By Stefaan G. Verhulst and Andrew Young from The GovLab[message_box title=”” color=”blue”]
This is part two of a two-part series on the impacts of open data in developing economies, including Latin American and Caribbean nations. Part one is available here.[/message_box]
As we mentioned on the previous post, The GovLab report “Open Data in Developing Economies: Toward Building an Evidence Base on What Works and How,” seeks to increase our understanding of the specific benefits of open data for countries with lower incomes, the impacts of open data on development processes, and above all, to understand what conditions can help create positive impacts.
To inform the deliberations at ConDatos – which takes place in Costa Rica this week- we seek to feature three projects we investigated- two in Latin America, Colombia and Paraguay, and one in the Caribbean, Jamaica, and reflect on how open data was a new asset for development. We draw upon the newly developed Periodic Table of Open Data to analyze what elements made a difference in creating these impacts.
1 Managing Climate in Colombia
The Aclímate Colombia project is a cross-sector partnership led by the International Center for Tropical Agriculture (CIAT). Its platform leverages a diversity of data sources, including many open government datasets, to help farmers understand how to better navigate shifting weather patterns. It has already had a tangible impact on the community, and received widespread recognition about how cross-sector data-sharing can translate data science insights into concrete, actionable information.
Particularly in developing economies where resources can be in short supply, a clear, detailed understanding of the problem to be addressed can help ensure targeted efforts. Aclímate Colombia’s user research (U) was laser-focused on the needs of smallholder rice farmers, ensuring that open data used in the platform was optimized for their needs. Through the use of data audits and inventory (Da), practitioners were able to explore the availability of datasets – both in the form of open government data and from other potentially useful and relevant data sources like NGOs and the private sector. For Aclímate Colombia, researchers identified the types of data needed for agriculture algorithms, and then engaged with the semi-public industry groups to make the data available.
Although open data is meant to provide value to data users without direct data-holder engagement, partnering with entities on the supply side (including government partnerships) can help fill data gaps and enable higher-impact data use. Aclímate Colombia is a strong example of the potential impacts that such partnerships can bring. The effort to provide farmers with climate-resilient crop-planting methods, would not be possible without the collaboration of a civil society organization (the driver of the initiative), government data holders (Dh), and semi-private agriculture industry domain experts (De) that served as intermediaries (I). These collaborators worked in partnership to get Aclímate Colombia’s tools into the hands of the smallholder farmers who needed access to the data.
2 Dengue Prevention in Paraguay
The National Health Surveillance Department of Paraguay recently opened up data related to dengue morbidity. As a result, researchers at Facultad Politecnica-Universidad de Asunción are leveraging the data to create a data-driven early warning system that can detect dengue-fever outbreaks a week in advance (and improving), effective in any Paraguayan city or region that has available data on morbidity, climate and water.
The university researchers behind the dengue prevention effort is small and somewhat lacking in resource availability and sustainability (Rs) in comparison to some other open data initiatives led by businesses or NGOs. The team does, however, possess the skills and expertise (Se) needed to do more with less. The researchers’ work is also built around clearly defined performance metrics (M), with a focus on reaching new levels of predictive accuracy and extending the timeline between prediction and outbreak.
3 Boosting Tourism in Jamaica
To demonstrate the potential for increased tourism and the spread of its economic benefits, a community mapping project in Jamaica sought to combine open government data with crowdsourced mapping data to enable a more participatory development of the tourism sector. This Interactive Community Mapping (ICM) to Benefit Tourism initiative is currently providing early insight into how open data can impact one of Jamaica’s most prominent industries.
The ICM efforts focused on partnering with diverse volunteer collaborators (C) to help supplement existing open government data with new, useful crowdsourced information. But just as open data’s release is less impactful without demand-side implementers to act on it, a lack of responsiveness (R) – often characterized by a lack of commitment to take up data-driven insights within governing institutions – can limit the success of open data initiatives. The key next step for creating a major impact on the tourism industry in Jamaica will likely require responsiveness from tourism authorities to act upon the insights generated through the crowdsourcing- and open data-driven initiative.
Next: A Need for More Evidence on Impact and a Greater Understanding of Demand
To be clear, we are only just beginning to understand what works in practice in the realm of open data in developing countries. We hope that the premises we uncovered in our research can benefit the broader fields of research and practice to enable greater experiment with new approaches for creating and analyzing the impact of open data. It is only with further experimentation and evidence-gathering that we can develop a clear and effective understanding of if, when and how open data can improve people’s lives in Latin America, the Caribbean and beyond.
One particular need that we will seek to address together with the IADB involves identifying in a more granular manner the demand side of open data. To a large extent, the lack of broad transformation is the result of the lack of systematic knowledge about the diversity of open data users and how the demand for open data aligns (or is misaligned) with its supply. This lack of understanding is especially acute when moving beyond blanket global assessments. To move beyond the traditional, reductive user archetypes of transparency watchdogs and lone app developers, we need a greater understanding of who uses or would benefit from using open data and how.
As always, we would be delighted to hear your interest and/or suggestions on jointly developing such an open data demand assessment tool. (Contact email@example.com).