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12. – 17. November 2017, Dagstuhl Seminar 17461

Connecting Visualization and Data Management Research


Remco Chang (Tufts University – Medford, US)
Jean-Daniel Fekete (INRIA Saclay – Orsay, FR)
Juliana Freire (New York University, US)
Carlos E. Scheidegger (University of Arizona – Tucson, US)

Auskunft zu diesem Dagstuhl Seminar erteilt

Dagstuhl Service Team


Dagstuhl Report, Volume 7, Issue 11 Dagstuhl Report
Gemeinsame Dokumente
Programm des Dagstuhl Seminars [pdf]


What prevents analysts from acquiring wisdom from data sources? To use data, to better understand the world and act upon it, we need to understand both the computational and the human-centric aspects of data-intensive work. In this Dagstuhl Seminar, we sought to establish the foundations for the next generation of data management and visualization systems by bringing together these two largely independent communities. While exploratory data analysis (EDA) has been a pillar of data science for decades, maintaining interactivity during EDA has become difficult, as the data size and complexity continue to grow. Modern statistical systems often assume that all data need to fit into memory in order to support interactivity. However, when faced with a large amount of data, few techniques can support EDA fluidly. During this process, interactivity is critical: if each operation takes hours or even minutes to finish, analysts lose track of their thought process. Bad analyses cause bad interpretations, bad actions and bad policies.

As data scale and complexity increases, the novel solutions that will ultimately enable interactive, large-scale EDA will have to come from truly interdisciplinary and international work. Today, database systems can store and query massive amounts of data, including methods for distributed, streaming and approximate computation. Data mining techniques provide ways to discover unexpected patterns and to automate and scale well-defined analysis procedures. Recent systems research has looked at how to develop novel database systems architectures to support the iterative, optimization-oriented workloads of data-intensive algorithms. Of course, both the inputs and outputs of these systems are ultimately driven by people, in support of analysis tasks. The life-cycle of data involves an iterative, interactive process of determining which questions to ask, the data to analyze, appropriate features and models, and interpreting results. In order to achieve better analysis outcomes, data processing systems require improved interfaces that account for the strengths and limitations of human perception and cognition. Meanwhile, to keep up with the rising tide of data, interactive visualization tools need to integrate more techniques from databases and machine learning.

This Dagstuhl seminar brought together researchers from the two communities (visualization and databases) to establish a research agenda towards the development of next generation data management and interactive visualization systems. In a short amount of time, the two communities learned from each other, identified the strengths and weaknesses of the latest techniques from both fields, and together developed a "state of the art" report on the open challenges that require the collaboration of the two communities. This report documents the outcome of this collaborative effort by all the participants.

  Creative Commons BY 3.0 Unported license
  Remco Chang, Jean-Daniel Fekete, Juliana Freire, and Carlos E. Scheidegger




Bücher der Teilnehmer 

Buchausstellung im Erdgeschoss der Bibliothek

(nur in der Veranstaltungswoche).


In der Reihe Dagstuhl Reports werden alle Dagstuhl-Seminare und Dagstuhl-Perspektiven-Workshops dokumentiert. Die Organisatoren stellen zusammen mit dem Collector des Seminars einen Bericht zusammen, der die Beiträge der Autoren zusammenfasst und um eine Zusammenfassung ergänzt.


Download Übersichtsflyer (PDF).


Es besteht weiterhin die Möglichkeit, eine umfassende Kollektion begutachteter Arbeiten in der Reihe Dagstuhl Follow-Ups zu publizieren.

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Seminar Homepage : Letzte Änderung 23.04.2018, 17:21 Uhr