Schema design and query processing in a federated multimedia database system

1. Schema design and query processing in a federated multimedia database system Henrike Berthold & Klaus Meyer-Wegener Dresden University of Technology, Germany CoopIS, Trento, Italy, 05/09/2001 Problem A Federated Multimedia Database System Global schema construction Query processing Summary Henrike Berthold

2. Application 1 Application n SDBS 1 SDBS k MSS 1 MSS n MRS 1 MRS m Problem • SDBS: Database system with a schema, a query language, ... • MRS: Media retrieval system • MSS: Media storage system Henrike Berthold

3. Media retrieval systems • Perform content-based search based on automatically extracted features (perception + semantical primitives) • work for a set of media objects of a certain media type such as image, text, video, audio or a subset with a certain semantics such as passport photos • Retrieval functions • single: search argument (example, feature, weighting), media object ->similarity value • coll: search argument -> list if tuples (similarity value, MID) • result restrictions of coll: lower bound for similarity values, subset of media objects, top n • Example systems: QBIC (IBM), Excalibur Image Datablade, Melodiscov (LIP6) • Problem: only interactive interface and no programming one Henrike Berthold

4. Media storage systems • Store and manage media objects like images, videos • provide operations for those • support especially timed playout of continuous media objects • all systems provide media description data such as size, format • some systems support transactional concepts like durability, atomicity • Example systems: Tiger Shark (IBM), Symphony (Uni Texas), Fellini (Bell Labs), Kangaroo/Memo.REAL (Dresden University of Technology) Henrike Berthold

5. Application 1 Application n FMDBMS SDBS 1 SDBS k MSS 1 MSS n MRS 1 MRS m FMDBS A Federated Multimedia Database System - Database schema and query processing - Operations on media objects - Transactions Henrike Berthold

6. Structured-data Schema (SDS) Media Schema (MS) integrates SDBS1-Schema SDBSk-Schema MSS1-Schema MSSn-Schema Global schema construction based on two intermediate schemas: • Structured-data schema (SDS) = global schema of all SDBS-Schemas • Media schema (MS) = global schema of all MSS schemas Henrike Berthold

7. :TSingleMedia :TObject ContMedia:TContMedia Video:TVideo Audio:TAudio Text:TText 1 * PassportPhoto:TImage City:TImageWithPart CityPart:TImagePart Example media schema Common data model: ODMG, CROQUE • Types and subtype-relation • Classes and subclass-relation Image:TImage Henrike Berthold

8. Schema architecture: Global Schema Structured-data Schema (SDS) Media Schema (MS) integrates SDBS1-Schema SDBSk-Schema MSS1-Schema MSSn-Schema Step 1: Base integration Henrike Berthold

9. Step 2: Integration of media retrieval functions • single: objekt method + • coll: class method -, function - • allows combination of boolean queries with media retrieval queries Henrike Berthold

10. t0 t0 t0 t0 t0 t0 c1:t5 c1:t1 c2:t1 c3:t2 t1 t1 t1 t2 c11:t6 c4:t3 c12:t6 c5:t3 c13:t7 c6:t4 c7:t3 t3 t4 t3 t3 t4 t5 (=t1‘) t6 (=t3‘) t7 (=t4‘) Step 2: Example Henrike Berthold

11. TVisualElement 1..* 1 TLecture TSlide TSingleMedia Time interval Region TVideoElement TVideo y TTextElement TText TImageElement TImage Region for image Region for video Video Image1 Image2 Region for text Text2 Text1 t in min x 2 8 Step 3: Extension • Simple extension: relationships • complex extension: new objects + relationships Henrike Berthold

12. Schema architecture Global Schema Structured-data Schema Media Schema Internal Schema integrates SDBS1-Schema SDBSk-Schema MSS1-Schema MSSn-Schema MRS1-Function MRSm-Function Henrike Berthold

13. Construction data Henrike Berthold

14. Query processing Henrike Berthold

15. GT3 GT1 GT2 GT4 FMDBS-specific problems • Modification • Vertical fragmentation complete replacement of a global object is not possible • Replacement of search methods Henrike Berthold

16. Comprehension syntax Henrike Berthold

17. Monads and algebras Henrike Berthold

18. Advantages • uniform representation of collections (set, bag, list) and aggregations • readability • there are equivalences defined • easy manipulation • there is a mapping to an algebraic expression • embedding in traditional query processing is possible • thus: better suited for manipulations than an object algebra Henrike Berthold

19. Modification Henrike Berthold

20. Improvements • Paths that belong to one source are replaced completely; so far: replacement of each single function • A generator which binds a global object is replaced by a sequence of qualifiers which produce all local objects that are used in the query; so far: production of local objects there, where they are used • exploit function coll and its result restrictions Henrike Berthold

21. Replacement of function single by coll Henrike Berthold

22. Identification of a lower bound Henrike Berthold

23. Identification of a subcollection restriction Henrike Berthold

24. Prototype Henrike Berthold

25. Summary • An FMDBS manages structured data and media data. It takes the integration efforts from the applications. • Development of a procedure to construct the global schema • data (relationships, new types and classes) and media retrieval functions can be added • Development of a procedure to modify queries • can handle the vertical fragmentation • choses efficiently executable media search functions • Applications have a powerful mean to find suitable data Henrike Berthold

26. Outlook • Problem: Chose a result restriction if some are applicable • Need of a general cost model of media search systems • Construction of a complete FMDBS • Need of tools which support the construction and the administration Henrike Berthold