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Documents authored by Fekete, Jean-Daniel

Document
DOI: 10.4230/DagRep.8.11.35
Provenance and Logging for Sense Making (Dagstuhl Seminar 18462)

Authors: Jean-Daniel Fekete, T. J. Jankun-Kelly, Melanie Tory, and Kai Xu

Published in: Dagstuhl Reports, Volume 8, Issue 11 (2019)

Abstract
Sense making is one of the biggest challenges in data analysis faced by both the industry and the research community. It involves understanding the data and uncovering its model, generating a hypothesis, selecting analysis methods, creating novel solutions, designing evaluation, and also critical thinking and learning wherever needed. The research and development for such sense making tasks lags far behind the fast-changing user needs, such as those that emerged recently as the result of so-called "Big Data". As a result, sense making is often performed manually and the limited human cognition capability becomes the bottleneck of sense making in data analysis and decision making. One of the recent advances in sense making research is the capture, visualization, and analysis of provenance information. Provenance is the history and context of sense making, including the data/analysis used and the users' critical thinking process. It has been shown that provenance can effectively support many sense making tasks. For instance, provenance can provide an overview of what has been examined and reveal gaps like unexplored information or solution possibilities. Besides, provenance can support collaborative sense making and communication by sharing the rich context of the sense making process. Besides data analysis and decision making, provenance has been studied in many other fields, sometimes under different names, for different types of sense making. For example, the Human-Computer Interaction community relies on the analysis of logging to understand user behaviors and intentions; the WWW and database community has been working on data lineage to understand uncertainty and trustworthiness; and finally, reproducible science heavily relies on provenance to improve the reliability and efficiency of scientific research. This Dagstuhl Seminar brought together researchers from the diverse fields that relate to provenance and sense making to foster cross-community collaboration. Shared challenges were identified and progress has been made towards developing novel solutions.
Cite as

Jean-Daniel Fekete, T. J. Jankun-Kelly, Melanie Tory, and Kai Xu. Provenance and Logging for Sense Making (Dagstuhl Seminar 18462). In Dagstuhl Reports, Volume 8, Issue 11, pp. 35-62, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@Article{fekete_et_al:DagRep.8.11.35,
  author =	{Fekete, Jean-Daniel and Jankun-Kelly, T. J. and Tory, Melanie and Xu, Kai},
  title =	{{Provenance and Logging for Sense Making (Dagstuhl Seminar 18462)}},
  pages =	{35--62},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{11},
  editor =	{Fekete, Jean-Daniel and Jankun-Kelly, T. J. and Tory, Melanie and Xu, Kai},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.8.11.35},
  URN =		{urn:nbn:de:0030-drops-103554},
  doi =		{10.4230/DagRep.8.11.35},
  annote =	{Keywords: Logging, Provenance, Sensemaking, Visualization}
}
Document
DOI: 10.4230/DagRep.8.10.1
Progressive Data Analysis and Visualization (Dagstuhl Seminar 18411)

Authors: Jean-Daniel Fekete, Danyel Fisher, Arnab Nandi, and Michael Sedlmair

Published in: Dagstuhl Reports, Volume 8, Issue 10 (2019)

Abstract
We live in an era where data is abundant and growing rapidly; databases storing big data sprawl past memory and computation limits, and across distributed systems. New hardware and software systems have been built to sustain this growth in terms of storage management and predictive computation. However, these infrastructures, while good for data at scale, do not well support exploratory data analysis (EDA) as, for instance, commonly used in Visual Analytics. EDA allows human users to make sense of data with little or no known model on this data and is essential in many application domains, from network security and fraud detection to epidemiology and preventive medicine. Data exploration is done through an iterative loop where analysts interact with data through computations that return results, usually shown with visualizations, which in turn are interacted with by the analyst again. Due to human cognitive constraints, exploration needs highly responsive system response times: at 500 ms, users change their querying behavior; past five or ten seconds, users abandon tasks or lose attention. As datasets grow and computations become more complex, response time suffers. To address this problem, a new computation paradigm has emerged in the last decade under several names: online aggregation in the database community; progressive, incremental, or iterative visualization in other communities. It consists of splitting long computations into a series of approximate results improving with time; in this process, partial or approximate results are then rapidly returned to the user and can be interacted with in a fluent and iterative fashion. With the increasing growth in data, such progressive data analysis approaches will become one of the leading paradigms for data exploration systems, but it also will require major changes in the algorithms, data structures, and visualization tools. This Dagstuhl Seminar was set out to discuss and address these challenges, by bringing together researchers from the different involved research communities: database, visualization, and machine learning. Thus far, these communities have often been divided by a gap hindering joint efforts in dealing with forthcoming challenges in progressive data analysis and visualization. The seminar gave a platform for these researchers and practitioners to exchange their ideas, experience, and visions, jointly develop strategies to deal with challenges, and create a deeper awareness of the implications of this paradigm shift. The implications are technical, but also human--both perceptual and cognitive--and the seminar provided a holistic view of the problem by gathering specialists from all the communities.
Cite as

Jean-Daniel Fekete, Danyel Fisher, Arnab Nandi, and Michael Sedlmair. Progressive Data Analysis and Visualization (Dagstuhl Seminar 18411). In Dagstuhl Reports, Volume 8, Issue 10, pp. 1-40, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@Article{fekete_et_al:DagRep.8.10.1,
  author =	{Fekete, Jean-Daniel and Fisher, Danyel and Nandi, Arnab and Sedlmair, Michael},
  title =	{{Progressive Data Analysis and Visualization (Dagstuhl Seminar 18411)}},
  pages =	{1--40},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{8},
  number =	{10},
  editor =	{Fekete, Jean-Daniel and Fisher, Danyel and Nandi, Arnab and Sedlmair, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.8.10.1},
  URN =		{urn:nbn:de:0030-drops-103464},
  doi =		{10.4230/DagRep.8.10.1},
  annote =	{Keywords: Approximate Query Processing, Online Aggregation, Exploratory Data Analysis, Visual Analytics, Progressive Data Analysis, Scalability}
}
Document
DOI: 10.4230/DagRep.7.11.46
Connecting Visualization and Data Management Research (Dagstuhl Seminar 17461)

Authors: Remco Chang, Jean-Daniel Fekete, Juliana Freire, and Carlos E. Scheidegger

Published in: Dagstuhl Reports, Volume 7, Issue 11 (2018)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 17461 "Connecting Visualization and Data Management Research".
Cite as

Remco Chang, Jean-Daniel Fekete, Juliana Freire, and Carlos E. Scheidegger. Connecting Visualization and Data Management Research (Dagstuhl Seminar 17461). In Dagstuhl Reports, Volume 7, Issue 11, pp. 46-58, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@Article{chang_et_al:DagRep.7.11.46,
  author =	{Chang, Remco and Fekete, Jean-Daniel and Freire, Juliana and Scheidegger, Carlos E.},
  title =	{{Connecting Visualization and Data Management Research (Dagstuhl Seminar 17461)}},
  pages =	{46--58},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2018},
  volume =	{7},
  number =	{11},
  editor =	{Chang, Remco and Fekete, Jean-Daniel and Freire, Juliana and Scheidegger, Carlos E.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.11.46},
  URN =		{urn:nbn:de:0030-drops-86708},
  doi =		{10.4230/DagRep.7.11.46},
  annote =	{Keywords: Interactive data analysis, Data visualization, Visual analytics, Data management system, Systems for data science}
}
Document
DOI: 10.4230/DagSemProc.07221.1
07221 Abstracts Collection – Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation

Authors: Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North

Published in: Dagstuhl Seminar Proceedings, Volume 7221, Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation (2007)

Abstract
From 28.05.07 to 01.06.07, the Dagstuhl Seminar 07221 ``Information Visualization – Human-Centered Issues in Visual Representation, Interaction, and Evaluation'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North. 07221 Abstracts Collection – Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation. In Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation. Dagstuhl Seminar Proceedings, Volume 7221, pp. 1-14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{kerren_et_al:DagSemProc.07221.1,
  author =	{Kerren, Andreas and Stasko, John T. and Fekete, Jean-Daniel and North, Chris},
  title =	{{07221 Abstracts Collection – Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation}},
  booktitle =	{Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation},
  pages =	{1--14},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7221},
  editor =	{Jean-Daniel Fekete and Andreas Kerren and Chris North and John T. Stasko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.07221.1},
  URN =		{urn:nbn:de:0030-drops-11367},
  doi =		{10.4230/DagSemProc.07221.1},
  annote =	{Keywords: Information Visualization, Visualization, Human-centered Aspects, Evaluation, Visual Analytics, Interaction, Exploration, Human-Computer Interaction}
}
Document
DOI: 10.4230/DagSemProc.07221.2
07221 Executive Summary - Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation

Authors: Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North

Published in: Dagstuhl Seminar Proceedings, Volume 7221, Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation (2007)

Abstract
Information Visualization (InfoVis) focuses on the use of visualization techniques to help people understand and analyze data. While related fields such as Scientific Visualization involve the presentation of data that has some physical or geometric correspondence, Information Visualization centers on abstract information without such correspondences. One important aim of this seminar was to bring together theoreticians and practitioners from Information Visualization and related fields as well as from application areas. The seminar has allowed a critical reflection on actual research efforts, the state of field, evaluation challenges, etc. This document summarizes the event.
Cite as

Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North. 07221 Executive Summary - Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation. In Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation. Dagstuhl Seminar Proceedings, Volume 7221, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{kerren_et_al:DagSemProc.07221.2,
  author =	{Kerren, Andreas and Stasko, John T. and Fekete, Jean-Daniel and North, Chris},
  title =	{{07221 Executive Summary - Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation}},
  booktitle =	{Information Visualization - Human-Centered Issues in Visual Representation, Interaction, and Evaluation},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7221},
  editor =	{Jean-Daniel Fekete and Andreas Kerren and Chris North and John T. Stasko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.07221.2},
  URN =		{urn:nbn:de:0030-drops-11356},
  doi =		{10.4230/DagSemProc.07221.2},
  annote =	{Keywords: Information Visualization, Visualization, Human-centered Aspects, Evaluation, Visual Analytics, Interaction, Exploration, Human-Computer Interaction}
}
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