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Abstract
To make good decisions about the future direction of cities we need data to contextualize and make recommendations that are based on past results and potential models for the future. Yet access to information including geographic information systems (GIS) is challenging, particularly as data are often seen as a commodity or source of power by those who control it, a dynamic more severe in contexts like Kenya. By generating GIS data for our own transportation model and then sharing them with those interested in doing research on Nairobi, we experienced firsthand some of the power dynamics associated with accessing and generating information in the developing country context. The project had several important lessons: (1) Simply developing data does not make them open; how “open access” is provided to the data is just as important as making them freely available. (2) Developing data can show commitment to a particular place or project that can help generate support for stronger partnerships and project goals. (3) Openly sharing data about place might help push those with access to information to share information as well. Overall this research project illustrated that sharing data can help support a more open access ecosystem locally by establishing a culture of data sharing but only if those interested in using it have the technical ability to both access and use data sets provided.
为了为城市的未来方向做出好的决策, 我们需要根据过去的结果和未来可能模型的数据, 进行脉络化并提出建议。但信息的获取, 包含地理信息系统 (GIS), 是具有挑战性的, 特别是因为对掌控者而言, 信息经常被视为商品或是权力的来源, 而此般情势在肯亚的脉络中更为严重。我们透过为自身的交通模型生产地理信息系统数据, 并将之与有兴趣研究奈洛比的研究者分享, 我们亲身经验了在发展中国家的脉络中, 关乎获取和生产信息的一些权力动态。该计画有下列几项重要的教训: (1) 建构数据本身并不代表开放数据; 如何提供数据的 “开放管道”, 与让它能够免费被使用同等重要。 (2) 建构数据能够展现对特定地方或计画的承诺, 进而有助于产生对更高的参与度及计画目标的支持。 (3) 公开分享一地的数据, 可能有助于促使原本拥有信息管道者分享其信息。总的来说, 本研究计画证实, 透过建立数据分享的文化, 有助于支持更为开放的在地生态系统, 但只有当有意使用数据者拥有获得并使用所提供的数据组的技术能力之时才成立。
Para tomar buenas decisiones sobre la futura administración de ciudades es necesario disponer de datos para contextualizar y formular recomendaciones apoyadas en resultados pasados y modelos potenciales para el futuro. Sin embargo, lograr acceso a información que incluya sistemas de información geográfica (SIG) es todo un reto, en particular porque los datos a menudo son vistos como una mercancía o una fuente de poder por quienes los controlan, dinámica que es aún más severa en contextos como Kenia. Generando datos SIG para nuestro propio modelo de transporte para luego compartirlos con los interesados en adelantar investigaciones sobre Nairobi, tuvimos la oportunidad de experimentar de primera mano algunas de las dinámicas de poder asociadas con la circunstancia de tener acceso y generar información, en el contexto de un país en desarrollo. El proyecto dejó varias lecciones importantes: (1) El simple hecho de desarrollar datos no los convierte en abiertos; cómo darle “acceso abierto” a los datos es igual de importante a presentarlos como libremente disponibles. (2) El desarrollar datos puede mostrar compromiso hacia un lugar o proyecto particular, lo cual puede ayudar a generar apoyo para asociaciones más fuertes y para los objetivos del proyecto. (3) Compartir abiertamente datos sobre el lugar podría ayudar a decidir a quienes tienen acceso a la información a que también compartan información. En general, este proyecto de investigación sirvió para ilustrar cómo compartir datos puede ayudar a apoyar localmente un ecosistema de acceso abierto más fuerte, estableciendo una cultura de compartir datos siempre que quienes estén interesados en beneficiarse de esta práctica tengan la habilidad técnica para acceder a los conjuntos de datos provistos y sepan usarlos.
Acknowledgments
The authors would like to thank the Volvo Research and Educational Foundations for generously supporting this research. Special thanks go to Columbia University's Spatial Information Design Lab and those who created the data set, including Gitanjali Dadlani, Chris Simi, Paul Berg, Aja Maria Hazelhoff, Rob Viola, Michelle Tabet, and Alejandro de Castro Mazarro. In addition, we thank Eric Aligula and James Gachanja at KIPPRA and Professor Elliott Sclar, Julie Touber, Jennifer Schumacher-Kocik, Jennifer Graeff, Jonathan Chanin, and Arif Noori at Columbia University's Earth Institute. We would also like to especially thank Professor Peter Ngau (University of Nairobi), Edwin Wamukaya, Miriam Maina, and Peter Kinyua for their support and involvement in this work.
Notes
1. Rambaldi has developed an online PPGIS training course for NGOs and GIS activists at http://pgis-tk-en.cta.int/ (last accessed 20 October 2013).
2. Early attempts to develop a GIS database in Botswana show that record keeping for land tenure in many developing countries can be complex and based on a cross-section between colonial allocation and indigenous systems, thus making it hard to develop databases that correctly convey ownership (Nkambwe Citation2001).
3. For example, in 2006 the Department of Geospatial and Space Technology within the school of Engineering at the University of Nairobi started a master of science in GIS program.
4. The policy of the KNSDI is to collect, integrate, and distribute geospatial information and services for use and sharing by all public, private, and civil society organizations in Kenya. The overall stated goal of the initiative is to encourage the use of geospatial information in local, regional, and national levels of government to achieve gains in market development, sustainable development, and transparent and participatory governance (Survey of Kenya 2008). KNSDI policy acknowledges the importance of establishing a national repository of spatial data to encourage access, sharing, and dissemination. Further, the policy acknowledges how important spatial information is for legislative and policy development, natural resource allocation, public safety, and regulatory activities.
5. Some of the limiting factors to achieving this goal include high Internet costs, the need for a clear communication strategy to reach more users and increase awareness of the NSDI, passing NSDI policy and related legislation to legalize and institutionalize GIS, a lack of adequate funding for NSDI for both hardware and software, and the wider recognition that spatial data are a resource that should be accessed freely and disseminated (Murage, Gitimu, and Sato Citation2008).
6. See opendata.go.ke
7. See http://www.virtualkenya.org (last accessed 3 January 2013).
8. The Volvo Research and Educational Foundations (VREF) represents a collaboration of four foundations that fund research and education on transportation, the environment, and energy. The four foundations that contribute funds to VREF include the Volvo Foundation, the Volvo Educational Foundation, the Dr. Pehr G. Gyllenhammar Foundation, and the Hákan Frisinger Foundation for Transport Research. It supports eight research centers funded by VREF, or Centres of Excellence (CoEs), located throughout the world that focus on the future of urban transport. VREF is governed by a board that decides which research will be funded, establishes policy, and is responsible for long-term asset management and the Scientific Council, which evaluates the scientific quality of research funding applications and the ongoing output of each of the CoEs. VREF funded this work as part of its Future Urban Transport Programme (FUT), which aims to “contribute to the development of sustainable transportation systems” through interdisciplinary academic research in collaboration with intended users’ research results, such as traffic and city planners, politicians, government agencies, and interest groups (VREF 2013).
9. As an anonymous reviewer for this articles pointed out, “This intra-development coalition competition for geospatial data is not confined to the Kenyan case. It is a fundamental reality for all users of geospatial systems” (see also Goss Citation1995).
10. It should be noted that transportation models usually need a combination of land use data, population information, and road network data. The road network data in a transportation model clearly form one of the most essential components, as they usually provide information on road capacity and limitations such as street direction or ability to turn. As mentioned, whereas census information for Nairobi was available for population information, land use and building density data could help to estimate the amount of trips generated by certain land uses. For example, a retail location will produce more trips than a residential location.
11. We recognized the importance of verifying data through on-the-ground observations, but the Survey of Kenya maps were made earlier than our maps and we wanted the data we digitized to represent the world as it was surveyed by JICA at the time.
12. See http://www.freebase.com/ (last accessed 20 October 2013).
13. In many ways, our addition of the data to a wiki space acted as an informal or bottom-up SDI for Nairobi where a governmental SDI did not yet exist.
14. See the project “Map of Land Use Change From Residential to Commercial: City of Nairobi: 2008–2010” at http://www.virtualkenya.org/maps/map-images/524-map-of-land-use-change-from-residential-to-commercial-city-of-nairobi-2008–2010 (last accessed 3 January 2013).
15. We also discovered that people within government or with links to government sometimes use spatial data as a commodity to be sold informally. Thus, this group would have little interest in making such information freely available.