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Leveraging VODKA for Enhanced Data Mining in Astronomy: Tools and Strategies

This paper presents VODKA, an innovative tool aimed at improving data mining efficiency within the framework of the Virtual Observatory (VO). As astronomical data sources rapidly expand, VODKA offers asynchronous updates and users-friendly features, tailored for newcomers and seasoned professionals alike. The tool simplifies complex queries, allowing users to easily access and utilize extensive datasets from various observatories. Future enhancements aim to integrate more capabilities and enhance user experience, making astronomical research more accessible and streamlined.

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Leveraging VODKA for Enhanced Data Mining in Astronomy: Tools and Strategies

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  1. VODKA: as VO-tool can be useful for data mining science R. Smareglia1, O. Laurino2, M. Brescia3 1 INAF - OATs 2 Smithsonian Astr. Obs. 3 INAF - OANa Jenam 2011 – Saint Petersburg

  2. How to face the Observational Data Tsunami • New services and new data continuously pop up, especially when the time domain comes into play (e.g. ELTs: LSST, OWL, ALMA, GAIA). • The Virtual Observatory is getting more and more alive • The interaction with the VO (in order to fetch data) is basically synchronous. • complex queries may take some time to run. Jenam 2011 – Saint Petersburg

  3. How to face the Observational Data Tsunami: • A Dam can be useful • Vodka users can be kept updated asynchronously and automatically Jenam 2011 – Saint Petersburg

  4. Vodka goals • expose the power of the VO but not its complexity; • make users perceive that the Virtual Observatory is alive, and easily understand whether the VO is useful to them or not; • try and pick the best features of the best existing VO data fetching tools; • give the user a quick glimpse of what he can find inside the VO; • save user’s inquiries; • Develop link with data mining specific tools for building datasets. Vodka is on it way to fully achieve all these goals. Jenam 2011 – Saint Petersburg

  5. Vodka Targets • VO newbies: no apps to download in order to start, automatic updates, live examples (no SQL, ADQL or other buzzwords whatsoever); • VO frequent flyers: many datasets (maybe inquiries) to manage, keeping up with new data; • Data miners: multi - cross matching, multi-BoK extraction. Jenam 2011 – Saint Petersburg

  6. Inqueries and Snaphots • An inquiry is defined by its searching criteria. It may carry only resources (Registry Inquiry) or also data (Data Inquiry) Jenam 2011 – Saint Petersburg

  7. Inqueries and Snaphots An inquiry consists of several snapshots; A snapshot consists of several resourceseach resource will have its own file. Jenam 2011 – Saint Petersburg

  8. Snapshot Differences Jenam 2011 – Saint Petersburg

  9. What users can do • Set up inquiries and decide the updating rate; • receive updates directly to their mailbox; • view inquiry details, i.e. the critera and the list of snapshots; • view snapshot details, i.e. the list of resources of a specific snapshot; • view the history of incremental time differences between snapshots, both in terms of resources and data; • download a single votable for the entire snapshot; • download a single votable for each resource in a snapshot, as it appeared when the snapshot was taken. • download incremental files (new data, old data, missing data); • broadcast data to SAMP-enabled applications (e.g. Topcat, Aladin) Jenam 2011 – Saint Petersburg

  10. Future Improvements • Vokda 2.0 is under development (end of August) It must be a scalable application ( working on cluster ) • Data mining specific tools for, e.g., BoK extraction; • Specific clients for most active services (e.g. simbad, ned, ads); • Add more capabilities (e.g. VO-TAP); • Finalize SOAP web service and client API packages (Java, Python); • Integration with VOSpace; Jenam 2011 – Saint Petersburg

  11. Jenam 2011 – Saint Petersburg

  12. Jenam 2011 – Saint Petersburg

  13. DAME MISSION… • A web application (or a Rich Internet Application, RIA) accessiblethrough a simple web browser, hence a web page enhanced by userdynamicalinteraction • The interface design objectivebehindDAME web application is to simulate the intuitive, immediate interaction of a traditional desktop application, butdoesn’t requireanylocalinstallation. • DAME appsprovide in a transparent way all remote computingpower and storage to the user (Cloud/Grid). Jenam 2011 – Saint Petersburg

  14. Conclusions.. • About Data Mining we are at level of “gold Prospector” • With Vodka we have created a tool to improve the efficiency… (we hope). Jenam 2011 – Saint Petersburg

  15. References Where you can find Vodka: • http://ia2.oats.inaf.it/vodka VOkda 2.0 is under test, will be on-line asap ( end of August ) DAME website: • http://dame.dsf.unina.it/ Jenam 2011 – Saint Petersburg

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