The IPAC Research Archives. Steve Groom IPAC / Caltech
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1 The IPAC Research Archives Steve Groom IPAC / Caltech
2 IPAC overview The Infrared Processing and Analysis Center (IPAC) at Caltech is dedicated to science operations, data archives, and community support for astronomy and solar system science missions, with a historical emphasis on infrared-submillimeter astronomy and exoplanet science. IPAC is entering its 30 th year of building and operating successful data centers and research archives for space- and ground-based astronomical observatories and large-scale survey programs. 4/22/13 2
3 IPAC Activities NASA/IPAC Infrared Science Archive (IRSA) NASA Extragalactic Database (NED) Google for galaxies NASA Exoplanet Science Institute (NExScI) Exoplanet Archive Keck Observatory Archive (KOA) IPAC is also home to: Spitzer Science Center NASA Herschel Science Center NASA/US Planck Data Center Las Cumbres Observatory Global Telescope (LCOGT) Archive 4/22/13 3
4 IRSA Overview IRSA is NASA s IR/sub-mm archive Began with IRAS and 2MASS, leading into the decade of IR missions Spitzer Wide-Field Infrared Survey Explorer (WISE) NASA Planck Archive IRSA also provides access to many other mission datasets, including some hosted at other institutions, brought together for the convenience of researchers 4/22/13
5 Purposes behind archiving Permits others to exploit data now and into the future Provides efficient access to mission data to enable research that has not yet been envisioned The most important questions our users want answered are: How do I get (and use) my data? Whom do I ask if I have a problem?
6 Archiving involves: Data curation Data access Documentation Tools for data reduction, analysis User support All are important to ensure usefulness of the data
7 Data access models Find: Discovery/Inventory what s available? Query: Detailed, dataset-specific query Find records/images matching constraints Combine: Multi-dataset query Display data from multiple datasets together Mine: Bulk query Upload list of search positions or other criteria Retrieve: Bulk dataset download Give me the whole thing Remote Access: Direct external access Can I just have my program connect directly to your database?
8 Archive Architecture Ingestion & Validation Storage, Indexing Reusable search engines Catalogs Image/extended spatial Product retrieval Also on-demand generation (e.g. image cutout, mosaic) Program (VO) interfaces Web UI s Support for external UI s
9 IRSA s common architecture supporting other activities NExScI Exoplanet Archive, Kepler Science Analysis System Keck Observatory Archive 20 years of observations Solar System NEOWISE Non-NASA: P60, PTF LCOGT LSST TCCON (Atmospheric research)
10 Questions to ask in archive design What are the products? Standard levels of processing/calibration/reduction? What are the use cases for search&retrieval? What are the units for data packaging, query, retrieval? What can be queried? Metadata date, instrument, position, etc Pre-calculated summary metrics/statistics Measurement data Derived/calculated properties, combinations of data Any proprietary data considerations? Mixing public and private data within the archive can greatly complicate handling of queries involving summary information
11 Questions - 2 Who needs access to the data? When do they need access? Real or Near-real time notification, event distribution: a topic all to itself! Hours/Days/Months/Years later Acceptable query latency? Interactive vs batch-style queries Anticipated usage/volume
12 Things to think about Consistency of formats & organization Completeness/Correctness of data initial validation is important Completeness of documentation Examples are helpful! Data reduction cookbooks User tutorials, workshops Important for the long haul: Consider longevity of technologies, data formats, programming languages/systems Media lifetime, periodic refresh
13 Trends: Rapid evolution of information-handling systems Technology for data handling changes even more quickly than technologies for photon gathering Fast internet everywhere Extremely portable disks and drives Grid computing and protocols for remote analysis The cloud
14 Trends: Archives as analysis environments Browse-and-download Identify data of interest, take it home for further study Complex queries Finding interesting data within large datasets In-database analysis? More complex queries over larger data volumes Data size growing faster than communications Bringing the software to the data? Big Data means you can t move it.
15 Common Formats and Tools Catalogs tabular data Images usually as FITS files Spectra Time-series photometry - light curves
16 Configurable user interfaces Decreases the costs of setting up access to new data sets and the costs of long-term maintenance. Provides unified user experience.
17 Summary Preservation of science data products as well as lower-level products enhances future research Can t predict all potential use cases Pay attention to formats, provenance, documentation Future usefulness of the data depends on it Quality can be subjective. One man s trash is another man s treasure. Caveat Emptor Reusable building blocks can effectively support a wide range of use cases Distinct perspectives for rapid vs long-term utilization Fast observation followup vs future data mining Discovery vs research use cases
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