The First Latin America Workshop on Data Science (LADaS 2018)
A VLDB 2018 workshop
August 27, 2018
Rio de Janeiro, Brazil


Dealing with the data deluge produced nowadays in different areas, ranging from basic sciences to billions of users of Global Internet services, emerges as one of the major challenges of our digital society. Presented as a multifaceted vector, this phenomenon has motivated several research initiatives. In science, Big Data has created new opportunities for investigation, motivating scientists, such as biologists, astronomers, biochemists, and researchers from other scientific areas, to face computational problems within the so-called “fourth paradigm” (data-intensive science). In industry, Big Data impacts the way predictive analysis/data analytics is conducted using powerful resources (clusters, clouds) while providing scalability and fault-tolerance. In the governance, there are opportunities to look into massive public databases to generate efficient planning as well as new services that may improve public services offered to citizens. In this context, the major challenge is to provide general methods for extracting relevant knowledge at big data scale. Data Science incorporates scientific methods, processes, and algorithms to extract knowledge from data in various forms. It builds upon techniques and theories from many fields in engineering and basic sciences. It is thus closely related to many traditional well-established disciplines but opens perspectives for a new highly-interdisciplinary area.

The goal of the 2018 Latin American Workshop on Data Science (LADaS 2018) is to provide a forum for scientists, engineers and researchers to discuss and exchange novel ideas, results, experiences, and work-in-progress on all aspects of Data Science.

The workshop intends to attract relevant contributions ranging from theoretical work to applications of Data Science in different areas of knowledge, including proposals involving new methodological artifacts in the area. Therefore, besides offering an opportunity for the Latin American community interested in Data Science to meet and attend VLDB, the workshop also proposes to act as a neutral ground for different Data Science research interests. It intends to provide a forum for networking among researchers whose primary interests are in methodological advancements with those interested in data-driven analysis applied to different fields of knowledge.

Regular articles should be at most eight (8) pages while short articles should be at most four (4) pages. Information guidelines for submitting papers is available at

Accepted papers will be published in the Online Proceedings for Scientific Conferences and Workshops ( At least one of the authors of an accepted paper must register and present the paper.

Topics of interest include, but are not limited to the following:

  • Data Management and Analytics
    • Data science theories and models
    • Big data algorithms and methods
    • Machine learning and deep learning
    • Data analytics
    • Data provenance
    • Fault tolerance, reliability, and availability
    • Security, privacy and trust management
    • Data-intensive computing
    • Network science
    • Scientific data visualization
  • Applications
    • Data-driven applications in science, industry, and government, such as health, energy, astronomy, cybersecurity, transportation, agriculture, natural resources, and biodiversity.
    • Large-scale data processing, including data streams and data integration
    • Knowledge extraction from heterogeneous data sources

Important Dates
Full Paper Submission Due Date: June 1, 2018
Decision Notification (email): July 2, 2018
Camera-Ready Copy Due Date: July 12, 2018

Submission Link

Please submit your paper at


  • Artur Ziviani – LNCC
  • Carmem Hara – UFPR
  • Eduardo Ogasawara – CEFET/RJ
  • José Antônio de Macêdo – UFC
  • Patrick Valduriez – INRIA & LIRMM

Program Committee

  • Aidan Hogan – Universidad de Chile
  • Alejandro A. Vaisman – Instituto Tecnológico de Buenos Aires
  • Alex Vieira – UFJF
  • Aline Carneiro Viana – Inria
  • Ana Paula Appel – IBM Research
  • Anderson Soares – UFG
  • Anelise Munaretto – UTFPR
  • Antonio Tadeu Gomes – LNCC
  • Carlos Sarraute – Grandata Labs
  • Carlos Ordonez – University of Houston
  • Claudia Medeiros – UNICAMP
  • Daniel de Oliveira – UFF
  • Diego Arroyuelo – Universidad Técnica Federico Santa María
  • Eduardo Bezerra – CEFET/RJ
  • Humberto T. Marques-Neto – PUC Minas
  • Isabel Cruz – University of Illinois
  • Jonas Dias – Dell EMC
  • Jonice Oliveira – UFRJ
  • Jorge Poco Medina – San Pablo Catholic University
  • Juan L. Reutter – Pontificia Universidad Católica
  • Julio Cesar Duarte – IME
  • Karin Becker – UFRGS
  • Lorena Etcheverry – Universidad de la República
  • Loreto Bravo – Universidad del Desarrollo
  • Marcelo Mendoza – Universidad Técnica Federico Santa María
  • Márton Karsai – ENS LYON/Inria
  • Nadia Kozievitch – UTFPR
  • Rafaelli Coutinho – CEFET/RJ
  • Ricardo Torres – UNICAMP
  • Ronaldo Goldschmidt – IME
  • Sergio Lifschitz – PUC-Rio