The Virtual Radiation Belt Observatory (ViRBO) and the Future of the VxO Environment

1. The Virtual Radiation Belt Observatory (ViRBO) and the Future of the VxO Environment R.S. Weigel Department of Computational and Data Sciences George Mason University, Fairfax, VA

2. Abstract ViRBO (http://virbo.org/) is one of the domain-specific virtual observatories that began operations in Fall, 2006 and is funded under the NASA Heliophysics Data Environment program. This presentation will cover three topics: (1) the data products available or exposed through ViRBO, (2) our experience in developing a VxO over the past three years, and (3) our perspectives and predictions about the future of the VxO Environment based on this experience. Data available through ViRBO include measurements from the SAMPEX, GOES, POES, LANL GEO, Polar, and GPS satellites. A number of new data sets, not previously openly available, include measurements from the HEO-1, HEO-3, CRRES, SCATHA, OV1-19, OV3-3, ICO, and S3-3 spacecraft along with scientist-contributed model and simulation data. Data are served in a number of ways, including a basic FTP site and an OPeNDAP server. As part of this project, we have developed or extended a number of existing software codebases. These codebases have cross-VxO uses, and we are developing them to be usable by other virtual observatories.

3. Outline • Goal of VO effort • Motivation for VO approach • What needs to be done • Keys to success • ViRBO data and status • ViRBO projects

4. Goal of VO effort • “VOs should make ‘standard’ scientific research much more efficient.”  [Roberts et al., 2005] • Rate of science output must keep up with rate of potential science output given amount of available data • The framework which is used must allow for this • Requires improvements in: search interfaces analysis visualization access communication • … all parts of the chain from instrument or model output to end user must continuously improve.

5. More ambitious goal • Ultimately VOs and associated services should enable us to answer “higher-order” queries such as “Show me the data from cases where a large CME and its effects that was observed by SOHO was also observed in situ in the heliosphere, in the Earth's magnetotail, and in responses in the magnetospheres and ionospheres of any planets.”  Roberts et al, 2005 [http://hpde.gsfc.nasa.gov/VO_Framework_7_Jan_05.html]

6. Other goals • … “If the new paradigm is successful, even the PI teams should be tempted to use VOs for looking at their own data.” 

7. Required Steps • Describe the data in a standard format (SPASE) • Create services • Connect services

8. Introduction: Motivation • The modern web at home • The modern web at work now • The modern web at work soon • Brought to you by VO activities

9. The modern web at home • Key points • Finding data from many sources • Finding associated “metadata” • Browsing data • Saving data • Few limitations

13. The modern web at work • Key points • It is easy to create a basic interface to your data base. • Not many well-developed tools exist that allow you to put your data into a more generally useful form or to serve your data in a more standard way. • Such tools need to be easier to implement than creating your own basic interface.

14. Example

15. The modern web at work soon

20. Specialization is needed

21. Keys to success • Everything should be viewed as a service • Importance of the Open Source Development Model • How does it evolve? • Allow for incremental and continuous improvements? • Leveraging community resources?

22. Metadata Creators Standard Query Edit Management Data Creators Ingestion service (with versioning!) Data Base API General Mass store and backup Fast Cache (Content delivery service) Filter service Visualization Pre-computed Static and on demand Interactive and dynamic Needed Services, Tools, and Roles

23. http://groups.google.com/group/vxo-developer/web/discussion-of-mcpherrons-2008-agu-talk?hl=enhttp://groups.google.com/group/vxo-developer/web/discussion-of-mcpherrons-2008-agu-talk?hl=en

24. How it (should?) work Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

25. How it (should?) work Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API and software Logging Service Service Data base

26. How it (should?) work Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

27. How it (should?) work Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

28. How it (should?) work Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

29. How it (should?) work Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

30. How it (should?) work Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

31. How it (should?) work Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

32. How it (should?) work Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

33. Role of the VO PI • Squeeze: Work with their community (“x”) to squeeze out more data (instrument and model) • Teach: Work with their community to improve metadata • Plumb: Connect existing services to meet their communities modern research needs • Request: Make requests to existing services to meet new community needs

34. ViRBO Data • Breaking the VxO paradigm in many ways • Improved high-level tools and services are fine, but first • Increase data accessibility • Increase in available data

36. ViRBO Projects • VxOware • Autoplot • Time Series Server

37. VxOware

38. Motivation (GIT)

39. Proposed Solution Role of VxOware (GIT)

40. Autoplot Has three parts that will be separated into three stand-alone libraries • Aggregator Knows how to ingest data from many data bases into an intermediate form. • Java API • User interface

41. Java API Content Delivery Service Filter Service Data API Software interface Aggregator Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

42. Autoplot • User Interface • Servlet • Applet • WebStart • Aggregator • Knows how to ingest data from many data bases into an intermediate form.

43. Aggregation

44. Time Series Server

45. Content Delivery Service Filter Service Data API Software interface Basic DB Mass Store & Backup Ingest Service & API API Logging Service Service Data base

46. Time Series Server • Leverages OPeNDAP software and protocols. • Typical data types • Time series • Image • 3-D simulation output

47. Future development • Identify redundancies • Take best or combine • Propose new software projects that solve a clearly defined problem and have several VxOs interested in its use • Propose new data products that have a clear demand from a VxO’s community

48. Some missing pieces • Attribution service • Connect SPASE to NASA/ADS • Usage service • Filter service • Ingest service • 3-D plotting service and software • 3-D interpolation service and software • Others?

49. Questions?

50. Example 1