ARCSS Program | Message from the ARCSS Committee
- ARCSS Note #1 (2 August 2004): Community Input on Synthesis
- ARCSS Note #2 (31 January 2005): Development of a New ARCSS Community Structure
- ARCSS Note #3 (4 April 2005): ARCSS eTown Meeting Announcement
- ARCSS Note #4 (15 April 2005): Update on ARCSS Program Activities
- ARCSS Note #5 (1 August 2005): Call for Communities of Practice
- ARCSS Note #6 (20 September 2005): ARCSS Synthesis eTown Meeting
- ARCSS Note #7 (16 November 2006): ARCSS Committee Meeting Notes
- ARCSS Note #8 (20 November 2006): ARCSS Committee Recommendations on Data Management
- ARCSS Note #9 (7 May 2007): Arctic System Synthesis Workshop Summary
- ARCSS Note #10 (29 June 2007): ARCSS Committee Meeting Notes
- ARCSS Note #11 (20 November 2007): ARCSS Committee Meeting Notes
- ARCSS Note #12 (7 August 2008): eTown Meeting Announcement: Changing Seasonality
- ARCSS Note #13 (3 June 2010) Recommendations for Successful Arctic System Science
Message from the ARCSS Committee
Dear Colleague:
The purpose of this letter is to summarize ARCSS Committee (AC) discussions regarding the emerging needs of ARCSS data management and recommendations for approaches that will advance the ARCSS research agenda and increase its utility to a variety of stakeholders. Below we summarize the AC recommendations for moving towards a redesigned ARCSS data management structure. The points below are organized by three fundamental issues: (I) the scientific rationale for a new approach to ARCSS data management; (II) identified priorities for data management that advances system-scale science; and (III) ways in which the research community could plan strategically for the future of ARCSS Program data management.
I. New Directions in Arctic Science Demand
New Approaches to Data Management
The NSF ARCSS Program is moving to increasingly
interdisciplinary, interscale, and integrative
approaches to understanding the arctic system.
Synthesis has become a central component of the
program, integrating and modeling large, complex, and
disparate data sets to answer questions about how the
Arctic functions as an integrated system. Simply
managing and making accessible the data sets
collected in the past has been a challenge. Dealing
with the data sets and data needs of the future
raises even greater challenges, but also greater
opportunities for synthetic science.
ARCSS must develop mechanisms to identify, ingest, visualize, and process what could ultimately be terabytes of data from sources as diverse as satellite remote sensing imagery to local hunter’s game tags. ARCSS data management must now support new modes of inquiry, such as intercomparison studies, data integration and assimilation, arctic and Earth system modeling, and cross-disciplinary data merging.
Several developments are now acting in concert to place this issue squarely before us: a well-documented record of rapid and systematic arctic environmental change, an increasingly vocal national and international policy debate surrounding such change, breakthroughs in complex modeling capabilities, the current wealth of new and legacy data sets requiring analysis, and the major influx of information anticipated from initiatives such as the Study of Environmental Arctic Change (SEARCH), the Arctic Observing Network (AON), and the International Polar Year (IPY). It is clear that the time to develop new approaches to managing data is now—the need is urgent and immediate.
II. Priorities for Data Management that
Advances System-Scale Science
To meet these emerging realities, the ARCSS research
community has identified several priorities for data
management to support the best science and
decision-making, including:
- An efficient process for researchers to submit data and metadata to a long-term archive;
- Minimal delay in the online availability of submitted data and metadata via a long-term archive;
- A coherent and comprehensive venue for data discovery, whereby data can be searched through a number of user-friendly methods;
- Standardized, open, and interoperable metadata and data formats;
- Data management structure, process, and tools that enable data organization, retrieval, and analysis across multiple sources and formats to facilitate consolidation of otherwise disparate disciplinary data sets; and
- An organizational structure that fosters data and allied data analysis and modeling activities that are closely connected to synthetic science questions.
III. Ways to Move Forward: Redefining ARCSS
Data Management
The ARCSS Committee has recommended that the NSF
ARCSS Program undertake community-based strategic
planning activities to formulate a new data system
design. Activities led by the ARCSS Committee in the
past year include the re-constitution of the Data
Working Group to the ad hoc Data and
Modeling Working Group and an online community data
meeting (see: http://www.arcus.org/ARCSS/ETM/march_06/data/).
Future activities planned to guide ARCSS data
management include:
Open Town Meeting at AGU on Arctic Data
Needs and Priorities
At the AGU Fall Meeting held in San Francisco from
11–15 December 2006, the ARCSS Committee is
sponsoring an open meeting to discuss challenges
faced in arctic data management, approaches to manage
those challenges, and recommendations for
infrastructure improvements. This open meeting is
tentatively scheduled for Thursday, 14 December from
6:30 p.m. – 8:00 p.m. at the San Francisco Marriott
Hotel. More information will be announced via the
ARCSS Listserve shortly.
Data/Modeling Workshop in January
2007
A small workshop is planned for January 2007 to
identify innovative approaches for uniting data
management and assimilation, recent developments in
technology, and modeling that will advance synthesis
studies of the arctic system. Invited participants
will include diverse representation from data
providers and users as well as information technology
experts and knowledge brokers. The broader community
will be invited to participate in several workshop
sessions through teleconferencing and/or online
meeting tools.
The workshop will consider a set of key discussion questions:
- What are the data and modeling needs to advance synthesis-focused arctic system science?
- What's currently working and what is not in terms of applying data and modeling for analysis to advance science? What are the existing impediments limiting the assimilation of disparate data sources needed to advance arctic synthesis studies, and what are the keys to success?
- What are the practical steps forward as far as mechanisms, approaches, tools and procedures, organization, standards, and related issues?
The workshop will result in a community-reviewed report summarizing key issues, common challenges, and general lessons that emerged during the workshop; the workshop report will include recommendations for NSF investments in this arena.
More information on this workshop, and how the broad community can participate, will be announced via the ARCSS Listserve in the coming weeks.
Longer-Term
Activities
In addition to the near-term activities above, the
ARCSS Committee has discussed holding a larger
workshop at a time that would be conducive to broader
planning and implementation of an ARCSS Data
Management design. This larger workshop would partner
with other programs in the environmental sciences
(Study of Environmental Arctic Change [SEARCH], the
Arctic Observing Network [AON], and the National
Ecological Observatory Network [NEON], for example)
that face similar challenges, with increased
participation from private industry to consider
creative approaches to implementing arctic data
identification, access, and use.
The ARCSS Committee intends to continue the dialogue with the research community on this important issue through various discussion venues. We also hope that you will feel free to contact any of us with concerns or recommendations on how the ARCSS Program may improve data management to advance arctic science.
Joshua
Schimel, University of California Santa Barbara,
Chair
Jennifer
Francis, Rutgers University
Marika
Holland, National Center for Atmospheric
Research
Joseph
McFadden, University of Minnesota
Maribeth Murray,
University of Alaska Fairbanks
Craig
Nicolson, University of Massachusetts
Jonathan
Overpeck (Past ARCSS Committee Chair), University
of Arizona
Don
Perovich, Cold Regions Research and Engineering
Laboratory
Mark
Serreze, Cooperative Institute for Research in
Environmental Sciences
Michael
Steele, University of Washington
Matthew
Sturm, Cold Regions Research and Engineering
Laboratory
Charles
Vörösmarty, University of New Hampshire