations AG WP 2 - Optique Review Meeting Munich

3. Overview 3 Optique Architecture & Integration Tomorrow‘s challenges Optique & pilot packaging, deployment

4. 4

5. XRM Datasource / Ontop Repository 5

6. 6

7. Ontology Management & Visualization 7

8. Scalable Mappings 8 Bootstrap mappings from SQL datasource Mapping analysis Find inconsistencies between ontology, datasource and mapping

9. 9

10. Ontology Based Querying 10

11. Widget-Based Collaborative UI 11 Analytics and Reporting Visualization and Exploration Mashups with Social Media Authoring and Content Creation Widgets are not static and can be integrated into the UI using a Wiki-style syntax.

12. 12

13. Streaming Queries 13

14. Streaming Data 14

15. Tomorrow‘s Challenges 15 Customers expect Access Control Platform High Availability Platform Scalability Optique & NoSQL

16. High Availability Delivered with 6.0 release 16

17. Scaleout Architecture 17 fluidOps Cluster RDF Database fluidOps federation layer RDF Database fluidOps federation layer RDF Database fluidOps federation layer RDF Database Parallel reads Load balanced middleware State changes are replicated to all federation layer nodes

18. Powerful Access Control 18

19. Optique & NoSQL 19 Hadoop ElasticSearch HANA Cassandra Spark Polyglot Persistence Define Big Data sources (HBase, Solr, …) Widgets support RDF parameterized native queries {{#widget: TableResult | query='select * from hbase.urls where url like ?:rdfValue'}}

20. fluidOps Platform & Apps 20 fluidOps Information Workbench eCloudManager Customer App Optique StatOil Siemens

21. Capture Knowledge in Apps 21 zip via http

22. fluidOps AppCenter & PaaS Cloud 22

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