Pontificia Universidad Católica de Chile Pontificia Universidad Católica de Chile
Arenas M., Barceló P. (2020)

Chile’s New Interdisciplinary Institute for Foundational Research on Data

Revista : Communications of the ACM
Volumen : 63
Número : 11
Páginas : 78-83
Tipo de publicación : ISI Ir a publicación


applications to tackling diverse issues
ranging from scientific challenges to
complex social problems.
As tasks of this kind are interdisciplinary by nature, IMFD gathers
a large number of researchers in
several areas that include traditional
computer science areas such as data
management, Web science, algorithms and data structures, privacy
and verification, information retrieval, data mining, machine learning,
and knowledge representation, as
well as some areas from other fields,
including statistics, political science,
and communication studies. IMFD
currently hosts 36 researchers, seven
postdoctoral fellows, and more than
100 students.
We at IMFD are convinced the
development of a science of data
requires producing a virtuous
amalgamation of all the aforementioned areas, in order to cope with
ever-increasing societal demands
for taking full advantage of available
information. A dramatic example
of such needs has been given to
humanity by the current COVID-19
pandemic, but there are clearly many
others. At IMFD, we are carrying out
several projects that aim to produce
such interdisciplinary crossings.
More importantly, we have worked to
develop a common research agenda
for the Institute, integrating the
efforts of its members into interdisciplinary teams whose goal is solving
some fundamental problems in data
science. Specifically, the research
agenda of IMFD has been organized
into five long-term and transversal
emblematic research projects, each
of which requires input from several,
if not all, the research areas mentioned previously. These emblematic
projects are:
? Data for the study of complex social
problems. This project seeks to encourage the combination of methodological strategies and techniques based on
data analysis to develop novel diagnoses about relevant socio-political