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Astroinformatics: data-oriented astronomy research and education

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Abstract

The growth of data volumes in science is reaching epidemic proportions. Consequently, the status of data-oriented science as a research methodology needs to be elevated to that of the more established scientific approaches of experimentation, theoretical modeling, and simulation. Data-oriented scientific discovery is sometimes referred to as the new science of X-Informatics, where X refers to any science (e.g., Bio-, Geo-, Astro-) and informatics refers to the discipline of organizing, describing, accessing, integrating, mining, and analyzing diverse data resources for scientific discovery. Many scientific disciplines are developing formal sub-disciplines that are information-rich and data-based, to such an extent that these are now stand-alone research and academic programs recognized on their own merits. These disciplines include bioinformatics and geoinformatics, and will soon include astroinformatics. We introduce Astroinformatics, the new data-oriented approach to 21st century astronomy research and education. In astronomy, petascale sky surveys will soon challenge our traditional research approaches and will radically transform how we train the next generation of astronomers, whose experiences with data are now increasingly more virtual (through online databases) than physical (through trips to mountaintop observatories). We describe Astroinformatics as a rigorous approach to these challenges. We also describe initiatives in science education (not only in astronomy) through which students are trained to access large distributed data repositories, to conduct meaningful scientific inquiries into the data, to mine and analyze the data, and to make data-driven scientific discoveries. These are essential skills for all 21st century scientists, particularly in astronomy as major new multi-wavelength sky surveys (that produce petascale databases and image archives) and grand-scale simulations (that generate enormous outputs for model universes, such as the Millennium Simulation) become core research components for a significant fraction of astronomical researchers.

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Notes

  1. http://serc.carleton.edu/usingdata/ and http://serc.carleton.edu/files/usingdata/UsingData.pdf

  2. http://www.vanderbilt.edu/gradschool/bridge

  3. http://grants.nih.gov/grants/guide/pa-files/PA-06-094.html

  4. http://esto.nasa.gov/info_technologies_aist.html and http://reason-projects.gsfc.nasa.gov/

  5. http://research.microsoft.com/en-us/um/cambridge/projects/towards2020science/

  6. http://universe.ucdavis.edu/docs/LSST_petascale_challenge.pdf

  7. http://www.nsf.gov/events/event_summ.jsp?cntn_id=116644&org=MPS

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Acknowledgments

We thank the National Science Foundation (NSF) for partial support of this work by the Division of Undergraduate Education (DUE) Course and Curriculum, and Laboratory Improvement (CCLI) program, through award #0737091. The author thanks numerous colleagues for their significant and invaluable contributions to the ideas expressed in this paper: Jogesh Babu, Douglas Burke, Andrew Connolly, Timothy Eastman, Eric Feigelson, Matthew Graham, Alexander Gray, Norman Gray, Suzanne Jacoby, Thomas Loredo, Ashish Mahabal, Robert Mann, Bruce McCollum, Misha Pesenson, M. Jordan Raddick, Alex Szalay, Tony Tyson, and John Wallin. Finally, the author wishes to express deep gratitude and appreciation to Keivan Stassun for his thorough and thoughtful review of an earlier version of this paper, and for his numerous helpful comments and suggestions, which considerably improved the final product.

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Authors and Affiliations

  1. Department of Computational and Data Sciences, George Mason University, Fairfax, VA, USA

    Kirk D. Borne

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Correspondence to Kirk D. Borne.

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Communicated by Thomas Narock

Appendix A National Study Groups Face the Data Flood

Appendix A National Study Groups Face the Data Flood

Several national study groups have issued reports on the urgency of establishing scientific and educational programs to face the data flood challenges, including:

  1. 1.

    NAS (National Academies of Science) report: Bits of Power: Issues in Global Access to Scientific Data, (1997) downloaded from http://www.nap.edu/catalog.php?record_id=5504

  2. 2.

    NSF report: Knowledge Lost in Information: Research Directions for Digital Libraries, (2003) downloaded from http://www.sis.pitt.edu/~dlwkshop/report.pdf

  3. 3.

    NSF report: Cyberinfrastructure for Environmental Research and Education, (2003) downloaded from http://www.ncar.ucar.edu/cyber/cyberreport.pdf

  4. 4.

    NSF Atkins Report: Revolutionizing Science & Engineering Through Cyberinfrastructure: Report of the NSF Blue-Ribbon Advisory Panel on Cyberinfrastructure, (2003) downloaded from http://www.nsf.gov/od/oci/reports/atkins.pdf

  5. 5.

    NSB (National Science Board) report: Long-lived Digital Data Collections: Enabling Research and Education in the 21st Century, (2005) downloaded from http://www.nsf.gov/nsb/documents/2005/LLDDC_report.pdf

  6. 6.

    NSF report with the Computing Research Association: Cyberinfrastructure for Education and Learning for the Future: A Vision and Research Agenda, (2005) downloaded from http://www.cra.org/reports/cyberinfrastructure.pdf

  7. 7.

    NSF report: The Role of Academic Libraries in the Digital Data Universe, (2006) downloaded from http://www.arl.org/bm~doc/digdatarpt.pdf

  8. 8.

    National Research Council, National Academies Press report: Learning to Think Spatially, (2006) downloaded from http://www.nap.edu/catalog.php?record_id=11019

  9. 9.

    NSF report: Cyberinfrastructure Vision for 21st Century Discovery, (2007) downloaded from http://www.nsf.gov/od/oci/ci_v5.pdf

  10. 10.

    JISC/NSF Workshop report on Data-Driven Science & Repositories (2007) downloaded from http://www.sis.pitt.edu/~repwkshop/NSF-JISC-report.pdf

  11. 11.

    DOE (Department of Energy) report: Visualization and Knowledge Discovery: Report from the DOE/ASCR Workshop on Visual Analysis and Data Exploration at Extreme Scale, (2007) downloaded from http://www.sc.doe.gov/ascr/ProgramDocuments/Docs/DOE-Visualization-Report-2007.pdf

  12. 12.

    DOE report: Mathematics for Analysis of Petascale Data Workshop Report, (2008) downloaded from http://www.sc.doe.gov/ascr/ProgramDocuments/Docs/PetascaleDataWorkshopReport.pdf

  13. 13.

    NSTC Interagency Working Group on Digital Data report: Harnessing the Power of Digital Data for Science and Society, (2009) downloaded from http://www.nitrd.gov/about/Harnessing_Power_Web.pdf

  14. 14.

    National Academies report: Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age, (2009) downloaded from http://www.nap.edu/catalog.php?record_id=12615

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Borne, K.D. Astroinformatics: data-oriented astronomy research and education. Earth Sci Inform 3, 5–17 (2010). https://doi.org/10.1007/s12145-010-0055-2

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