August 09, 2021

Embed open data principles in Master Plans to make planning more inclusive

This blog was written for the Data Governance Network.

 

The Delhi Development Authority (DDA) missed a beat in the public consultation round of the recently released Delhi Master Plan 2041. Despite the fact that planning exercises in cities collect and generate valuable geospatial data, the DDA did not put out the proposed land use plans in spatial file formats. Releasing the data in such a way would have allowed holistic analysis of the masterplan by combining it with other datasets. Instead, the authority released the maps in unusable formats for public comment by 23rd August 2021, inhibiting a proper examination by civil society. 

 

Fortunately, the open data community stepped in and reproduced the spatial data from the land use map and created a simple open source tool to enable the citizens to interact with the different layers of the proposed plan. The value of this data and the tool was quickly evident with the Main Bhi Dilli (MBD) campaign using the tool in parts of their larger Master Plan awareness drive. Further, some communities under the MBD campaign showcased how their homes were not recognised under the plan.

 

This recent experience with the Delhi Master Plan is not an anomaly, rather the norm. Land use plans released in the correct geospatial formats are extremely rare. At present, despite vast surveys and data collection and generation exercises undertaken as part of the plan, the only components that are found in the public domain are often a PDF, JPEG or scanned photo of the proposed land use plan. By adopting geospatial formats, in-depth analysis of the master plan can be conducted, allowing for richer, more productive feedback from civil society. 

 

While some cities such as Mumbai have built a portal to allow citizens to interact with the draft development plan 2034, the layers themselves cannot be downloaded from here for any further spatial analysis by citizens or researchers. Moreover, while civil society has been able to step in to bridge this spatial data gap partially, these too fall short of reproducing the whole. In particular, the data volunteers who developed the tool for the Delhi Master Plan, could only recreate the geometries (such as, boundary shapes of various land use types) of the layers from the plan, but not the categorisation within each layer. For example, the recreated data would only capture the classification of a piece of land as ‘commercial', not what commercial activity it is specifically marked for such as retail shopping, hotel, community centre, and many others.

 

With the recent Geospatial Guidelines and the subsequent National Geospatial Policy 2021, the Government of India has acknowledged the importance of granular spatial data across diverse sectors. In fact, the guidelines have expressed commitment to make easily accessible all spatial data generated through public funds. These developments should encourage urban planning authorities at multiple levels of the government to share spatial datasets generated through the planning process publicly. Further, a list prepared by the Department of Science and Technology with features and installations and their sensitive attributes can be referred to for handling security related concerns, if any, before publishing the spatial data. 

 

In general, an open data culture needs to be built within planning exercises. A first step towards this goal is to acknowledge its importance in the policy realm of the planning process. Currently, some states such as GujaratMaharashtra, and Mizoram have legally binding Town and Country Planning Acts that mandate making the ‘maps’ and ‘charts’ public along with the draft of the development plan or the master plan. However, they do not mandate publishing the spatial data publicly. While the national level Urban and Regional Development Plans Formulation and Implementation (URDPFI) Guidelines, prepared by the Ministry of Housing and Urban Affairs, do emphasise the value of public participation in planning, they need to go one step further and highlight the importance of open spatial data to improve the quality of participatory planning. The guidelines can further specify some of the basic file formats in which the local level spatial data should be published for improved standardisation. Moreover, metadata standards should also be created and data should be released under the Government Open Data License (GODL) wherever possible. 

 

Second, the Ministry of Housing and Urban Affairs (MoHUA) should track the progress of cities publishing this data. One policy tool that can be leveraged to achieve this goal is the centrally funded sub-scheme to formulate GIS based master plans in the Atal Mission for Rejuvenation and Urban Transformation. The Ministry tracks the progress made by the mission cities under this sub-scheme on a centralised dashboard along ten stages, from geo-database creation to formulation of the final master plan. The scheme should mandate local planning bodies to open the spatial databases created to the wider public and add this as one of the stages to track on the dashboard. Examples of such data include baseline spatial data, existing land use, and the proposed plan. 

 

Third, to make spatial data more accessible and usable by a wider audience, local planning bodies should find ways to collaborate with open data communities to build tools on top of the spatial datasets, instead of relying on proprietary solutions that financially burden an already resource-crunched system. For this, governments need to acknowledge that open data communities in India are both willing and capable of building solutions with public bodies. For instance, an interactive platform for citizens to interact with the layers of the proposed plan and collect location-based comments and feedback can be built collaboratively with the community over platforms like Github. Open source solutions, especially when built with the community, not only strengthen the state-citizen relationship, but also create an opportunity for new innovations. The best part about such solutions is that, once built, they can be customised and deployed by other planning authorities with minimal additional effort.

 

The current way in which planning exercises carry out public consultation needs to change. Doing so would allow for holistic, data driven feedback by civil society on ways to improve the plan. By inculcating a culture of openness in the process through improving guidelines, oversight by MoHUA and onboarding relevant civil society partners in the exercise, the ultimate quality of such plans will increase, allowing for a more inclusive and holistic long-term development of our cities.

 

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