Interdisciplinary explorations for the scaling of experimental interventions

SEGRETIN, M.S.; LOPEZ ROSENFELD, MATÍAS; LIPINA, S.J.

Neuroscientific perspectives on poverty

International School on Mind, Brain and Education (Ettore Majorana Foundation and Center for Scientific Culture)

Lugar: Erice; Año: 2020; p. 310 - 330

When addressing a large amount of information available in digital form on different aspects of human development, one of the critical aspects to consider is how to organize this information in order to answer different questions from different social actors. In this context, visualizations are one of the tools available that contribute to this goal . The computer applications currently available for the development of visualizations allow one to quickly generate maps, charts, timelines, graphics, word clouds, and search interfaces, among others. Neighborhoods, cities, and states are settings in which different types of life events occur for different social groups, and it is precisely in such settings is where human development occurs and where social relationships are built. For example, maps have been a key instrument to identify and solve challenges in the areas of public health, economic development, and psychology. Some challenges for the design and implementation of these computational efforts in the study of human development are related to the fact that individual data do not necessarily provide information to answer questions that involve processes at different scales (e.g., inter-individual). Furthermore, since each data source contains its own set of errors and complexities, adequate statistical methods are required to integrate information from different sources. However, efforts have begun to produce promising results. The capacities that are being generated and used on the internet could contribute to improving these aspects. At the same time, these tools can create challenges that the scientific community must anticipate. First, new approaches are required to determine the best way to visualize scientific data. There are also discussions that propose to change the general principles of effective visualization to those of greater specificity for scientific use, such as discussions concerning the best way to combine statistical methods with visualizations. Other types of challenges are related to how to create, maintain, and analyze data for visualizations, which implies taking into account the quality of the information, as well as its potential biases and contextual relevance. While significant efforts have been made over the past two decades to address these challenges, further research is still needed to generate scalable solutions that can be dynamically and interactively adapted and updated in the context of the internet.