Inquiries to Eric Vance, Head of the Laboratory for Statistical Analysis Interdisciplinary (LISA) - 2020 Network
In an effort to enhance data-driven innovation in developing countries, the LISA 2020 Network has been established. This network aims to create a vibrant and strong community by the fourth World Statistics Day in 2025, with a potential expansion to all countries.
The primary focus of the LISA 2020 Network is to enable granular spatial data analysis, revealing localized patterns and clusters that are crucial in addressing socio-economic, health, and infrastructure challenges. This is achieved through the use of Local Indicators of Spatial Association (LISA) methods, which help map and identify significant spatial clusters such as disease hotspots, economic development areas, and regions with poor access to services. These insights can directly guide targeted policy and innovation strategies on the ground.
By offering policymakers and stakeholders detailed spatial insights tailored to local realities, rather than relying solely on generic or global innovation metrics, the LISA 2020 Network helps developing countries, including those in Africa, more effectively measure, understand, and address their unique innovation and development challenges. This approach overcomes limitations of traditional innovation indicators that often do not reflect informal, locally adapted innovation prevalent in poorer regions.
The network also aims to advance spatial data infrastructure and analytical capacities to help countries develop and institutionalise new, context-appropriate metrics for innovation and socio-economic development. It facilitates collaboration across countries and sectors to share data, methodologies, and best practices. Additionally, it supports policies that empower marginalized populations, create jobs, and build resilience to climate and economic shocks.
The LISA 2020 Network also seeks to expand the application of spatial data analytics in diverse areas such as health, transport accessibility, gender equity in mobility, and economic development to inform more equitable and sustainable interventions.
Moreover, stat labs within the LISA 2020 Network can serve as mentors for new labs in Europe or North America, and as "leapfrog" innovations to help countries catch up and raise data innovation levels. Students working in stat labs can learn to solve locally relevant problems through projects and mentoring from across the network.
The network also aims to strengthen and sustain each stat lab by enhancing education and training, particularly in statistical computing and collaboration with domain experts. However, a main challenge to improving global data access is the lack of equal access to quality education and training in mathematics, statistics, and computing.
Lastly, everyone involved with data-driven innovation should consider both the positive impacts and potential harm of their work. Collaboration with expert statisticians and data scientists can benefit everyone, not just developing countries.
- The LISA 2020 Network's objective is data-driven innovation, aiming to foster a strong community by World Statistics Day 2025, potentially expanding to all countries.
- The network utilizes Local Indicators of Spatial Association (LISA) methods to analyze granular spatial data, identifying local patterns and clusters, crucial for addressing socio-economic, health, and infrastructure challenges.
- By providing policymakers with detailed spatial insights, the LISA 2020 Network empowers developing countries, including African nations, to more effectively measure, understand, and address unique innovation and development challenges.
- The network also seeks to advance spatial data infrastructure, aid in the development of context-appropriate innovation and socio-economic development metrics, and facilitate collaboration across countries and sectors.
- The network applies spatial data analytics to diverse fields such as health, transport, gender equity, and economic development, aiming to inform equitable and sustainable interventions.
- Stat labs within the LISA 2020 Network serve multiple purposes, including mentoring new labs in Europe or North America, and developing as "leapfrog" innovations to improve data innovation levels in other countries.
- Improving global data access faces a challenge: the lack of equal access to quality education and training in mathematics, statistics, and computing, which should be addressed in collaboration with experts to consider both the positive impacts and potential harm of data-driven work.
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