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Delving Deep Into Data: The Big Question of Science Evolution

Explore the changing landscape of scientific research with a focus on data processing, management, and reasoning. Delve into key issues such as (re)creation vs. validation, data vs. process, and the importance of standards and frameworks. Discover the different modes of operation in scientific fields and the evolving role of standards in data integration and schema evolution.

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Delving Deep Into Data: The Big Question of Science Evolution

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Presentation Transcript

  1. Deep Thoughts after < 15 minutes of reflection Michael Franklin Jim Frew

  2. The Big Question: Why are we here? Two Primary Answers: • There is a sea change in the way that science will be done. • Processing on a world-wide ever increasing collection of experimental data • From primary collecting to “data mining” • We need to reason about, assemble, manage, and avoid re-doing loosely coupled, long-running, world wide computations. 2

  3. Some Major Issues from Day 1 • (re) creation vs. validation/explanation • Data vs. Process • Talmud vs. (Kosher) Sausage Factory • The “S” Word… 3

  4. The “Bogus”(?) Distinction • Derivation • Provenance • Lineage • Annotation • Pedigree • (Re) creation vs. validation • Is the DPLAP Executable? 4

  5. Subject, Object, Verb? • Which should be our focus? • Edges • Boxes • Both of the above • What flows along the edges? • Data • Control • Events • All of the above 5

  6. Talmud vs. (Kosher) Sausage Factory • We seem to have two very different (perhaps irreconcilable?) modes of operation. • e.g.,Bioinformatics Databases – Continual Accretion of knowledge. • e.g., Physics Experiments – Composable DAGs/GRAPHS/Pipelines leading towards “data products” • Differences: • Scale: Time, Resources, … • Human involvement vs. automation • How desirable, necessary is each? 6

  7. The Great Thing About Standards is… Core + Extensibility Framework: • Keys for Objects (i.e., Identifiers) • Granularity • Equivalence and Similarity • Are these application/scientist-dependent? • Common Terminology/Data Integration • Versioning and Schema Evolution • Need to Choose: • Declarative vs. Procedural • Strongly Typed? 7

  8. What else? 8

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