Advancing Strategic Science A Spatial Data Infrastructure Roadmap for the U.S. Geological Survey (2012) / Chapter Skim
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Appendix D: Questionnaire Responses
Appendix D: Questionnaire Responses
Pages 100-116
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From page 100... ...
The responses are grouped below by issue. Lessons Learned Questionnaire Responses Issue Lesson Standardization Full acceptance of the organization of the need for rigid standardization of its data and information products to agreed international standards Organizational commitment to internationally agreed metadata standards [Successful organizations]
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From page 101... ...
Data Scientists must make available data that underpin knowledge products Federal data are created to some minimum achievable standard Census using local roads data Landsat 7...we've done the best we could. We need the continuity mission now.
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From page 102... ...
But in order to address this domain successfully, we rely on a wide range of non-biological data inputs, such as imagery (of varying types and resolutions) , digital elevation, synthesized climate data (past, current, future)
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From page 103... ...
Although much of our work is supported by geospatial data, much of the data supporting that work is never published because of this. [What has worked?
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From page 104... ...
New map services are providing data access in new ways. These include NWIS web services, NWIS Mapper, real-time earthquake maps, and StreamStats.
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From page 105... ...
High expectations - Increasingly, scientists as well as decision makers, business and the public not only want, but expect all data will be instantly available online at no cost, and fully interoperable. Such systems are standard on a number of popular network television crime shows where all data of any kind sought are brought to the desk top instantly and fully integrated with no need to convert, process, or interpret them.
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From page 106... ...
create government centers of excellence for highest priority data sets and require cross agency funding mechanisms for collection and maintenance, 3) promote standards-based, optimized, geospatial data service hosting for federal agencies to increase capacity and uptake.
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From page 107... ...
and USGS is the result of too little attention to the fundamentals of data standards and data applications across the spectrum of spatial data services in USGS. There is a partitioning of data collection among themes and funding of these themes, as well as partitioning of support services for Geospatial Data collections and the research scientists requiring GIS support to use our enterprise license.
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From page 108... ...
Not much has worked well; no support; standards not well defined; very little guidance; very little incentive; software tools to create consistent metadata lacking; datasets are almost considered a burden, especially large ones; search mechanisms of data in NSDIs lacking. [Challenges]
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From page 109... ...
The USGS Geospatial programs are primarily outward looking, and driven what they feel is public demand. This does very little to support USGS science.
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From page 110... ...
The major challenge is financial: support for SDI requires additional personnel, with changes technology and cultural behaviors. Many academic and non-governmental organizations (as well as a number of governmental entities below the federal level)
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From page 111... ...
States who are not coordinated and have a state level geospatial coordinating body. There must be an entity who can speak with authority on funding issues for geospatial data at the state level, otherwise fed state partnerships are very difficult to put together.
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From page 112... ...
The FGDC, USGS, and other bodies need to be better supported, more open in membership (i.e., to science NGOs) , and empowered to support more robust dialogue, clarify shared goals, and facilitate sharing of financial resources.
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From page 113... ...
The data network then looks more like the Web each provider is responsible for what they want to share. There will be a continuing need for archive and orphan data repositories for data that do not have permanent homes, and for data scavenged from historical and analog sources.
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From page 114... ...
Build better metadata tools. Make management accountable to publish geospatial data from all projects Make all projects identify spatial data results, plan for, and publish them before project is considered complete.
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From page 115... ...
e.g., downscaled climate data and models. Promotion and development of fast, reliable, web services that provide discovery and access to geospatial data.
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