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Data Discovery: Drilling down into Compound Data Objects - Granularity and Persistent Identifiers

Data Discovery: Drilling down into Compound Data Objects - Granularity and Persistent Identifiers. Arnold Rots SAO/ CXC. Discoverability. Scope: higher level data products Scattered over many repositories Requires Persistent Identifiers (PID) Registry infrastructure M etadata standards

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Data Discovery: Drilling down into Compound Data Objects - Granularity and Persistent Identifiers

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  1. Data Discovery:Drilling down into Compound Data Objects- Granularity and Persistent Identifiers Arnold Rots SAO/ CXC IVOA Interop Waikoloa/DCP: PID Granularity - Arnold Rots

  2. Discoverability • Scope: higher level data products • Scattered over many repositories • Requires • Persistent Identifiers (PID) • Registry infrastructure • Metadata standards • Metadata extraction tools • Provenance information • But this is only part of the problem IVOA Interop Waikoloa/DCP: PID Granularity - Arnold Rots

  3. Complex Cases • Versioning • Purists will insist that PIDs are version specific • Growing realization that users often prefer current default • Improved calibration, more complete datasets, etc. • Version information can also be appended to the “root” PID • Compound datasets or data objects • Made up of smaller components • Multiple files, multiple data objects, etc. IVOA Interop Waikoloa/DCP: PID Granularity - Arnold Rots

  4. Drilling Down intoCompound Data Objects • From the user’s perspective • For instance, a user interested in masses of galaxies • “Get me papers on galaxy mass estimates” • Respond with a list of pointers to papers in ADS • “Get me galaxy mass estimates” • Don’t provide the list of papers, provide pointers to the electronic versions of the tables in those papers • “Get me mass estimates for M81” • Just provide the relevant number(s) IVOA Interop Waikoloa/DCP: PID Granularity - Arnold Rots

  5. How to Drill Down? • The obvious way is to implement this by introducing a hierarchical structure in the tokens tacked on to the end of the PIDs • However, watch out for interference with versioning • A table (figure, …) can easily be identified as a component of a paper, but a single cell in the table??? • Need vastly more metadata about the content of compound data objects • How do we know what users may want to retrieve? • Would it be sufficient to store the quantities contained and the objects covered, then parameterize? IVOA Interop Waikoloa/DCP: PID Granularity - Arnold Rots

  6. Forward At this time we are trying to solve the issue of how to cite simple datasets and data objects Next we will need to put effort into discoverability But I strongly believe the demand for more sophisticated data discovery, this drilling down into compound data objects, is just around the corner Several people at RDA seemed to be thinking in the same direction – that is a hopeful sign In whatever we are working on now, though, we need to keep the future perspectives in mind IVOA Interop Waikoloa/DCP: PID Granularity - Arnold Rots

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