Federated Service Oriented Information Management

1. Federated Service Oriented Information Management Ahmet Sayar asayar@cs.indiana.edu

2. Introduction • Aim is utilizing distributed heterogeneous information and knowledge provided by different repositories and vendors in an efficient and robust manner. • No agreed upon –useful- architecture framework for • Federating • Obtaining • Analyzing • Interpreting the heterogeneous distributed data/information for decision makers in scientific application domains

3. Motivation • SOA based on Web Services • Information Sources are “Filters”: • A service inputs DIKW (Data-Information-Knowledge-Wisdom Hierarchy) from Grid and outputs DIKW • Web Services, easy to extend and federate. • Easy to publish, located and bind. • predictable input and output interfaces and defined by metadata • Information management through ASIS (Application Specific Information System) framework in Science Domains such as GIS. • Data and metadata concepts and formats • A repository or sensor has or gets DIKW from "outside Grid"; it outputs DIKW

4. DB DB DB DB DB DB DB DB Problem Recognition Coverage data SS Vector data netCDF Bitmap data Image jpeg SS SS Binary data HDF5 XML data SS Bar graphs Plots images Statistics data SS Interactive Tools

5. Problem Recognition • Services like discovery and notification do not need to be made application specific. • BUT If the domain changes then : • choices, • Database requirements, • data format, • core service requirements, • attributes, and • metadata context CHANGES ! • What are the common concepts and characteristics for • Data, • Metadata, • Query Language, • Services, and • Communication language, in order to drive information/knowledge from the heterogeneous data/information sources in Application Domains ?

6. Overall Structure Solution • ASL : Application Specific Language. XML based hierarchical data representation format. • Cross language, platform and operating system • ASVS : Application Specific Visualization System • Last filter before the decision maker. • Provides information/knowledge in human readable formats • ASFS : Application Specific Feature Service. • Stores and provides common data model (ASL) • Treat binary and common data (in ASL) differently. ASFS ASVS Display AS Repository AS Tool (generic) AS Service (user defined) AS Tool (generic) AS “Sensor” Message Using ASL

7. Overall Structure Solution -cont • Common data (in ASL) is kept in ASFS. Enables interactive querying through GUI. • Tentative architecture. • In the DIKW world, everything is mixed as data and filters • In a given domain every filter speaks in ASL • ASVS both visualize information and provide a way of navigating ASFS and their underlying DB. • ASVS can itself be federated and present output interface. • GIS and Astronomy have some standards but not many others have

8. Vector data Raster data Data capability Interactive Decision Support FS Example (1):GIS Domain (OGC) • FS-1 : Master Filter (WMS) • Providing the available data list and capabilities to the end user clients - Interactive tools • FS-2 : Web Feature Server • Provides vector data such as rivers, state and city boundaries in GML • FS-3 : Web Map Server • Provides image data in the form of jpeg, svg, png etc. Defined in its capabilities file • FS-4 : Web Coverage Server • Provides coverage (raster) data. Grided data, pixel info • Query : No Standard – Filter specification – SQL • Data Encodings : GML, images • Metadata : capability doc. • No event notification – we use WSContext for asynchronous run • Registry : WRS – MD • Queryable Data in : WFS Data:b FS-4 (Minnesota) Data:a MD FS-2 FS-3 Data:b Data:c (Nasa) (CGL) FS-1 (CGL) Data:a Data:b Data:c PORTAL Data:a Data:b Data:c

9. DB DB DB Data capability Interactive Decision Support Example (2):Astronomy Domain (IVOA) • FS-1 : VOPlot • Integrating, Interacting visualization tools • FS-2 : SkyNode • ADQL based SOAP interface returning VOTable based results • FS-3 : SIA • 2D sky projection, logically a grid of pixels encoded as a FITS image • FS-4 : SSA • URL-based returning a dataset "document" (VOTable) • Query : ADQL –extension of SQL • Data Encoding: VOTable, FITS • Metadata : UCD, VOResource • Event notification : VOEvent • Registry : VORegistry • QueryableData in : SSAP and SIAP, VOStore FS-3 FS-4 FS-2 FS-1 MD PORTAL

10. Interactive Decision Support Tools- Interactive query,- Interactive display, movie and animation- Integration to Application Science Simulations http://virtualsky.org (R. Williams et al.)

11. Issues To Be Discussed (1) • Requirements for the domain metadata in capability • What does capabilities do and need to have to federate filters? • Requirements for the ASL (such as CML, GML) • What does ASL need to have to federate the filters? • Concept of data (such as feature, coverage) • Common representation? Possible? To what extend? • A common information management framework which can be applied to any domain. • some instructions- any field, what needs to be done

12. Issues To Be Discussed (2) • Application level data/information federation • Integrating the system with application science simulations. • Creating interactive decision support tools utilizing integrated filter services. • Tools for map animation, map movies, images • Interactive query support to get further information on the image and/or animation. • Enabling binding of services into pipelines with or without human intervention through metadata. • Caching and load balancing to handle large scientific data in an efficient and robust manner (application based)

13. Summary of SRB & Ogsa-DAI • SRB • Storage Resource Broker • Uniform access to dist. heterogeneous data resources by attributes • Catalog service is MCAT (Metadata Catalog Service) • Resource and data location transparency • Remote authentication authorization – user groups • Not just for access, transferring and replicating • Sample projects using SRB: BIRN and NASA IPG • Ogsa-DAI • Open Grid Service Architecture - Data Access and Integration • Access to heterogeneous data via common interfaces on the grid. • Catalog service is MCS (Metadata Catalog Service) • OGSI-compliant Grid • Components are Grid services. Resources should be registered. • Sample projects using Ogsa-DAI : LEAD, MyGrid

14. Discussions on SRB & Ogsa-DAI • SRB • Monolithic – does too much • MCAT dependent • MCAT has limited support for application-level metadata • Need diff metadata for diff domain, and extensions for applications • Not standard based – Not open source • Not handling data based on DIKW hierarchy • Ogsa-DAI • At the data and Database level • MCS dependent • MCS has limited support for application-level metadata • Need diff metadata for diff domain, and extensions for applications • For Grid applications - GGF standards • Data only in relational and XML database or ordinary files • Not handling data based on DIKW hierarchy

15. Our Work Compared to SRB & Ogsa-DAI Ready to use information and knowledge Wisdom decisions, knowledge and information extraction by the user • Reusable components Filter Services with specific ports and interfaces • Distributed DIKW abstraction • Metadata in capability document • Metadata aggregators • New metadata for different domains • User uses just getData interface to query • -Central data access abstraction. Uniform access to heterogeneous data sources • Metadata : SRB/MCAT, Ogsa-DAI/MCS • Both provides extensible metadata arch for diff domains • SRB has “zone” concept address similar issues but different FS FS FS MasterSRB Ogsa-GDSF SRB Agents Ogsa/GDS FS FS FS R R R R R R Wisdom decisions Information/knowledge Data access and query

16. Why are we different ? • SOA (Service Oriented Architecture) • Easy to extend • Reusable components • Cross platform and language. • XML based hierarchical data representation • Easy data integration • Easy querying • Human readable information • Easy to access data – no command line • Interactive tools • On the fly query creation. • Not only accessing data but also transforming through its path to end users. • Ports to integrate application simulation to application specific information system (ASIS)

17. Contributions • Instructions how to build ASL and metadata in capability for the application sciences. • Instructions how to build application specific information system (ASIS) federating multiple filters speaking ASL. • Information grid (ASIS) formalization through capabilities metadata, defining all the data/information sources as interacting Web Service filters with standard metadata service ports. • Optimize and enhance the distributed heterogeneous information management.

18. THANKS asayar@cs.indiana.edu Ahmet Sayar