1. Distributed Archives Interoperability Cynthia Y. Cheung NASA Goddard Space Flight Center IAU 2000 Commission 5 Manchester, UK August 12, 2000

2. Current Status Global Astrophysics Data Resources Loosely Connected By the Internet – Observational data archives or repositories – Derived data products (astronomical catalogs, browse images, video) – Data analysis packages – Visualization/presentation packages – Special services (bibliography, discipline-specific knowledge bases, directories) Distributed Storage, Processing, and Management – Multispectral surveys (Data volume ~ terabytes) – Islands of Information? Requires both Vertical and Horizontal Integration

3. Path to the Future Current (connections via hyperlinks): one to one Near Future (connections to multiple DBs all at once, via middleware): one to many Long Term (multiple inter- connectivity, federated databases): many to many - Distributed Autonomous data centers - Intelligent Agents - User-defined Profiles and Preferences - Access via Multiple Interfaces User Middleware Resources

4. Components of Interoperability Integrated search and discovery - URL Registry (e.g., Yellow Pages, GLU, AstroBrowse) - Query processor (e.g., AMASE, ISAIA) - Browsing/visualization to support selection (ADC Data Viewer, AEQ) - Batch queries (Feed output stream of one data service to another) - Tools to support integration of results Data and software exchange - FTP of data and software updates (pull) - Download of Browser Plug-in (pull) - Automated Updates (HST DB replication) (push) - Hybrid Techniques (with data cache or aircache) (push & pull) - Packaging of software with data (XDF)

5. Technical Issues and Challenges Example: Positional correlation of objects in a region of the sky across multiple wavelengths (Radio, IR, Optical, UV, X-rays, Gamma Rays) Data volume and network bandwidth – Cache of pre-computed results (e.g., astronomical catalogs) – Data filtering at data site, ship results only – Deployment of user code (platform independent S/W) – Data visualization for exploration and selection Registration, Sensitivity, Positional Accuracy – Coordinate transformation on a large scale – Calibration and normalization Query Optimization across Multiple Sites – Query execution plan for efficient cross-correlation – Indexing for fast access

6. Semantic Interoperability Content-based Searches – Science goal driven queries instead of SQL Data Understanding (Domain Context) – Human Interface —> S/W Mapping —> Object-oriented Mapping Data Annotation for Correct Interpretation – Measured parameters, units, quality, range of validity – Algorithm and calibration used, pedigree – Theoretical models applied Data Organization – File directory structure – Database schema Need Information in both Machine-understandable and Human-understandable form

7. Metadata Standards Syntax – Directory Structure – Size, Format, Location, URL Semantics – Usage Convention (e.g., FITS) –Extensible Standards to Encompass Different Disciplines (DTD, XML) – Astronomical Nomenclature and Designation Conceptual Data Model Metadata Language or Representation – FITS, ASCII, IEEE Binary –Astronomical XML

8. Aspects of Metadata Usage [Ref: Bretherton & Singley 1994 Proc of 7th SSDBM, p. 166] Search, browse, retrieval (Human) –Data extraction and interpretation –Navigate among services Ingest, quality assurance, (re-)processing –Science product generation pipeline –Content analysis Storage, archive (Data Management) –Information relevant for effective system design and operation Application to application transfer (Machine) –Enable “ context ” interchange (distributed queries and transformations) Need transfer language with mappings from conceptual level to different logical representation

9. Other Supporting Tools Interface Standards for Software Tools Tools for Schema Mapping – Document logical structure of database (key elements and relationship) – Mapping of local definitions into common terminology – Track changes and updates at other sites Tools for Data Integration and Fusion – Dynamic Interface with user preferences – Intelligent Software Agents to mediate interaction Goal: Global query to many distributed autonomous evolving data resources