Local Insights for Global Action: Mexico

February 22, 2021

At Iran Open Data, we have been working to make resources about open data and access to information available to open data advocates in Iran. The following blog post from Open Data Charter is one of the resources we have made available in Persian. This post originally appeared here.

Led by the National Digital Platform (PDN) of the Executive Secretariat of the National Anticorruption System (SESNA), the government mapped 27 datasets that are priority for their country, grouped in three categories: Public Health, Socio-political and Economic needs. One workshop per topic was held between October 27- 29.

Photo by Regina Victorica on Unsplash

Mexico’s learnings and highlights are summarised as follows:

For Public Health

  1. Data is necessary for action.
    Having inaccurate data regarding the number of COVID-19 cases prevents the authorities from making decisions and will in turn make any community feel helpless amidst a crisis.
  2. Data structures must be dynamic.
    Governments must think in terms of data structures that allow the dynamism of a pandemic. It is important to document the entire history of the evolution of each case of COVID-19 with panel data that considers the dimension of time.
  3. Data must be interoperable.
    Public health is closely related to socio-economic, and demographic variables. COVID-19 is also complicated by co-morbidities such as obesity and diabetes, as well as by economic, age and socio-economic conditions. You have to think about how to structure and open your data in such a way that it can be analysed in conjunction with various databases.

For Socio-political contexts

  1. Identify the community’s most vulnerable groups and handle all data responsibly.
    Collecting data that can show the effects of the pandemic according to gender, race and social class is a challenge, but necessary. The pandemic would have affected vulnerable groups the most (and in different ways) and it is crucial to ensure that the variables used to identify these vulnerable groups and the data collected are handled responsibly.
  2. Identify the data users and be aware of their data skills.
    It is also important to think about the people who might use the data. The interests of each person in the citizenry can be very diverse. There is a great variation in the abilities to work with data and being upfront about the community’s data capabilities are important.
  3. For better or worse, the backdrop of all of this is still, climate change.
    It is necessary to look at all this data with regard to the environment and climate change. Pandemics and new diseases are largely explained by how human activity shapes the environment. In addition, data referring to the environment could benefit other phenomena such as natural disasters. It is worth doing an iteration of the data mapping to identify environmental data relevant to pandemics.

For the Economy

  1. Prioritise the data that will benefit a greater population.
    Economic activities at various levels have been deeply and differently affected by the pandemic and have negatively altered the production chains. Other economic activities (e.g. shopping or dining at restaurants), have been impeded by health measures to slow or stop infections. Likewise, the deterioration of the population’s health reduces the workforce. Mexico learned that it is necessary to prioritise what data is needed to provide the greatest benefit and could allow citizens to make decisions.
  2. Identify the most vulnerable and support them.
    Data on employment are among the most important for making decisions at different levels. In this way, one could identify which people have been most affected and how to support them. Furthermore, having disaggregated data on employment would make it possible to understand which sectors of the economy need more stimulus.
  3. Potential of data to mitigate future risks.
    The participants recognised that there is great potential in the mining of data of individual banking operations: withdrawals, deposits, loans, amounts, remittances by financial institution for example. These reveal how the pandemic has impacted people’s behavior and could help to mitigate risks. However, there are reasonable privacy concerns that must be considered.

A screen capture of one of Mexico‘s COVID-19 meet-ups.

The three meet-ups were recorded and can be viewed here.
The complete list of prioritized datasets is available in this AirTable.