Nikos Bikakis
2018-11-30 15:55:44 UTC
Call for Papers
BigVis 2019 :: 2nd International Workshop on Big Data Visual Exploration and Analytics
https://bigvis.imsi.athenarc.gr/bigvis2019
EDBT/ICDT 2019, March 26, 2019, Lisbon, Portugal
Held in conjunction with the 22nd Intl. Conference on Extending Database Technology & 22nd Intl. Conference on Database Theory (EDBT/ICDT 2019)
In the Big Data era, the growing availability of a variety of massive datasets presents challenges and opportunities to not only corporate data analysts but also others, such as research scientists, data journalists, policy makers, SMEs, and individual data enthusiasts datasets are typically: accessible in a raw format that are not being loaded or indexed in a database (e.g., plain text, json, rdf), dynamic, dirty and heterogeneous in nature. The level of difficulty in transforming a data-curious user into someone who can access and analyze that data is even more burdensome now for a great number of users with little or no support and expertise on the data processing part. The purpose of visual data exploration is to facilitate information perception and manipulation, knowledge extraction and inference by non-expert users. Interactive visualization, used in a variety of modern systems, provides users with intuitive means to interpret and explore the content of the data, iden!
tify interesting patterns, infer correlations and causalities, and supports sense-making activities that are not always possible with traditional data analysis techniques.
In the Big Data era, several challenges arise in the field of data visualization and analytics. First, the modern exploration and visualization systems should offer scalable data management techniques in order to efficiently handle billion objects datasets, limiting the system response in a few milliseconds. Besides, nowadays systems must address the challenge of on-the-fly scalable visualizations over large and dynamic sets of volatile raw data, offering efficient interactive exploration techniques, as well as mechanisms for information abstraction, sampling and summarization for addressing problems related to visual information overplotting. Further, they must encourage user comprehension offering customization capabilities to different user-defined exploration scenarios and preferences according to the analysis needs. Overall, the challenge is to enable users to gain value and insights out of the data as rapidly as possible, minimizing the role of IT-expert in the loop.
The BigVis workshop aims at addressing the above challenges and issues by providing a forum for researchers and practitioners to discuss exchange and disseminate their work. BigVis attempts to attract attention from the research areas of Data Management & Mining, Information Visualization and Human-Computer Interaction and highlight novel works that bridge together these communities.
Workshop Topics
-------------------------------
In the context of visual exploration and analytics, topics of interest include, but are not limited to:
- Visualization and exploration techniques for various Big Data types (e.g., stream, spatial, high-dimensional, graph)
- Human-centered database techniques
- Indexes and data structures for data visualization
- In situ visual exploration and analytics
- Progressive visual analytics
- Interactive caching and prefetching
- Scalable visual operations (e.g., zooming, panning, linking, brushing)
- Big Data visual representation techniques (e.g., aggregation, sampling, multi-level, filtering)
- Setting-oriented visualization (e.g., display resolution/size, smart phones, pixel-oriented, visualization over networks)
- User-oriented visualization (e.g., assistance, personalization, recommendation)
- Visual analytics (e.g., pattern matching, timeseries analytics, prediction analysis, outlier detection, OLAP)
- Immersive visualization and visual analytics
- Visual and interactive data mining
- Models of human-in-the-loop data analysis
- High performance/Parallel techniques
- Visualization hardware and acceleration techniques
- Linked Data and ontologies visualization
- Case and user studies
- Systems and tools
Submissions
-------------------------------
- regular research papers (up to 8 pages)
- work-in-progress papers (up to 4 pages)
- vision papers (up to 4 pages)
- system papers and demos (up to 4 pages)
Important Dates
-------------------------------
Submission: January 4, 2019
Notification: January 22, 2019
Camera-ready: January 29, 2019
Deadlines expire at 5pm PT
Workshop: March 26, 2019
Organizing Committee
-------------------------------
Nikos Bikakis, University of Ioannina, Greece
Kwan-Liu Ma, University of California-Davis, USA
Olga Papaemmanouil, Brandeis University, USA
George Papastefanatos, ATHENA Research Center, Greece
Special Issue
-------------------------------
Extended versions of the best papers of BigVis 2019 will be invited for submission in a special issue of an international journal. (confirmation awaiting)
Program Committee
-------------------------------
James Abello, Rutgers University, USA
Demosthenes Akoumianakis, Techn Instit of Crete, Greece
Gennady Andrienko, Fraunhofer, Germany
Manos Athanassoulis, Harvard, USA
Leilani Battle, University of Maryland, USA
Carsten Binnig, Brown University, UK
Nan Cao, Tongji University, China
Maria Beatriz Carmo, Universidade de Lisboa, Portugal
Giorgio Caviglia, Trifacta Inc
Wei Chen, Zhejiang University, China
Rick Cole, Tableau
Alfredo Cuzzocrea, University of Trieste, Italy
Aba-Sah Dadzie, The Open University, UK
Issei Fujishiro, Keio University, Japan
Giorgos Giannopoulos, ATHENA Research Center, Greece
Parke Godfrey, University of York, Canada
Daniel Goncalves, University of Montpellier, France
Michael Gubanov, University of Texas at San Antonio, USA
Marcel Hlawatsch, University of Stuttgart, Germany
Yifan Hu, Yahoo!
Christophe Hurter, ENAC, France
Eser Kandogan, IBM
Anastasios Kementsietsidis, Google
James Klosowski, AT&T Research
Stephen G. Kobourov, University of Arizona, USA
Georgia Koutrika, ATHENA Research Center, Greece
Giuseppe Liotta, University of Perugia, Italy
Guoliang Li, Tsinghua University, China
Zhicheng Liu, Adobe
Steffen Lohmann, Fraunhofer, Germany
Marios Meimaris, ATHENA Research Center, Greece
Davide Mottin, Hasso Plattner Institute, Germany
Martin Nöllenburg, Vienna University of Technology, Austria
Chris North, Virginia Tech, USA
Paul Parsons, Purdue University, USA
Neoklis Polyzotis, Google
Gerik Scheuermann, University of Leipzig, Germany
Tobias Schreck, Graz University of Technology, Austria
Thibault Sellam, Columbia University, USA
Mike Sips, GFZ, Germany
Dimitrios Skoutas, ATHENA Research Center, Greece
Kostas Stefanidis, University of Tampere, Finland
Cagatay Turkay, City University London, UK
Yannis Tzitzikas, University of Crete, Greece
Panos Vassiliadis, University of Ioannina, Greece
Chaoli Wang, University of Notre Dame, USA
Kai Xu, Middlesex University, UK
Hongfeng Yu, University of Nebraska-Lincoln, USA
_______________________________________________
Please do not post msgs that are not relevant to the database community at large. Go to www.cs.wisc.edu/dbworld for guidelines and posting forms.
To unsubscribe, go to https://lists.cs.wisc.edu/mailman/listinfo/dbworld
BigVis 2019 :: 2nd International Workshop on Big Data Visual Exploration and Analytics
https://bigvis.imsi.athenarc.gr/bigvis2019
EDBT/ICDT 2019, March 26, 2019, Lisbon, Portugal
Held in conjunction with the 22nd Intl. Conference on Extending Database Technology & 22nd Intl. Conference on Database Theory (EDBT/ICDT 2019)
In the Big Data era, the growing availability of a variety of massive datasets presents challenges and opportunities to not only corporate data analysts but also others, such as research scientists, data journalists, policy makers, SMEs, and individual data enthusiasts datasets are typically: accessible in a raw format that are not being loaded or indexed in a database (e.g., plain text, json, rdf), dynamic, dirty and heterogeneous in nature. The level of difficulty in transforming a data-curious user into someone who can access and analyze that data is even more burdensome now for a great number of users with little or no support and expertise on the data processing part. The purpose of visual data exploration is to facilitate information perception and manipulation, knowledge extraction and inference by non-expert users. Interactive visualization, used in a variety of modern systems, provides users with intuitive means to interpret and explore the content of the data, iden!
tify interesting patterns, infer correlations and causalities, and supports sense-making activities that are not always possible with traditional data analysis techniques.
In the Big Data era, several challenges arise in the field of data visualization and analytics. First, the modern exploration and visualization systems should offer scalable data management techniques in order to efficiently handle billion objects datasets, limiting the system response in a few milliseconds. Besides, nowadays systems must address the challenge of on-the-fly scalable visualizations over large and dynamic sets of volatile raw data, offering efficient interactive exploration techniques, as well as mechanisms for information abstraction, sampling and summarization for addressing problems related to visual information overplotting. Further, they must encourage user comprehension offering customization capabilities to different user-defined exploration scenarios and preferences according to the analysis needs. Overall, the challenge is to enable users to gain value and insights out of the data as rapidly as possible, minimizing the role of IT-expert in the loop.
The BigVis workshop aims at addressing the above challenges and issues by providing a forum for researchers and practitioners to discuss exchange and disseminate their work. BigVis attempts to attract attention from the research areas of Data Management & Mining, Information Visualization and Human-Computer Interaction and highlight novel works that bridge together these communities.
Workshop Topics
-------------------------------
In the context of visual exploration and analytics, topics of interest include, but are not limited to:
- Visualization and exploration techniques for various Big Data types (e.g., stream, spatial, high-dimensional, graph)
- Human-centered database techniques
- Indexes and data structures for data visualization
- In situ visual exploration and analytics
- Progressive visual analytics
- Interactive caching and prefetching
- Scalable visual operations (e.g., zooming, panning, linking, brushing)
- Big Data visual representation techniques (e.g., aggregation, sampling, multi-level, filtering)
- Setting-oriented visualization (e.g., display resolution/size, smart phones, pixel-oriented, visualization over networks)
- User-oriented visualization (e.g., assistance, personalization, recommendation)
- Visual analytics (e.g., pattern matching, timeseries analytics, prediction analysis, outlier detection, OLAP)
- Immersive visualization and visual analytics
- Visual and interactive data mining
- Models of human-in-the-loop data analysis
- High performance/Parallel techniques
- Visualization hardware and acceleration techniques
- Linked Data and ontologies visualization
- Case and user studies
- Systems and tools
Submissions
-------------------------------
- regular research papers (up to 8 pages)
- work-in-progress papers (up to 4 pages)
- vision papers (up to 4 pages)
- system papers and demos (up to 4 pages)
Important Dates
-------------------------------
Submission: January 4, 2019
Notification: January 22, 2019
Camera-ready: January 29, 2019
Deadlines expire at 5pm PT
Workshop: March 26, 2019
Organizing Committee
-------------------------------
Nikos Bikakis, University of Ioannina, Greece
Kwan-Liu Ma, University of California-Davis, USA
Olga Papaemmanouil, Brandeis University, USA
George Papastefanatos, ATHENA Research Center, Greece
Special Issue
-------------------------------
Extended versions of the best papers of BigVis 2019 will be invited for submission in a special issue of an international journal. (confirmation awaiting)
Program Committee
-------------------------------
James Abello, Rutgers University, USA
Demosthenes Akoumianakis, Techn Instit of Crete, Greece
Gennady Andrienko, Fraunhofer, Germany
Manos Athanassoulis, Harvard, USA
Leilani Battle, University of Maryland, USA
Carsten Binnig, Brown University, UK
Nan Cao, Tongji University, China
Maria Beatriz Carmo, Universidade de Lisboa, Portugal
Giorgio Caviglia, Trifacta Inc
Wei Chen, Zhejiang University, China
Rick Cole, Tableau
Alfredo Cuzzocrea, University of Trieste, Italy
Aba-Sah Dadzie, The Open University, UK
Issei Fujishiro, Keio University, Japan
Giorgos Giannopoulos, ATHENA Research Center, Greece
Parke Godfrey, University of York, Canada
Daniel Goncalves, University of Montpellier, France
Michael Gubanov, University of Texas at San Antonio, USA
Marcel Hlawatsch, University of Stuttgart, Germany
Yifan Hu, Yahoo!
Christophe Hurter, ENAC, France
Eser Kandogan, IBM
Anastasios Kementsietsidis, Google
James Klosowski, AT&T Research
Stephen G. Kobourov, University of Arizona, USA
Georgia Koutrika, ATHENA Research Center, Greece
Giuseppe Liotta, University of Perugia, Italy
Guoliang Li, Tsinghua University, China
Zhicheng Liu, Adobe
Steffen Lohmann, Fraunhofer, Germany
Marios Meimaris, ATHENA Research Center, Greece
Davide Mottin, Hasso Plattner Institute, Germany
Martin Nöllenburg, Vienna University of Technology, Austria
Chris North, Virginia Tech, USA
Paul Parsons, Purdue University, USA
Neoklis Polyzotis, Google
Gerik Scheuermann, University of Leipzig, Germany
Tobias Schreck, Graz University of Technology, Austria
Thibault Sellam, Columbia University, USA
Mike Sips, GFZ, Germany
Dimitrios Skoutas, ATHENA Research Center, Greece
Kostas Stefanidis, University of Tampere, Finland
Cagatay Turkay, City University London, UK
Yannis Tzitzikas, University of Crete, Greece
Panos Vassiliadis, University of Ioannina, Greece
Chaoli Wang, University of Notre Dame, USA
Kai Xu, Middlesex University, UK
Hongfeng Yu, University of Nebraska-Lincoln, USA
_______________________________________________
Please do not post msgs that are not relevant to the database community at large. Go to www.cs.wisc.edu/dbworld for guidelines and posting forms.
To unsubscribe, go to https://lists.cs.wisc.edu/mailman/listinfo/dbworld