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CONTROL ID: 959926
TITLE: Seamless Provenance Representation and Use in Collaborative Science Scenarios
PRESENTATION TYPE: Assigned by Committee (Oral or Poster)
CURRENT SECTION/FOCUS GROUP: Earth and Space Science Informatics (IN)
CURRENT SESSION: IN02. Enabling and Encouraging Transparency in Science Data
AUTHORS (FIRST NAME, LAST NAME): Paolo Missier
1
, Bertram Ludaescher
2
, Shawn Bowers
3
, Ilkay
Altintas
4
, Manish Kumar Anand
4
, Saumen Dey
2
, Anandarup Sarkar
2
, Biva Shrestha
5
, Carole Goble
1
INSTITUTIONS (ALL): 1. School of Computer Science, University of Manchester, Manchester, United
Kingdom.
2. Dept. of Computer Science, University of California, Davis, CA, United States.
3. Dept. of Computer Science, Gonzaga University, Spokane, WA, United States.
4. San Diego Supercomputer Center, University of California, San Diego, CA, United States.
5. Dept. of Computer Science, Appalachian State University, Boone, NC, United States.
Title of Team:
ABSTRACT BODY: The notion of sharing scientific data has only recently begun to gain ground in science,
where data is still considered a private asset. There is growing evidence, however, that the benefits of
scientific collaboration through early data sharing during the course of a science project may outgrow the risk
of losing exclusive ownership of the data. As exemplar success stories are making the headlines[1], principles
of effective information sharing have become the subject of e-science research. In particular, any piece of
published data should be self-describing, to the extent necessary for consumers to determine its suitability for
reuse in their own projects. This is accomplished by associating a body of formally specified and machine-
processable metadata to the data.
When data is produced and reused by independent groups, however, metadata interoperability issues
emerge. This is the case for provenance, a form of metadata that describes the history of a data product, Y.
Provenance is typically expressed as a graph-structured set of dependencies that account for the sequence of
computational or interactive steps that led to Y, often starting from some primary, observational data.
Traversing dependency graphs is one of the mechanisms used to answer questions on data reliability.
In the context of the NSF DataONE project[2], we have been studying issues of provenance interoperability in
scientific collaboration scenarios. Consider a first scientist, Alice, who publishes a data product X along with

its provenance, and a second scientist who further transforms X into a new product Y, also along with its
provenance. A third scientist, who is interested in Y, expects to be able to trace Y's history up to the inputs
used by Alice. This is only possible, however, if provenance accumulates into a single, uniform graph that can
be seamlessly traversed. This becomes problematic when provenance is captured using different tools and
computational models (i.e. workflow systems), as well as when data is published and reused using
mechanisms that are not provenance-aware.
In this presentation we discuss requirements for ensuring provenance-aware data publishing and reuse, and
describe the design and implementation of a prototype toolkit that involves two specific, and broadly used,
workflow models, Kepler [3] and Taverna [4]. The implementation is expected to be adopted as part of
DataONE's investigators' toolkit, in support of its mission of large-scale data preservation.
Refs.
[1]Sharing of Data Leads to Progress on Alzheimer’s, G. Kolata, NYT, 8/12/2010
[2]http://www.dataone.org
[3]Ludaescher B., Altintas I. et al. Scientific Workflow Management and the Kepler System. Special Issue:
Workflow in Grid Systems. Concurrency and Computation: Practice & Experience 18(10): 1039-1065, 2006
[4]D. Hull, K. Wolstencroft, R. Stevens, C. Goble, M. R. Pocock, P. Li, T. Oinn. Taverna: a tool for building and
running workflows of services. Nucl. Acids Res. 34: W729-W732, 2006
INDEX TERMS: [1948] INFORMATICS / Metadata: Provenance, [1998] INFORMATICS / Workflow.
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Sponsor
SPONSOR NAME: Bruce Wilson
SPONSOR EMAIL ADDRESS: wilsonbe@ornl.gov
SPONSOR MEMBER ID: 10549509
Additional Details
Previously Presented Material:
Scheduling Request:
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