LADaS 2018 Workshop

The LADaS 2018 Workshop (Latin America Data Science Workshop) was organized in conjunction with the VLDB 2018 (Very Large Data Bases) at Rio de Janeiro on August 27th.

Scope: 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.


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

Technical Program Committee Chair:

  • Eduardo Ogasawara – CEFET/RJ
About Eduardo Ogasawara
I am a Professor of the Computer Science Department of the Federal Center for Technological Education of Rio de Janeiro (CEFET / RJ) since 2010. I hold a PhD in Systems Engineering and Computer Science at COPPE / UFRJ. Between 2000 and 2007 I worked in the Information Technology (IT) field where I acquired extensive experience in workflows and project management. I have solid background in the Databases and my primary interest is Data Science. He currently studies space-time series, parallel and distributed processing, and data preprocessing methods. I am a member of the IEEE, ACM, INNS, and SBC. Throughout my career I have been presenting consistent number of published articles and projects approved by the funding agencies, such as CNPq and FAPERJ. I am also reviewer of several international journals, such as VLDB Journal, IEEE Transactions on Service Computing and The Journal of Systems and Software. Currently, I am heading the Post-Graduate Program in Computer Science (PPCIC) of CEFET / RJ.

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