Claremont Report on Database Research: Research Directions (Le Gruenwald)

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This is a set of slides from the Claremont Report on Database Research, see http://db.cs.berkeley.edu/claremont/ for more details. These particular slides are from a "Research Directions" talk by "Le Gruenwald." (Uploaded for discussion at the Stanford InfoBlog, http://infoblog.stanford.edu/.)

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  • Claremont Report on Database Research: Research Directions (Le Gruenwald)

    1. 1. What is to be done? The Future of Database Research <ul><li>Le Gruenwald </li></ul><ul><li>National Science Foundation </li></ul><ul><li>Presented to 2008 Database Self-Assessment Submit </li></ul><ul><li>May 29-30, 2008 </li></ul>
    2. 2. Topics to Consider <ul><li>Formal Data Semantics </li></ul><ul><li>Graph Database </li></ul><ul><li>Human-Centered Database Computing </li></ul><ul><li>Multi-disciplinary Database Research </li></ul><ul><li>Mobile Database </li></ul><ul><li>Database Performance Evaluation </li></ul>
    3. 3. Formal Data Semantics <ul><li>For most of the past 40 years DB community has largely ignored most issues concerning data semantics, even such basic matters as measurement units. </li></ul><ul><li>Nearly all DB systems today lack formal specification of data semantics. </li></ul><ul><li>This issue is of increasing importance as we attempt to integrate more diverse databases. </li></ul><ul><li>Need to provide formal data semantics (metadata), e.g., logic – but which logic? DL, FOL, sorted, ... </li></ul><ul><li>Need ability to integrate and query data semantics. </li></ul><ul><li>Increasing demands for integrated DB retrieval and inference. </li></ul>
    4. 4. Graph Database <ul><li>Big demand: transportation, bio, social networks </li></ul><ul><li>E.g. perform disjunctive queries over different relationship types </li></ul><ul><li>E.g. find the shortest path from point A to point B </li></ul><ul><li>Need a flexible data model and query language </li></ul>
    5. 5. Human-Centered Database Computing <ul><li>Need to accommodate different types of users </li></ul><ul><li>Usability studies </li></ul><ul><li>Visualization </li></ul>
    6. 6. Multi-disciplinary DB Research <ul><li>Need to reach out to other disciplines: </li></ul><ul><ul><li>What are the innovative uses of existing DB research results that enable transformative research in other disciplines? </li></ul></ul><ul><ul><li>What transformative DB research would be derived from the needs of other disciplines? </li></ul></ul><ul><li>Major DB conferences and journals need to embrace multi-disciplinary DB research </li></ul>
    7. 7. Mobile Database <ul><li>Increasing demand for mobile applications (including mobile sensor applications) </li></ul><ul><li>Issues: mobility, disconnection, energy limitation, etc. </li></ul><ul><li>More activities in this area in Europe and Japan than in the U.S. </li></ul><ul><li>Major DB conferences need to embrace mobile database research </li></ul><ul><li>Can energy-aware mobile DB research be extended to achieve GREEN DB for static environments? </li></ul>
    8. 8. Database Performance Evaluation <ul><li>Many of current DB research evaluation plans include: </li></ul><ul><ul><li>Performing simulation experiments using </li></ul></ul><ul><ul><ul><li>Synthetic datasets </li></ul></ul></ul><ul><ul><ul><li>Real-life datasets </li></ul></ul></ul><ul><ul><ul><li>Benchmark datasets (not always available) </li></ul></ul></ul><ul><ul><li>Making some generalized conclusions without regards to statistical relevance </li></ul></ul><ul><li>Too ad-hoc, lack of science -> Need a more credible evaluation approach </li></ul>
    9. 9. <ul><li>THANK YOU! </li></ul>
    10. 10. <ul><li>Extra Slides for additional topics </li></ul>
    11. 11. Data Models for Vector Fields <ul><li>Vector fields occur in many scientific, engineering applications: </li></ul><ul><ul><li>Computational fluid dynamics: weather, climate, oceanography, airplane design, wind turbine design and placement, finite element modeling, .... </li></ul></ul><ul><li>Relational model is largely useless </li></ul><ul><li>Attempts: Fiber Bundle Data Model (lloyd Treinish, ibm walson david butler, limit point), Vector Bundle Data Model (eddie saek, richard Muntz, ucla ...)‏ /*restricive fiber with map from mesh to vector space from one end to another end */ </li></ul><ul><li>Need data models, query languages, ... </li></ul><ul><li>Need interpolation </li></ul>
    12. 12. Shape Based Retrieval <ul><li>Applications: </li></ul><ul><ul><li>Part retrieval, protein docking, protein-ligand binding, drug design, archeology, airplane crash reconstruction, ... </li></ul></ul><ul><li>Need invariant shape descriptions w.r.t. translation and rotation </li></ul><ul><li>Need efficient representations and query processing </li></ul><ul><li>Need methods for “compliant” shape matching (docking)‏ /* mating */ </li></ul>
    13. 13. Impedance Mismatch Between Programming Languages and DBMSs <ul><li>Longstanding problem of integration of queries into programs </li></ul><ul><li>Generally poor support by programming languages </li></ul><ul><li>OODBMSs failed </li></ul><ul><li>Latest effort: Microsoft Linq </li></ul><ul><li>Remains, open, difficult problem </li></ul><ul><li>See related work on XDUCE, CDUCE </li></ul>
    14. 14. Very Large Data Integration <ul><li>Data Integration / DB Federation over large numbers of DB (100's or 1000's) remains unsolved problem </li></ul><ul><li>Increasing important for bioinformatics, intelligence, e-commerce, ... </li></ul><ul><li>Need better metadata, better tools, new approaches ?? </li></ul>

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