Tracking R&D funding in the Global South: challenges and opportunities in India

Global South countries have less capacity to spend on R&D, often less than 1% of GDP. For example, India spent around 0.8% of its GDP on R&D in recent years. Given such limited spending, it is particularly important for these countries to understand how and what research they are funding, and for which purposes. This can help maximize the use of limited resources, minimize waste and duplication, avoid spending disproportionate amounts on research that may not be relevant to local contexts, and improve coordination between the different funding agencies operating in a country.

In a recent IDRC funded project on Funding Flows in the Global South, we found that there are major gaps in the tracking of research funding within and to the Global South. A lot of information is missing regarding funding flows from the Global North to the Global South, as currently provided by either scientific funding agencies or through official development aid (see discussion and sources). However, our analyses also revealed that for most countries (and certainly for middle-income countries), these flows were relatively small in comparison to national R&D funding (except for Africa, see regional dashboard), yet information about national research funding in the Global South had the biggest gaps. For a small number of funding agencies (e.g. from Brazil, Chile and South Africa), we found that the coverage was incomplete. But for most funding agencies in the Global South, the information is missing.

In most countries, besides the traditional aggregate R&D statistics, the only way to track research funding flows in more detail is through the funding metadata collected from scientific publications acknowledging their national funding agencies. But this method obviously cannot capture flows where no papers are published because the outcomes are very different, for example, a product, prototype, technology, dataset, policy intervention, or other forms of research output. And even when papers are published, the funding metadata does not reveal grant amounts; it is often incomplete, and therefore, it cannot produce a reliable picture of the funding landscape.

This problem is well known to policymakers. In India, for example, NITI Aayog, the apex policy think tank of the government, published the report ‘Ease of Doing Research and Development in India – Removing Obstacles, Promoting Enablers’, which states that ‘greater emphasis must be placed on clarity of purpose, flexibility in execution and accountability for outcomes’. The report also flags that substantial funding from one of the major science funding agencies in the country goes to only a handful of premier institutes, accounting for about 80% of the total funding, and it also expresses concerns that multiple central agencies may be funding similar research areas, resulting in overlap and what the report calls the “inefficient” use of public money.

The solution proposed is a Unified Project Management System (UPMS), and public announcements have been made regarding plans to launch such a system to track and manage research funding by central agencies. This would allow the system to coordinate, reduce duplication and overlaps, identify complementarities in funding, and effectively track the outcomes of projects funded by these agencies. These are the usual activities that any country’s research funding system should be able to support, but they have been missing in India for a very long time.

While this is a good move, many questions remain unanswered about the system. Technically, building a project management system is relatively straightforward, but it must incorporate a range of essential features for the system to function properly and to be used for the purpose for which it is being built – mapping the research funding landscape of India.

Furthermore, there has been very little discussion about the use of persistent identifiers (PIDs) and about what metadata must be captured: which agency gave the money, to which institution, to which researcher, what amount was granted, over what period, and in which research field. Quality metadata associated with grants is a must. Otherwise, what has been envisioned may not result in a genuinely usable system for understanding and mapping the research funding landscape of India.

There are examples from other countries that India could look into and benefit from, particularly from a design-principles perspective. For example, the UK’s Gateway to Research portal and the European Union’s Community Research and Development Information Service (CORDIS). They provide government- or publicly supported portals as a single point of entry for research funding information, and their systems make use of identifiers that are compatible with global standards such as Crossref, ROR, and ORCID – allowing analyses of funding landscapes based on grant data (rather than traditional bibliometric mapping).

One interesting question that emerges when reflecting on the quality and availability of metadata needed to map or track research funding flows is whether AI-supported solutions can capture metadata rather than relying entirely on manual input to populate metadata fields. With advances in the capabilities of LLMs to analyze large volumes of text, identify entities and relationships, and recognize patterns, this may now be possible. Could AI be used to extract and organize information from funding instruments, grant descriptions, project reports, publications, and other available sources?  For a large, complex, and diverse research system like India, such solutions could potentially work much better than relying entirely on the human resources of funding agencies to do this job. Funding agencies are already dealing with too many responsibilities, and asking them to manually create and maintain high-quality metadata for every project may not be realistic.

As the ongoing discussion in India suggests, strengthening research systems in the Global South requires a better understanding of the purposes of R&D funding, how those purposes are articulated into funding instruments, then translated into grants, and finally whether they lead (or not) to the expected outcomes. To achieve such understanding, detailed tracking of R&D funding is essential.

Photo by Micheile Henderson on Unsplash
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