Difference between revisions of "Response to RFI for US Gov GeoSpatial"

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# Mike Davis (interspersed as workload permits)
 
# Mike Davis (interspersed as workload permits)
 
# Bob Basques (as workload permits)
 
# Bob Basques (as workload permits)
#  
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# Kevin Yam
  
 
==== Notes to use ====
 
==== Notes to use ====
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Place any additional notes about our information here...
 
Place any additional notes about our information here...
  
Note that we don't have to respond to every question.  The RFI says 'If you choose not to respond to a question, indicate “no response” and identify the rationale.'
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Note that we don't have to respond to every question.  The RFI says 'If you choose not to respond to a question, indicate “no response” and identify the rationale.' One can bypass a whole section (e.g. the scenarios, to which no-one has made a response here); 
 +
"Please respond to the appropriate Sections based on your experience"
 +
 
 +
The RFI urges this consideration of its goals, in responses:
 +
 
 +
''Respondents must factor key public values as defined by the NSDI into each response whenever applicable. Key public values include:''
 +
 
 +
* ''Privacy and security of citizens’ personal data and accuracy of statistical information on people, both in raw form and in derived information products''
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* ''Access for all citizens to spatial data, information, and interpretive products, in accordance with OMB Circular A-130''
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* ''Protection of proprietary interests related to licensed information and data''
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* ''Interoperability of Federal information systems to enable the drawing of resources from multiple Federal agencies and their partners''
  
 
== RFI Questionnaire Section 1: Respondent Information ==
 
== RFI Questionnaire Section 1: Respondent Information ==
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''Contact information (provide a point of contact, phone number and e-mail address):''
 
''Contact information (provide a point of contact, phone number and e-mail address):''
 +
<p>Primary contact:
 +
Chris Holmes, 212-219-6062, cholmes@openplans.org</p>
 +
 +
<p>Secondary contact:
 +
Ned Horning, 212-313-7947, horning@amnh.org</p>
  
 
== ''Lifecycle Activities'' ==
 
== ''Lifecycle Activities'' ==
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''2.2.1 In which data themes of national importance is there opportunity for increased effectiveness, efficiency, and cost savings potential across the Federal Government, and what is the recommended transition approach? OMB Circular A-16 framework data themes and other data themes of national significance are (1) geodetic control, (2) orthoimagery, (3) elevation and bathymetry, (4) transportation, (5) hydrography, (6) cadastral, and (7) governmental units.''
 
''2.2.1 In which data themes of national importance is there opportunity for increased effectiveness, efficiency, and cost savings potential across the Federal Government, and what is the recommended transition approach? OMB Circular A-16 framework data themes and other data themes of national significance are (1) geodetic control, (2) orthoimagery, (3) elevation and bathymetry, (4) transportation, (5) hydrography, (6) cadastral, and (7) governmental units.''
  
''2.2.2 What are the critical change management issues and best practices for successful transition to and full implementation of common solutions?'' A fundamental change management issue is to promote and adapt open standards for the collection (protocols), storage (file formats, media, and metadata), access, and processing of geographic data. A recently released report by the Digital Connections Council of the Committee for Economic Development, “Open Standards, Open Source, and Open Innovation: Harnessing the Benefits of Openness” (http://www.ced.org/projects/ecom.shtml#open) highlights the benefits from adapting open standards. This report found that openness can be used effectively to build effective standards that in turn can be used to enhance interoperability.  
+
'''no response? rationale?'''
 +
 
 +
''2.2.2 What are the critical change management issues and best practices for successful transition to and full implementation of common solutions?''  
 +
 
 +
Promotion and adoption of open standards for the collection, storage, access, and processing of geographic data is fundamental to the development of best-practise common solutions. Common implementation of standard protocols (for exchange) and formats (for storage and distribution) of geographic data are can greatly simplify  future transitions.
 +
 
 +
A recently released report by the Digital Connections Council of the Committee for Economic Development, “Open Standards, Open Source, and Open Innovation: Harnessing the Benefits of Openness” (http://www.ced.org/projects/ecom.shtml#open) highlights the interoperability benefits gained from adopting open standards.  
 +
 
 +
However, the presence of standards alone is not sufficient. The Open GeoSpatial Consortium (OGC) has made great strides in developing a set of standards, which precisely define a solution for interoperability of geographic data and systems.  Yet uptake has been slow, as few outside of the standards writers see compelling reason to implement common solutions.  Additionally, there are often large investments needed to adopt a standard.  Investments may take the form of an upgrade to current software, developing or acquiring new software, or investing significant time in getting an open source solution running.
 +
 
 +
In transition to a common solution, these concerns can be addressed by:
 +
 
 +
- providing proof of best practise in ease of implementation of open standards for geographic data
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- providing proof of value and return on investment in doing so
 +
 
 +
In order to encourage uptake, data providers need some compelling reason to transition a common solution.  While the OGC community passed by promotion of their standards to write newer, more niche ones geared towards higher overhead uses, Google Earth came along with a compelling, user friendly environment with lots of available data.  Far more organizations are making their data available as KML, the Google Earth standard, than have set up a Web Map Service interface.  With WMS one tends to only replicate functionality that was already available, albeit in a more open way. 
 +
 
 +
A compelling example of the power of interoperability is needed to render a new investment attractive to stakeholders; an open standards based solution cannot be merely a requirement demanded from above. The essence this is "bottom up" rather than "top down" approach is exemplified by the World Wide Web. Participation in the  was not a question of being obliged to implement HTML and HTTP standards to share one's information; not doing so, one would be "missing the boat". If the Geospatial Web is perceived as something that is working now, and can be as compelling as the World Wide Web, it is naturally to everyone's advantage to implement common solutions.
 +
 
 +
The impact of potentially large infrastructure investment needed to adopt a standard, can be greatly minimized by available user friendly open source implementations of the open standards. This allows organizations to 'try out' new open standards without having to heavily invest in new infrastructure, the advantages of which are unknowable.
 +
 
 +
This is in no way exclusive of proprietary implementations of open standards, and most proprietary vendors that we've talked to welcome the availability of open source implementations.
 +
 
 +
After an initial evaluation phase of the standard itself, using the open source software, most organizations will complete a full evaluation of available solutions, and many times proprietary solutions will fit them best.  Open standards and common solutions also benefit from many implementations; the more data that is available, the more compelling an environment.  For vendors of proprietary software, 'a rising tide raises all boats', even if many people choose open source solutions. To go back to the World Wide Web analogy; though the open source Apache Web Server has a majority of the web server market, the proprietary vendors all have much greater sales as a result of the fact that more organisations are offering their online via standard protocols and formats; an outcome which Apache enabled by greatly lowering the barrier to entry. 
 +
 
 +
Additionally, open source solutions will easily operate alongside legacy systems, so that an entirely new investment is not needed to transition over a whole infrastructure.  Open source can run side by side with proprietary solutions, with open source implementing the new open standards. Stakeholders can maintain their regular workflows and transition to a more common solution in time.  The open nature of the code means that even if a certain legacy system is not already available to be integrated, it is relatively easy to modify the open code to work with the legacy code.  This mitigates the risk of transition to common solutions by allowing the transition to be iterative, incrementally adding small pieces along the way, instead of requiring a massive upheaval.
  
Available open source solutions to allow organizations to 'try out' new open standards with lower barriers to entry. 
 
  
Ability to modify the source code allows organizations to alter the common solutions to be compatible with their legacy systems, so that transition can proceed at a more natural pace, running new and old systems side by side. 
+
''2.2.3 What cultural impediments and training issues are paramount at which stages of the transition? What are the solutions to them?''
  
''2.2.3 What cultural impediments and training issues are paramount at which stages of the transition? What are the solutions to them?
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<p>Although the United States is a global leader in providing public access to data,  the process of collecting and maintaining, storing and processing these data are open. Historically, this has been the case because vendors providing these services use proprietary methods with the intent of gaining a competitive edge over their competition. This approach is rooted in traditional intellectual property protection ideals and can result in incompatibility between data sets, and high costs to the government. This mindset is a significant cultural impediment to achieving common solutions for working with geospatial data and can be overcome by developing open data and software standards and promoting the benefits of this approach to the business community and government organizations.</p>
  
 
Cultural Issues
 
Cultural Issues
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Training Issues
 
Training Issues
 
<ul>
 
<ul>
<li>Cost of use, training materials derived from open source packages vs commercial packages.</li>
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<li>Cost of use, training materials derived from open source packages vs proprietary packages.</li>
 
<li>Simple is better, if something is easier to use, it's more likely to be used.</li>
 
<li>Simple is better, if something is easier to use, it's more likely to be used.</li>
<li>Commercial vs OpenSource</li>
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<li>Proprietary vs OpenSource</li>
 
</ul>
 
</ul>
  
 
''2.2.4 From your experience, please describe the cost/benefit of coordinating the use of geographic information or optimizing NSDI components and related spatial data activities across all sectors and levels of government.''
 
''2.2.4 From your experience, please describe the cost/benefit of coordinating the use of geographic information or optimizing NSDI components and related spatial data activities across all sectors and levels of government.''
 +
 +
Many current activities rely on a string of participants to manage a Geographic Information System.  A system needs to allow individual data owners to update and maintain their respective datasets with the least amount of percieved extra work.  If the process is precieved by the data owners to be additional effort on their part, it's much less likely to take hold as a standard.  The process needs to be as painless as possible for the Data Steward in order for a system to be self sustaining.
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Publication by Data Owners requires a few basic needs be met, such as:
 +
<ul>
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<li>Move publication and maintenance of data as close as possible to the data owners/creators.</li>
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<li>Owners/creators are also responsible for appropriate metadata for their respective datasets.  This aids in data discovery mechanisms for the end users.</li>
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<li>Responsibly for upkeep and timeliness of data should be traceable to the owners/creators by average users of the data.</li>
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<li>User Feedback systems need to be in place for relaying of errors and/or omissions back to the data owners.</li>
 +
</ul>
  
 
''2.2.5 What are the top three critical factors for successfully coordinating the use of geographic information or optimizing related spatial data activities?''
 
''2.2.5 What are the top three critical factors for successfully coordinating the use of geographic information or optimizing related spatial data activities?''
 
<ul>
 
<ul>
<li>Data Consistency</li>
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<li>Data interoperability – It is important that data can be used in all anticipated situations. This means it must be possible to combine it with other data and it must be usable within a broad range of available systems.</li>  
<li>Ease of Access</li>
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<li>Accessibility – This includes physical access to data layers and the ability to work with those data in available usable systems (for example a GIS with trained personnel.)</li>
<li>Data Currency</li>
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<li>Data Currency – Data currency must be within the requirements of the intended application.</li>  
 
</ul>
 
</ul>
  
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<li>Data Accuracy</li>
 
<li>Data Accuracy</li>
 
<li>Data Availability</li>
 
<li>Data Availability</li>
<li>Data Compatability</li>
+
<li>Data Compatibility</li>
 
</ul>
 
</ul>
<p>The three biggest risks when building business practices based on shared geospatial information reflect the critical factors mentioned in 2.2.5.  For shared systems to work, each proponent must be willing and able to meet a certain standard level of service that ensures the reliability and consistancy of the data provided.  These data must be available in a format that is accessable to the end user regardless of software package or vendor.</p>
+
<p>The three biggest risks when building business practices based on shared geospatial information reflect the critical factors mentioned in 2.2.5.  For shared systems to work, each proponent must be willing and able to meet a certain standard level of service that ensures the reliability and consistancy of the data provided.  These data must be available in a format that is accessible to the end user regardless of software package or vendor.</p>
  
 
''2.2.7 What are the key performance indicators related to coordinating the use of geographic information or optimizing related spatial data activities? What metrics can be obtained to measure performance and how?''
 
''2.2.7 What are the key performance indicators related to coordinating the use of geographic information or optimizing related spatial data activities? What metrics can be obtained to measure performance and how?''
<p>While data accuracy can be a difficult metric to measure shared spatial data by, it is probably the most important factor when relying on such data for business processes.
 
  
Easier to measure is the level of consistancy maintained by shared spatial data.  Data that follows an established standard (ie. SDSFIE) can be graded based on how well it follows and implements said standard.
+
While data accuracy can be a difficult metric to measure shared spatial data by, it is probably the most important factor when relying on such data for business processes.
  
Another important metric for shared spatial data is the length of time required for changes made by the data steward to be reflected in the shared dataset.  Minimizing this refresh time is critical if the shared datasets are to be considered an authoritative source of information.</p>
+
Easier to measure is the level of consistancy maintained by shared spatial data.  Data that follows an established standard (ie. SDSFIE) [https://tsc.wes.army.mil/ https://tsc.wes.army.mil/] can be graded based on how well it follows and implements said standard.
 +
 
 +
Another important metric for coordinating use geographic data is the length of time required for changes made by the data steward to be reflected in the shared dataset.  Minimizing this refresh time is critical if the shared datasets are to be considered an authoritative source of information.
  
 
''2.2.8 How do you retain the advantages of competition while reaping the benefits of geospatial coordination and optimization?''
 
''2.2.8 How do you retain the advantages of competition while reaping the benefits of geospatial coordination and optimization?''
<p>Common standards, and clearly defined metrics of success create an environment in which entities can compete on a level playing field.</p>
+
 
 +
Advantages of competition are perceived to be improved innovation (producing a better product) and reduced cost to the consumer. By developing and using open standards innovation is improved because of the size and diversity of the community developing the standards. Cost is also reduced because once the standards and clearly defined metrics of success are in place, the cost of entry for product development is reduced. To strengthen competition it helps if companies can compete on a level playing field that is promoted through the use of open standards.</p>
  
 
''2.2.9 How do you ensure and manage ongoing innovation in geospatial coordination and optimization?''
 
''2.2.9 How do you ensure and manage ongoing innovation in geospatial coordination and optimization?''
 +
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The most effective way to ensure continued innovation is to promote and adopt open standards for the creation/collection, storage, access, and processing of geospatial data. This includes contributing to the development of open source geospatial software that supports and promotes common standards.
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It is in the data users’ and producers’ interest to have interoperable solutions and the most effective way to accomplish this is to include them in the process of developing standards and software. The benefits of using open methods are becoming well publicized (for example see: http://www.amso.army.mil/cc-tteam/PMG_04_MOSA.pdf). [''quote?'']
 +
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To further benefit from current open approaches it is necessary to fund research and development for improved interoperability and access. Research should also be conducted on innovative open approaches for creating and maintaining geospatial data layers in an open environment. The potential of openness in the geospatial sector is great but funded research is needed to expedite the realization of these benefits.</p>
  
 
''2.2.10 What are the incentives and disincentives for participation in geospatial coordination and optimization as a collaboration partner, a customer and as a service provider?''
 
''2.2.10 What are the incentives and disincentives for participation in geospatial coordination and optimization as a collaboration partner, a customer and as a service provider?''
 +
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'''no response? rationale?'''
  
 
''2.2.11 How do you achieve and sustain senior management involvement and commitment to coordinating the use of geographic information or optimizing related spatial data activities?''
 
''2.2.11 How do you achieve and sustain senior management involvement and commitment to coordinating the use of geographic information or optimizing related spatial data activities?''
  
<p>Display all Geographic Data in bright shinny colors... Kidding</p>
 
 
<p>Sustained commitment from senior management within an organization can be assured in two ways:
 
<p>Sustained commitment from senior management within an organization can be assured in two ways:
 
<ul><li>Funding</li><li>Mission</li></ul>
 
<ul><li>Funding</li><li>Mission</li></ul>
Tying funding to an entities' ability to create, maintain, and distribute geospatial information is the most immediate way to ensure the interest of senior management.  For long term success, the organization must evolve to embrace the geospatial data lifecycle as a key component of its mission.</p>
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Tying funding to an entity's ability to create, maintain, and distribute geospatial information is the most immediate way to ensure the interest of senior management.  For long term success, the organization must evolve to embrace the geospatial data lifecycle as a key component of its mission.</p>
 +
 
 +
[''more detail..?'']
  
 
''2.2.12 What governance model do you use or would you recommend for coordinating the use of geographic information or optimizing related spatial data activities?''
 
''2.2.12 What governance model do you use or would you recommend for coordinating the use of geographic information or optimizing related spatial data activities?''
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 +
A refined and clear cut governance model for coordinating the use of geographic information and related activities does not yet exist. As with developing standards, this should be developed using an open process.  The success of the World Wide Web, the open source software movement, and online initiatives like Wikipedia, point to the success of what Benkler calls 'commons-based peer production' in ''Coase's Penguin'' (http://www.yale.edu/yalelj/112/BenklerWEB.pdf).  The prerequisite of such activities is that the work is made available under an open access license (thus a commons), that a community of peers can collaborate on to improve.  Value is built by coordination of a diverse group of individuals and institutions, located in many different places, to do an iterative set of tasks.
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In Benkler's analysis of a "bottom up" process that is oriented towards users, rather than a "top down" process dominated by producers, that can be applied to the geospatial domain.  Ultimately most agencies which produce geographic information are also potential consumers of it; a focus on the user needs should work for all.  Since geospatial information is so diverse, and comes with varying quality of metadata, a top down coordination mechanism may be prone to crumble under its own weight. 
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 +
Open access should be a prerequisite, and that access should be simplified, not requiring lots of expensive software or training.  Geographic information should be accessible online, for rapid re-use and integration into other applications.  If enough value is released into an open environment, then potential users can contribute to the coordination and optimization of spatial data. 
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The open source movement and commons-based peer production leaves it to users to figure out what tasks of coordination and distribution they are most effective at.  Just as some users of Amazon are excited to write reviews of thousands of books, so too there may be potential users of geospatial data who are motivated to write metadata and classify the quality, scale, year, and domain of available geospatial data.  A culture of fear around putting out data without rigorously complete accompanying metadata can be avoided; producers should be able to release their data in to an open environment that can actually assist with the classification and additional information needed by other users. 
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The governance model for commons based peer production can not be dictated in advance, as it is different across domains and individuals involved.  But those that have met success, after an iterative bootstrap period of figuring out the appropriate model, have changed their respective domains.  If access is truly open, not just in license but in real availability, then it becomes possible to leverage the joint efforts of all users to coordinate a process that no single agency could do alone.  The open source software community, the Wikipedia collaborative encyclopedia, the World Wide Web itself, all point to the real world success of such processes.  "Grassroots" projects such as Open Street Map (http://openstreetmap.org) starts to show the potential of coordinating the creation and maintenance of geographic data with full participation from data users. 
 +
  
 
''2.2.13 What is the best approach for assembling and using multiple data sets from diverse fields where scale, units of analysis and data types differ?''
 
''2.2.13 What is the best approach for assembling and using multiple data sets from diverse fields where scale, units of analysis and data types differ?''
 +
<p>The key to working with diverse data is interoperability; this can be best achieved through the use of open standards for data and software. Open source geospatial software offerings have a proven track record for often being the first to implement geospatial standards developed by the Open Geospatial Consortium (OGC). </p>
 +
<p>The inability to read a particular file format is often the factor preventing access to a particular data set. This can occur for several reasons but two common problems are an insufficient capability of a software program to read a particular file format or the inability to read a proprietary file format using incompatible software. Adopting open standards and open source software can alleviate both of these problems. Having a community of individuals and organizations build on open source software libraries can help strengthen the ability of software packages to handle a wide variety of format. A good example of this is the open source Geospatial Data Abstraction Library (GDAL) and OGR which are raster (GDAL) and vector (OGR) translator libraries. Building on open source libraries provides excellent resources for open source and proprietary software developers alike. </p>
  
 
''2.2.14 What geospatial cross-cutting services, best practices, interoperable technologies, and data standards exist but are not necessarily coordinated or optimized by the Federal government?''
 
''2.2.14 What geospatial cross-cutting services, best practices, interoperable technologies, and data standards exist but are not necessarily coordinated or optimized by the Federal government?''
 +
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'''no response? rationale? '''
  
 
''2.2.15 What key issues and challenges must be considered when geospatial lifecycle activities occur in a foreign country that may or may not share borders with the US? What solutions do you propose to overcome these issues and challenges?''
 
''2.2.15 What key issues and challenges must be considered when geospatial lifecycle activities occur in a foreign country that may or may not share borders with the US? What solutions do you propose to overcome these issues and challenges?''
 +
 +
''' no response? rationale?'''
  
 
== ''Scenarios'' ==
 
== ''Scenarios'' ==
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''2.3.9 How can we enable the use of geospatial assets, including both structured and unstructured data (e.g. statistical, geographic, imagery, narrative, etc.) and services for the types of research described in scenario 2?''
 
''2.3.9 How can we enable the use of geospatial assets, including both structured and unstructured data (e.g. statistical, geographic, imagery, narrative, etc.) and services for the types of research described in scenario 2?''
 +
 
''2.3.10 How can the use of geospatial data, technologies and spatial data analysis be leveraged in this scenario?''
 
''2.3.10 How can the use of geospatial data, technologies and spatial data analysis be leveraged in this scenario?''
 +
 
''2.3.11 What are the key components – organizational, training, business, and technical – that establish an environment that is capable of leveraging geospatial data and assets to achieve research objectives?''
 
''2.3.11 What are the key components – organizational, training, business, and technical – that establish an environment that is capable of leveraging geospatial data and assets to achieve research objectives?''
  
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''Federal agencies and other organizations, both individually and collectively, manage billions of dollars of resources that traditionally have not exploited geospatial assets. This encompasses human resources, facilities, supplies, and finance (including grants, contracts, and intramural resources). In the grants management arena, Federal agencies are often required by OMB and Congress to assess and report on the efficiency, effectiveness and return on investment of multiple grant programs and other expenditures made annually to meet mission goals and provide service to citizens.''
 
''Federal agencies and other organizations, both individually and collectively, manage billions of dollars of resources that traditionally have not exploited geospatial assets. This encompasses human resources, facilities, supplies, and finance (including grants, contracts, and intramural resources). In the grants management arena, Federal agencies are often required by OMB and Congress to assess and report on the efficiency, effectiveness and return on investment of multiple grant programs and other expenditures made annually to meet mission goals and provide service to citizens.''
 
''2.3.12 How can we establish the effective and efficient use of geo-referenced or geo-enabled data and assets across organizations, for the types of activities described in scenario 3?''
 
''2.3.12 How can we establish the effective and efficient use of geo-referenced or geo-enabled data and assets across organizations, for the types of activities described in scenario 3?''
 +
 
''2.3.13 How can the use of geospatial data, assets and spatial data analysis be leveraged in scenario 3?''
 
''2.3.13 How can the use of geospatial data, assets and spatial data analysis be leveraged in scenario 3?''
 +
 
''2.3.14 What are the key components – organizational, training, business, and technical – that establish an environment that is capable of leveraging geospatial assets to achieve operational administrative and resource management objectives?''
 
''2.3.14 What are the key components – organizational, training, business, and technical – that establish an environment that is capable of leveraging geospatial assets to achieve operational administrative and resource management objectives?''
  
 
=== Additional Information ===
 
=== Additional Information ===
 
''Please feel free to provide additional information, beyond the questions found in Section 2.2 and 2.3 that you feel should be considered to meet the goals and objectives of the Geospatial Line of Business.''
 
''Please feel free to provide additional information, beyond the questions found in Section 2.2 and 2.3 that you feel should be considered to meet the goals and objectives of the Geospatial Line of Business.''

Latest revision as of 21:44, 7 May 2006

Introduction

This is a wiki version of the questions we need to answer for the RFI. Please feel free to start answering questions, and to edit the existing stuff, even without asking. It's all versioned, so we can roll back if a new change that we don't like is in. Be sure to read the full RFI, that has more about what they're looking for, at: http://www.estrategy.gov/lineofbusiness/docs/geospatial_rfi.doc

Right now we have four people who've thrown their hats in to work on this, feel free to add your name.

  1. Chris Holmes (interspersed time till start of may)
  2. Ned Horning (little time this week, start of may)
  3. Dave McIlhagga (start of may)
  4. Mike Davis (interspersed as workload permits)
  5. Bob Basques (as workload permits)
  6. Kevin Yam

Notes to use

Just ran across this, which may be helpful as a citation of sorts: http://www.linuxdevices.com/news/NS2542131185.html It's about a report 'examining open standards, open source software, and "open innovation." The report concludes that openness should be promoted as a matter of public policy, in order to foster innovation and economic growth in the U.S. and world economies.'

Bibliography of OS and Geo information

Notes on submission

Submission of RFI Responses Responses to the RFI must be submitted by e-mail to GSA by 5:00 p.m. EDT, May 5th, 2006. In responding to the RFI, please use the template labeled Part II: RFI Questionnaire. This template is also available at the following URL: http://www.whitehouse.gov/omb/egov/c-6-8-glob.html. Place your responses in-line in the document, retaining the question number and question text before each answer. Your e-mail should be clearly marked in the subject line with reference to RFI-GSV06PD00089 and your organization. You are required to include a point of contact for your organization. E-mail your response in Word (version 2000 or higher) to geospatial@gsa.gov. Please do not include marketing materials with your response at this time and ensure that any sensitive or protected information is marked as such. The government will ensure this information is not released externally. The overarching objective for this RFI is information gathering and not development of possible government acquisition of products or services.

  • So someone's going to have to paste from this wiki back in to the original document, and email it in.

More notes

Place any additional notes about our information here...

Note that we don't have to respond to every question. The RFI says 'If you choose not to respond to a question, indicate “no response” and identify the rationale.' One can bypass a whole section (e.g. the scenarios, to which no-one has made a response here); "Please respond to the appropriate Sections based on your experience"

The RFI urges this consideration of its goals, in responses:

Respondents must factor key public values as defined by the NSDI into each response whenever applicable. Key public values include:

  • Privacy and security of citizens’ personal data and accuracy of statistical information on people, both in raw form and in derived information products
  • Access for all citizens to spatial data, information, and interpretive products, in accordance with OMB Circular A-130
  • Protection of proprietary interests related to licensed information and data
  • Interoperability of Federal information systems to enable the drawing of resources from multiple Federal agencies and their partners

RFI Questionnaire Section 1: Respondent Information

Please provide the following information about your organization. Responding Organization Name: Open Source GeoSpatial Foundation

Are you responding as a:

User organization from experience coordinating the use of geographic information or optimizing related spatial data activities

Vendor or consultant from experience providing products or services to help other organizations coordinate the use of geographic information or optimize related spatial data activities

Both

Both

Type of organization (e.g. Federal agency, non-profit, state, private): Non-Profit

Contact information (provide a point of contact, phone number and e-mail address):

Primary contact: Chris Holmes, 212-219-6062, cholmes@openplans.org

Secondary contact: Ned Horning, 212-313-7947, horning@amnh.org

Lifecycle Activities

The Office of Management and Budget (OMB) Circular A-161 provides direction for Federal agencies that produce, maintain, or use spatial data either directly or indirectly in the fulfillment of their respective missions. OMB Circular A-16, Section 8 describes Federal agency responsibilities and reporting requirements for collecting, using, or disseminating geographic information or carrying out related spatial data activities. These activities are identified as lifecycle activities for the purposes of this RFI.

Please answer the following questions from the perspective of an overall solution and approach for coordinating the use of geographic information and/or optimizing related spatial data activities. Lifecycle activities are being defined as (1) acquire, (2) process, (3) distribute, (4) use, 5) maintain, and (6) preserve spatial data. Be sure to include innovative practices, the applicability of these practices to Government and any relevant past experience.

2.2.1 In which data themes of national importance is there opportunity for increased effectiveness, efficiency, and cost savings potential across the Federal Government, and what is the recommended transition approach? OMB Circular A-16 framework data themes and other data themes of national significance are (1) geodetic control, (2) orthoimagery, (3) elevation and bathymetry, (4) transportation, (5) hydrography, (6) cadastral, and (7) governmental units.

no response? rationale?

2.2.2 What are the critical change management issues and best practices for successful transition to and full implementation of common solutions?

Promotion and adoption of open standards for the collection, storage, access, and processing of geographic data is fundamental to the development of best-practise common solutions. Common implementation of standard protocols (for exchange) and formats (for storage and distribution) of geographic data are can greatly simplify future transitions.

A recently released report by the Digital Connections Council of the Committee for Economic Development, “Open Standards, Open Source, and Open Innovation: Harnessing the Benefits of Openness” (http://www.ced.org/projects/ecom.shtml#open) highlights the interoperability benefits gained from adopting open standards.

However, the presence of standards alone is not sufficient. The Open GeoSpatial Consortium (OGC) has made great strides in developing a set of standards, which precisely define a solution for interoperability of geographic data and systems. Yet uptake has been slow, as few outside of the standards writers see compelling reason to implement common solutions. Additionally, there are often large investments needed to adopt a standard. Investments may take the form of an upgrade to current software, developing or acquiring new software, or investing significant time in getting an open source solution running.

In transition to a common solution, these concerns can be addressed by:

- providing proof of best practise in ease of implementation of open standards for geographic data - providing proof of value and return on investment in doing so

In order to encourage uptake, data providers need some compelling reason to transition a common solution. While the OGC community passed by promotion of their standards to write newer, more niche ones geared towards higher overhead uses, Google Earth came along with a compelling, user friendly environment with lots of available data. Far more organizations are making their data available as KML, the Google Earth standard, than have set up a Web Map Service interface. With WMS one tends to only replicate functionality that was already available, albeit in a more open way.

A compelling example of the power of interoperability is needed to render a new investment attractive to stakeholders; an open standards based solution cannot be merely a requirement demanded from above. The essence this is "bottom up" rather than "top down" approach is exemplified by the World Wide Web. Participation in the was not a question of being obliged to implement HTML and HTTP standards to share one's information; not doing so, one would be "missing the boat". If the Geospatial Web is perceived as something that is working now, and can be as compelling as the World Wide Web, it is naturally to everyone's advantage to implement common solutions.

The impact of potentially large infrastructure investment needed to adopt a standard, can be greatly minimized by available user friendly open source implementations of the open standards. This allows organizations to 'try out' new open standards without having to heavily invest in new infrastructure, the advantages of which are unknowable.

This is in no way exclusive of proprietary implementations of open standards, and most proprietary vendors that we've talked to welcome the availability of open source implementations.

After an initial evaluation phase of the standard itself, using the open source software, most organizations will complete a full evaluation of available solutions, and many times proprietary solutions will fit them best. Open standards and common solutions also benefit from many implementations; the more data that is available, the more compelling an environment. For vendors of proprietary software, 'a rising tide raises all boats', even if many people choose open source solutions. To go back to the World Wide Web analogy; though the open source Apache Web Server has a majority of the web server market, the proprietary vendors all have much greater sales as a result of the fact that more organisations are offering their online via standard protocols and formats; an outcome which Apache enabled by greatly lowering the barrier to entry.

Additionally, open source solutions will easily operate alongside legacy systems, so that an entirely new investment is not needed to transition over a whole infrastructure. Open source can run side by side with proprietary solutions, with open source implementing the new open standards. Stakeholders can maintain their regular workflows and transition to a more common solution in time. The open nature of the code means that even if a certain legacy system is not already available to be integrated, it is relatively easy to modify the open code to work with the legacy code. This mitigates the risk of transition to common solutions by allowing the transition to be iterative, incrementally adding small pieces along the way, instead of requiring a massive upheaval.


2.2.3 What cultural impediments and training issues are paramount at which stages of the transition? What are the solutions to them?

Although the United States is a global leader in providing public access to data, the process of collecting and maintaining, storing and processing these data are open. Historically, this has been the case because vendors providing these services use proprietary methods with the intent of gaining a competitive edge over their competition. This approach is rooted in traditional intellectual property protection ideals and can result in incompatibility between data sets, and high costs to the government. This mindset is a significant cultural impediment to achieving common solutions for working with geospatial data and can be overcome by developing open data and software standards and promoting the benefits of this approach to the business community and government organizations.

Cultural Issues

  • Data Ownership vs. Data Stewardship
  • Drawing Centric vs. Data Centric (especially in CADD shops)
  • Public vs Private (or percieved to be Private).
  • Data format preferences still exist that may not coincide with the greater good.

Training Issues

  • Cost of use, training materials derived from open source packages vs proprietary packages.
  • Simple is better, if something is easier to use, it's more likely to be used.
  • Proprietary vs OpenSource

2.2.4 From your experience, please describe the cost/benefit of coordinating the use of geographic information or optimizing NSDI components and related spatial data activities across all sectors and levels of government.

Many current activities rely on a string of participants to manage a Geographic Information System. A system needs to allow individual data owners to update and maintain their respective datasets with the least amount of percieved extra work. If the process is precieved by the data owners to be additional effort on their part, it's much less likely to take hold as a standard. The process needs to be as painless as possible for the Data Steward in order for a system to be self sustaining.

Publication by Data Owners requires a few basic needs be met, such as:

  • Move publication and maintenance of data as close as possible to the data owners/creators.
  • Owners/creators are also responsible for appropriate metadata for their respective datasets. This aids in data discovery mechanisms for the end users.
  • Responsibly for upkeep and timeliness of data should be traceable to the owners/creators by average users of the data.
  • User Feedback systems need to be in place for relaying of errors and/or omissions back to the data owners.

2.2.5 What are the top three critical factors for successfully coordinating the use of geographic information or optimizing related spatial data activities?

  • Data interoperability – It is important that data can be used in all anticipated situations. This means it must be possible to combine it with other data and it must be usable within a broad range of available systems.
  • Accessibility – This includes physical access to data layers and the ability to work with those data in available usable systems (for example a GIS with trained personnel.)
  • Data Currency – Data currency must be within the requirements of the intended application.

2.2.6 What are the top three risks in coordinating the use of geographic information or optimizing related spatial data activities? How do you mitigate these risks?

  • Data Accuracy
  • Data Availability
  • Data Compatibility

The three biggest risks when building business practices based on shared geospatial information reflect the critical factors mentioned in 2.2.5. For shared systems to work, each proponent must be willing and able to meet a certain standard level of service that ensures the reliability and consistancy of the data provided. These data must be available in a format that is accessible to the end user regardless of software package or vendor.

2.2.7 What are the key performance indicators related to coordinating the use of geographic information or optimizing related spatial data activities? What metrics can be obtained to measure performance and how?

While data accuracy can be a difficult metric to measure shared spatial data by, it is probably the most important factor when relying on such data for business processes.

Easier to measure is the level of consistancy maintained by shared spatial data. Data that follows an established standard (ie. SDSFIE) https://tsc.wes.army.mil/ can be graded based on how well it follows and implements said standard.

Another important metric for coordinating use geographic data is the length of time required for changes made by the data steward to be reflected in the shared dataset. Minimizing this refresh time is critical if the shared datasets are to be considered an authoritative source of information.

2.2.8 How do you retain the advantages of competition while reaping the benefits of geospatial coordination and optimization?

Advantages of competition are perceived to be improved innovation (producing a better product) and reduced cost to the consumer. By developing and using open standards innovation is improved because of the size and diversity of the community developing the standards. Cost is also reduced because once the standards and clearly defined metrics of success are in place, the cost of entry for product development is reduced. To strengthen competition it helps if companies can compete on a level playing field that is promoted through the use of open standards.

2.2.9 How do you ensure and manage ongoing innovation in geospatial coordination and optimization?

The most effective way to ensure continued innovation is to promote and adopt open standards for the creation/collection, storage, access, and processing of geospatial data. This includes contributing to the development of open source geospatial software that supports and promotes common standards.

It is in the data users’ and producers’ interest to have interoperable solutions and the most effective way to accomplish this is to include them in the process of developing standards and software. The benefits of using open methods are becoming well publicized (for example see: http://www.amso.army.mil/cc-tteam/PMG_04_MOSA.pdf). [quote?]

To further benefit from current open approaches it is necessary to fund research and development for improved interoperability and access. Research should also be conducted on innovative open approaches for creating and maintaining geospatial data layers in an open environment. The potential of openness in the geospatial sector is great but funded research is needed to expedite the realization of these benefits.

2.2.10 What are the incentives and disincentives for participation in geospatial coordination and optimization as a collaboration partner, a customer and as a service provider?

no response? rationale?

2.2.11 How do you achieve and sustain senior management involvement and commitment to coordinating the use of geographic information or optimizing related spatial data activities?

Sustained commitment from senior management within an organization can be assured in two ways:

  • Funding
  • Mission

Tying funding to an entity's ability to create, maintain, and distribute geospatial information is the most immediate way to ensure the interest of senior management. For long term success, the organization must evolve to embrace the geospatial data lifecycle as a key component of its mission.

[more detail..?]

2.2.12 What governance model do you use or would you recommend for coordinating the use of geographic information or optimizing related spatial data activities?

A refined and clear cut governance model for coordinating the use of geographic information and related activities does not yet exist. As with developing standards, this should be developed using an open process. The success of the World Wide Web, the open source software movement, and online initiatives like Wikipedia, point to the success of what Benkler calls 'commons-based peer production' in Coase's Penguin (http://www.yale.edu/yalelj/112/BenklerWEB.pdf). The prerequisite of such activities is that the work is made available under an open access license (thus a commons), that a community of peers can collaborate on to improve. Value is built by coordination of a diverse group of individuals and institutions, located in many different places, to do an iterative set of tasks.

In Benkler's analysis of a "bottom up" process that is oriented towards users, rather than a "top down" process dominated by producers, that can be applied to the geospatial domain. Ultimately most agencies which produce geographic information are also potential consumers of it; a focus on the user needs should work for all. Since geospatial information is so diverse, and comes with varying quality of metadata, a top down coordination mechanism may be prone to crumble under its own weight.

Open access should be a prerequisite, and that access should be simplified, not requiring lots of expensive software or training. Geographic information should be accessible online, for rapid re-use and integration into other applications. If enough value is released into an open environment, then potential users can contribute to the coordination and optimization of spatial data.

The open source movement and commons-based peer production leaves it to users to figure out what tasks of coordination and distribution they are most effective at. Just as some users of Amazon are excited to write reviews of thousands of books, so too there may be potential users of geospatial data who are motivated to write metadata and classify the quality, scale, year, and domain of available geospatial data. A culture of fear around putting out data without rigorously complete accompanying metadata can be avoided; producers should be able to release their data in to an open environment that can actually assist with the classification and additional information needed by other users.

The governance model for commons based peer production can not be dictated in advance, as it is different across domains and individuals involved. But those that have met success, after an iterative bootstrap period of figuring out the appropriate model, have changed their respective domains. If access is truly open, not just in license but in real availability, then it becomes possible to leverage the joint efforts of all users to coordinate a process that no single agency could do alone. The open source software community, the Wikipedia collaborative encyclopedia, the World Wide Web itself, all point to the real world success of such processes. "Grassroots" projects such as Open Street Map (http://openstreetmap.org) starts to show the potential of coordinating the creation and maintenance of geographic data with full participation from data users.


2.2.13 What is the best approach for assembling and using multiple data sets from diverse fields where scale, units of analysis and data types differ?

The key to working with diverse data is interoperability; this can be best achieved through the use of open standards for data and software. Open source geospatial software offerings have a proven track record for often being the first to implement geospatial standards developed by the Open Geospatial Consortium (OGC).

The inability to read a particular file format is often the factor preventing access to a particular data set. This can occur for several reasons but two common problems are an insufficient capability of a software program to read a particular file format or the inability to read a proprietary file format using incompatible software. Adopting open standards and open source software can alleviate both of these problems. Having a community of individuals and organizations build on open source software libraries can help strengthen the ability of software packages to handle a wide variety of format. A good example of this is the open source Geospatial Data Abstraction Library (GDAL) and OGR which are raster (GDAL) and vector (OGR) translator libraries. Building on open source libraries provides excellent resources for open source and proprietary software developers alike.

2.2.14 What geospatial cross-cutting services, best practices, interoperable technologies, and data standards exist but are not necessarily coordinated or optimized by the Federal government?

no response? rationale?

2.2.15 What key issues and challenges must be considered when geospatial lifecycle activities occur in a foreign country that may or may not share borders with the US? What solutions do you propose to overcome these issues and challenges?

no response? rationale?

Scenarios

Scenario 1 - Emergency Response:

The U.S. is experiencing an “Incident of National Significance”, as defined by Homeland Security Presidential Directive 5 (HSPD-5) that has required activation of the National Response Plan (NRP). The NRP provides a framework for the coordination of Federal, state, local, private, volunteer, and Non-Governmental organizations to work together in real time to respond effectively. Under the NRP, significant Federal geospatial data and assets are mobilized and made available to the responding homeland security (HLS) community. However, significant geospatial data and assets are available at the state and local level that are not immediately available to responding Federal Departments and agencies.

2.3.1 Please describe the types of non-Federal geospatial data that are available at the state and local government level, as well as from private utilities and other entities that might improve the effectiveness of the NRP.

In your response please address any issues regarding licensing of data, the need for information sharing agreements and similar impediments to other than full and open sharing of geospatial data within the HLS community.

2.3.2 What activities need to be undertaken during the Preparedness phase of the emergency lifecycle to assure emergency managements are aware of the potential of geospatial data and assets to support emergency response?

2.3.3 What activities need to be undertaken during the Preparedness phase of the emergency lifecycle to assure that geospatial technology subject matter experts and data stewards are aware of the emergency response requirement and standard operating procedures?

2.3.4 During response to an Incident of National Significance, what needs to be done to assure geospatial data and assets are made available to all participants in the NRP? In particular, please identify issues that must be addressed to assure state and local geospatial data and assets can be made readily available to all participants in the response?

2.3.5 What activities to coordinate geospatial data and assets for emergency management applications are you aware of?

2.3.6 What activities do you suggest be undertaken to coordinate the use of geographic information or optimize related spatial data activities for emergency management?

2.3.7 Geospatial data can also play a critical role in performing analyses to support pre-disaster mitigation plan development and implementation as well as support of recovery operations. Please describe key aspects of the use of geospatial data and assets for pre-disaster mitigation and recovery.

2.3.8 What are the key components – organizational, training, business, and technical (including fixed and mobile technology) – that establish an environment that is ready to respond (preparedness), able to respond (incident management), capable of supporting pre-disaster mitigation and post-disaster recovery analysis, and provides enhancements or lessons learned for future event management?

Scenario 2 - Long Term Research Scenario:

The U.S. perceives societal benefit in performing long-term research. Research is being conducted in numerous social and physical science fields such as demographics, public infrastructure, climatology, health care, economics, and crime, etc.

2.3.9 How can we enable the use of geospatial assets, including both structured and unstructured data (e.g. statistical, geographic, imagery, narrative, etc.) and services for the types of research described in scenario 2?

2.3.10 How can the use of geospatial data, technologies and spatial data analysis be leveraged in this scenario?

2.3.11 What are the key components – organizational, training, business, and technical – that establish an environment that is capable of leveraging geospatial data and assets to achieve research objectives?

Scenario 3 - Administration and Resources Management:

Federal agencies and other organizations, both individually and collectively, manage billions of dollars of resources that traditionally have not exploited geospatial assets. This encompasses human resources, facilities, supplies, and finance (including grants, contracts, and intramural resources). In the grants management arena, Federal agencies are often required by OMB and Congress to assess and report on the efficiency, effectiveness and return on investment of multiple grant programs and other expenditures made annually to meet mission goals and provide service to citizens. 2.3.12 How can we establish the effective and efficient use of geo-referenced or geo-enabled data and assets across organizations, for the types of activities described in scenario 3?

2.3.13 How can the use of geospatial data, assets and spatial data analysis be leveraged in scenario 3?

2.3.14 What are the key components – organizational, training, business, and technical – that establish an environment that is capable of leveraging geospatial assets to achieve operational administrative and resource management objectives?

Additional Information

Please feel free to provide additional information, beyond the questions found in Section 2.2 and 2.3 that you feel should be considered to meet the goals and objectives of the Geospatial Line of Business.