In this day and age, data has become a resource sought after by businesses and policymakers alike. Countries like
India, the
United Kingdom (UK),
Australia, and
many others are leveraging the power of enormous data reserves, collected and maintained by government departments, to reform their approach to governance and economic growth. The government, especially in India, is in control of heaps of raw datasets collected over decades through publicly funded projects and schemes like
the Mahatma Gandhi National Rural Employment Guarantee Act 2005 which could be utilised to inform better policymaking.
UNESCO declared 28 September as the
International Day for Universal Access to Information to promote citizens' demand for information transparency from governments as access to information is closely linked to the realisation of other rights, such as freedom of the press, etc. Moreover, access to Open Government Data (OGD) allows citizens to track the effectiveness and efficiency of government schemes and enables businesses to build community-oriented innovations. It also facilitates data and knowledge sharing between government departments to break silos, monitor schemes beyond their departments, and identify issues for intra and inter-ministerial collaboration. It pushes governments and businesses to prioritise transparency and accountability which are the cornerstones of resilient and inclusive societies.
Governments are yet to maximise the potential of data collected. Missing datasets, asynchronous approaches to data collection methods and metadata, and counterintuitive approaches to data visualisation limit the access and usability of OGD.
However, governments are yet to maximise the potential of data collected. Missing datasets, asynchronous approaches to data collection methods and metadata, and counterintuitive approaches to data visualisation limit the access and usability of OGD. Moreover, open data policies also fail to adequately define technical and legal standards required for data re-usability.
India’s OGD journey started back in 2012 with the Ministry of Science and Technology publishing the
National Data Sharing and Accessibility Policy (NDSAP). Since then, India’s OGD mandate has evolved. Several states such as
Tamil Nadu and
Punjab have developed state-specific data sharing policies; the Digital India programme has recognised OGD as one of its core pillars, and NITI Aayog launched the
National Data and Analytics Platform (NDAP). This article traces the evolution of India’s OGD journey and proposes recommendations to plug the gaps in India’s OGD ecosystem.
Evolution of India’s OGD platform
The government’s vision with NDSAP was clear. In the absence of a data management system that could facilitate data sharing between government departments and citizens, troves of data generated by government departments were being underutilised for policy making. NDSAP initiated the process of sharing the data generated using public funds with data owners and between government agencies using OGD Platform,
data.gov.in. It was supposed to be updated periodically and provide standardised data in human-readable and machine-readable forms to ensure wider accessibility. The platform contains datasets from 165 government departments across 33 sectors today.
However, only a few datasets met the mark. NDSAP had not laid clear protocols for information gathering, processing, and sharing. For instance, government departments were not aligned on data collection methodologies and terminologies—they were collecting different information under the same heading or the same information under different headings. Most often, data is uploaded in the form of scanned PDFs or images on government websites making data extraction difficult. Moreover, India does not have data anonymisation standards yet. The Ministry of Electronics and Information Technology (MeitY) released the draft data anonymisation guidelines only recently in August 2022 but
withdrew the document within almost a week as it believed the draft required more expert consultations. As such, central government departments, much like the state departments, are not aligned on the framework to ensure privacy and data protection.
Standard Operating Protocols (SOPs) for data standardisation have been outlined to regularly update the data, track compliance among departments and present it using clearly outlined definitions to ensure users can make sense of similar data from different sources.
NITI Aayog’s NDAP aims to address many of the aforementioned gaps amongst others by building on existing initiatives such as
data.gov.in,
DISHA by the Ministry of Rural Development, and state-specific open data policies. NDAP is designed to standardise data originating from diverse sources to make it accessible and conducive for innovation, research, policymakers, and public consumption. Standard Operating Protocols (SOPs) for data standardisation have been outlined to regularly update the data, track compliance among departments and present it using clearly outlined definitions to ensure users can make sense of similar data from different sources. NITI Aayog has been working on this project for years now. The call for consultants to support technical aspects of the mission was published in
2018, followed by the vision document published in
2020. The piloting stage of the platform was initiated in
2021 and was made available for public usage in
2022.
Bridging OGD ecosystem gaps
NDSAP has played a pivotal role in improving wider data accessibility. Now, NDAP is aiming to
build on it and other open data initiatives to enhance data usability. For, one, NDAP, at the very outset, incorporated feedback on the limitations of the existing OGD platforms from technical experts and data users like bureaucrats, innovators, journalists, policymakers, citizens and researchers to ensure NDAP stays relevant and is coherent. It also aims to sustain such communication between data producers and data users. Two, it set out clear criteria for ensuring the quality of datasets.
Going forward, to ensure India’s sustainable and streamlined progress on OGD, capacity building of Chief Data Officers (CDOs), incentivising OGD usage and ensuring synchronisation of values assigned to data between government and state departments must be prioritised. In addition to increasing the number of training workshops for CDOs, there is a need to assign specific resource persons or
data contributors with the skillset required to collect, clean, process, upload and analyse the data within each government department. This will assist in overcoming the resistance amongst government officials in proactively sharing standardised datasets. The data contributor could also facilitate identifying projects to foster inter and intra-ministerial collaboration.
In addition to increasing the number of training workshops for CDOs, there is a need to assign specific resource persons or data contributors with the skillset required to collect, clean, process, upload and analyse the data within each government department.
Besides organising
OGD hackathons and other competitions to garner public interest, GoI should also monitor the backend of the platform(s) for the datasets that are in demand and annually present case studies on existing and prospective use cases similar to the
Data-Driven Decision Making compendium that was launched in June 2016. Additionally, high-value datasets could correspond to the use cases within the
five sectors identified by NITI Aayog in its National Strategy on Artificial Intelligence a) healthcare, b) education, c) agriculture d) smart cities and infrastructure and e) smart mobility and transportation. As such, these datasets could be uploaded on priority.
Earlier this year, MeitY published the
Draft India Data Accessibility & Use Policy 2022 to standardise the data management framework and establish uniform metadata standards to improve the quality of and access to non-personal government datasets. Soon after its release, the policy was withdrawn and replaced by the
Draft National Data Governance Framework Policy as the proposition to commercialise government datasets in the previous draft received wide criticism. Stakeholders were worried that the draft prioritised commercial interests over privacy since the government demonstrated an inclination toward
licensing data to the private sector. State governments like Odisha and Karnataka have also
resonated with the idea of monetising OGD in
Odisha State Data Policy and
Karnataka Open Data Policy.
In the absence of comprehensive data anonymisation and protection framework in India, the central government needs to ensure values assigned to data are in sync with the existing laws and frameworks of data governance and adequately prioritise individual privacy. Moreover, the final draft of the data governance framework must also outline protocol to avoid duplicity of efforts in collecting and uploading data.
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