Christine Borgman, chair of Info Studies at UCLA, and author of the essential Scholarship in the Digital Age, is giving a talk on The Knowledge Infrastructure of Astronomy. Her new book is Big Data, Little Data, No Data: Scholarship in the Networked World, but you’ll have to wait until January. (And please note that precisely because this is a well-organized talk with clearly marked sections, it comes across as choppy in these notes.)

Her new book draws on 15 yrs of studying various disciplines and 7-8 years focusing on astronomy as a discipline. It’s framed around the change to more data-intensive research across the sciences and humanities plus, the policy push for open access to content and to data. (The team site.)

They’ve been looking at four groups:

• Sloan Digital Sky Survey: moving into archives




• Large Synoptic Survey Telescope: data management, ethnography study of practices




• Center for Embedded Networking Sensing: followed all the way through, the interactions among scientists and others




• Center for Dark Energy Biosphere Investigations (cores from deep ocean): what happens to the cores?

The world thinks that astronomy and genomics have figured out how to do data intensive science, she says. But scientists in these groups know that it’s not that straightforward. Christine’s group is trying to learn from these groups and help them learn from one another

Knowledge Infrastructures are “string and baling wire.” Pieces pulled together. The new layered on top of the old.

The first English scientific journal began almost 350 yrs ago. (Philosophical Transactions of the Royal Academy.) We no longer think of the research object as a journal but as a set of articles, objects, and data. People don’t have a simple answer to what is their data. The raw files? The tables of data? When they’re told to share their data, they’re not sure what data is meant.”Even in astronomy we don’t have a single, crisp idea of what are our data.”

It’s very hard to find and organize all the archives of data. Even establishing a chronology is difficult. E.g., “Yes, that project has that date stamp but it’s really a transfer from a prior project twenty years older than that.” It’s hard to map the pieces.

Seamless Astronomy: ADS All Sky Survey, mapping data onto the sky. Also, they’re trying to integrate various link mappings, e.g., Chandra, NED, Simbad, WorldWide Telescope, Arxiv.org, Visier, Aladin. But mapping these collections doesn’t tell you why they’re being linked, what they have in common, or what are their differences. What kind of science is being accomplished by making those relationships? Christine hopes her project will help explain this, although not everyone will agree with the explanations.

Her group wants to draw some maps and models: “A Christmas Tree of Links!” She shows a variety of maps, possible ways of organizing the field. E.g., one from 5 yrs ago clusters services, repositories, archives and publishers. Another scheme: Publications, Objects, Observations; the connection between pubs (citations) and observations is the most loosely coupled. “The trend we’re seeing is that astronomy is making considerable progress in tying together the observations, publications, and data.” “Within astronomy, you’ve built many more pieces of your infrastructure than any other field we’ve looked at.”

She calls out Chris Erdmann [sitting immediately in front of me] as a leader in trying to get data curation and custodianship taken up by libraries. Others are worrying about bit-rot and other issues.

Astronomy is committed to open access, but the resource commitments are uneven.

Strengths of astronomy:

• collaboration and openness.

• International coordination.

• Long term value of data.

• Agreed standards.

• Shared resources.

Gaps of astronomy:

• Investment in data sstewardship: varies by mission and by type of research. E.g., space-based missions get more investment than the ground-based ones. (An audience member says that that’s because the space research was so expensive that there was more insistence on making the data public and usable. A lively discussion ensues…)




• The access to data varies.




• Curation of tools and technologies




• International coordination. Sould we curate existing data? But you don’t get funding for using existing data. So, invest in getting new data from new instruments??

Christine ends with some provocative questions about openness. What does it mean exactly? What does it get us?

Q&A

Q: As soon as you move out of the Solar System to celestial astronomy, all the standards change.

A: When it takes ten years to build an instrument, it forces you to make early decisions about standards. But when you’re deploying sensors in lakes, you don’t always note that this is #127 that Eric put the tinfoil on top of because it wasn’t working well. Or people use Google Docs and don’t even label the rows and columns because all the readers know what they mean. That makes going back to it is much harder. “Making it useful for yourself is hard enough.” It’s harder still to make it useful for someone in 5 yrs, and harder still to make it useful for an unknown scientist in another country speaking another language and maybe from another discipline.

Q: You have to put a data management plan into every proposal, but you can’t make it a budget item… [There is a lively discussion of which funders reasonably fund this]

Q: Why does Europe fund ground-based data better than the US does?

A: [audience] Because of Riccardo Giacconi.

A: [Christine] We need to better fund the invisible workforce that makes science work. We’re trying to cast a light on this invisible infrastructure.

Categories: big data, libraries, liveblog, science, too big to know dw