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Requirements from astronomy in the Virtual Observatory era Bob Mann Institute for Astronomy & NeSC University of Edinburgh.

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Presentation on theme: "Requirements from astronomy in the Virtual Observatory era Bob Mann Institute for Astronomy & NeSC University of Edinburgh."— Presentation transcript:

1 Requirements from astronomy in the Virtual Observatory era Bob Mann Institute for Astronomy & NeSC University of Edinburgh

2 Outline of talk What is the Virtual Observatory (VObs)? What is the Virtual Observatory (VObs)? –How is it changing astronomy? Who in astronomy needs e-Science skills? Who in astronomy needs e-Science skills? –Data centre staff –VObs middleware developers –Data analysis tool developers –Research astronomers Summary Summary –What skills are needed? –How can these requirements be met?

3 What is the Virtual Observatory? A goal : A goal : –An interoperable federation of the world’s astronomical data sources A standards agency/coordination body: A standards agency/coordination body: –International Virtual Observatory Alliance –Its members are VObs projects in Australia, Canada, China, France, Germany, Hungary, India, Italy, Japan, Korea, Russia, Spain, UK, USA, and the EU.

4 Why is the VObs needed? We observe across the whole electromagnetic spectrum We observe across the whole electromagnetic spectrum Different views of a local spiral galaxy Different views of a local spiral galaxy –Need all of them to understand its physics fully –The databases holding them are located all over the world IRAS 25  2MASS 2  DSS Optical IRAS 100  NVSS 20cm GB 6cm ROSAT ~keV WENSS 92cm

5 Schematic of the VObs DB 1 DB 5 DB 4 DB 3 DB 2 Registry Compute Resource 1 Compute Resource 2 App 5 App 3 App 2 App 1 App 4 Portal Workflow User

6 What services will the Virtual Observatory need? Data discovery Data discovery –Looking up metadata in a registry Data access Data access –With/without authentication & authorization Data integration Data integration –Cross-matching entries in databases Data manipulation Data manipulation –Data mining, data analysis, etc

7 Data centre staff DB 1 DB 5 DB 4 DB 3 DB 2 Registry Compute Resource 1 App 1 Data Curation: Provenance, DBMS design and operations Data Access Security, Registry Metadata, Web Services Data Manipulation User-uploaded code, job scheduling

8 VObs middleware developers VObs middleware developers DB 1 DB 2 Registry Compute Resource 2 App 3 Portal Workflow Web/Grid services for the discovery, transport and integration of data Workflow & service composition Metadata and service registration Job management Security

9 Data analysis tool developers DB 1 Registry Compute Resource 2 App 3 Workflow Data Access: OGSA-DAI/data access web services Service Registration Integration into workflows Job submission

10 Research astronomers DB 1 DB 2 Registry Compute Resource 2 App 5 App 4 Portal Workflow User Initially: Use of portal Soon: Script and tool development using APIs, local job control, wrapping apps as web services

11 Summary of skills needed Web/Grid services for data discovery, access, integration and manipulation Web/Grid services for data discovery, access, integration and manipulation Metadata for data & service registration Metadata for data & service registration Data curation – provenance, preservation Data curation – provenance, preservation Workflow creation and execution Workflow creation and execution Job control – local and remote Job control – local and remote Security Security

12 How can these needs be met? (1) Learning through experience Learning through experience –Difficult: fast moving field; where to start? Danger of learning the wrong technologies Danger of learning the wrong technologies –Inefficient: undirected training can be slow Hiring people with appropriate skills Hiring people with appropriate skills –Not many people with e-Science skills yet …and expensive to employ on research grants …and expensive to employ on research grants –Really need astronomers for some jobs Danger of losing scientific direction to projects Danger of losing scientific direction to projects

13 How can these needs be met? (2) Existing staff: training courses Existing staff: training courses –Can be expensive and time-consuming –Need to budget time and money for them Funders need to understand their necessity Funders need to understand their necessity Future staff: education Future staff: education –Astronomers: MSc-level courses – either as MSc or as part of PhD training –IT specialists: inclusion of e-science content in CS degree programmes


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