InfoVis:Wiki - User contributions [en]

BigVis 2020

2019-10-17T19:22:44Z

Bikakis: Created page with "*'''Title''': 3rd International Workshop on Big Data Visual Exploration and Analytics *'''Date:''' March 30, 2020 *'''Location:''' Copenhagen, wik..."

*'''Title''': 3rd International Workshop on Big Data Visual Exploration and Analytics
*'''Date:''' March 30, 2020
*'''Location:''' [[wikipedia:Copenhagen|Copenhagen]], [[wikipedia:Denmark|Denmark]]
*'''Homepage:''' https://bigvis.imsi.athenarc.gr/bigvis2020
*'''Paper Submission Deadline:''' January 5, 2020

[[Category:Conferences]]

Template:Conferences

2019-10-17T19:20:47Z

Bikakis: bigvis entry

<h1 style="padding: 5px">Upcoming Events</h1>
[[Help:How_To_Enter_Events|How to enter events?]]
*'''[[GD 2019]]''': September 17-20, Prague, Czech Republic. '''27th International Symposium on Graph Drawing and Network Visualization'''
*'''[[VINCI2019]]''': September 20-22, Shanghai, China. '''12th International Symposium on Visual Information Communication and Interaction'''
*'''[[IEEE VIS 2019]]''': October 20-25, Vancouver, Canada. '''IEEE VIS 2019'''
*'''[[VISAP'19]]''': October 21-25, Vancouver, Canada. '''IEEE VIS Arts Program 2019'''
*'''[[IEEE AIVR'19]]''': December 9-11, San Diego, USA. '''IEEE Conference on Artificial Intelligence and Virtual Reality'''
*'''[[BigVis 2020]]''': March 30, Copenhagen, Denmark. '''3rd International Workshop on Big Data Visual Exploration and Analytics'''
*'''[[IEEE PACIFIC VIS 2020]]''': April 14-17, Tianjin, China. '''IEEE Pacific Visualization Symposium '''

[[Category:Conferences]]

2019-10-17: CFP: BigVis 2020 : 3rd International Workshop on Big Data Visual Exploration and Analytics, Copenhagen, Denmark

2019-10-17T19:15:39Z

Bikakis: Created page with " BigVis 2020 Call for Papers BigVis 2020 :: 3rd International Workshop on Big Data Visual Exploration and Analytics Home: https://bigvis.imsi.athenarc.gr..."

BigVis 2020 Call for Papers 

BigVis 2020 :: 3rd International Workshop on Big Data Visual Exploration and Analytics

Home: https://bigvis.imsi.athenarc.gr/bigvis2020 

Held in conjunction with the 23rd Intl. Conference on Extending Database Technology & 23rd Intl. Conference on Database Theory (EDBT/ICDT 2020)

Information Visualization is nowadays one of the cornerstones of Data Science, turning the abundance of Big Data being produced through modern systems into actionable knowledge. Indeed, the Big Data era has realized the availability of voluminous datasets that are dynamic, noisy and heterogeneous in nature. 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. Thus, the area of data visualization, visual exploration and analysis has gained great attention recently, calling for joint action from different research areas from the HCI, Computer graphics and Data management and mining communities.

In this respect, several traditional problems from these communities such as efficient data storage, querying & indexing for enabling visual analytics, new ways for visual presentation of massive data, efficient interaction and personalization techniques that can fit to different user needs are revisited. The modern exploration and visualization systems should nowadays offer scalable techniques to efficiently handle billion objects datasets, limiting the visual response in a few milliseconds along with 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 offer self-service visual analytics, i.e. enable data scientists and business analysts to visually 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, exploration & analytics techniques for various data types; e.g., stream, spatial, high-dimensional, graph
- Human-in-the-loop processing
- Human-centered databases
- Data modeling, storage, indexing, caching, prefetching & query processing for interactive applications
- Interactive machine learning
- Interactive data mining
- User-oriented visualization; e.g., recommendation, assistance, personalization
- Visualization & knowledge; e.g., storytelling
- Progressive analytics
- In-situ visual exploration & analytics
- Novel interface & interaction paradigms
- Visual representation techniques; e.g., aggregation, sampling, multi-level, filtering
- Scalable visual operations; e.g., zooming, panning, linking, brushing
- Scientific visualization; e.g., volume visualization
- Analytics in the fields of scholarly data, digital libraries, multimedia, scientific data, social data, etc.
- Immersive visualization
- Interactive computer graphics
- Setting-oriented visualization; e.g., display resolution/size, smart phones, visualization over networks
- High performance, distributed & parallel techniques
- Visualization hardware & acceleration techniques
- Linked Data & ontologies visualization
- Benchmarks for data visualization & analytics
- Case & user studies
- Systems & tools

Submissions
------------------------------------
Regular/Short Research papers [up to 8/4 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 5, 2020
Notification: January 24, 2020
Camera-ready: January 29, 2020
Workshop: March 30, 2020

Organizing Committee
------------------------------------
David Auber, University Bordeaux, France
Nikos Bikakis, University of Ioannina, Greece
Panos Chrysanthis, University of Pittsburgh, USA
George Papastefanatos, ATHENA Research Center, Greece
Mohamed Sharaf, United Arab Emirates University, UAE

Special Issue
------------------------------------
Extended versions of the best papers of BigVis 2020 will be invited for submission in a special issue of an international journal.

Program Committee
------------------------------------
James Abello, Rutgers Univ, USA
Gennady Andrienko, Fraunhofer, Germany
Rick Cole, Tableau
Alfredo Cuzzocrea, ICAR-CNR & Univ of Calabria, Italy
Danyel Fisher, Honeycomb.io
Steffen Frey, Univ of Stuttgart, Germany
Giorgos Giannopoulos, ATHENA Research Center, Greece
Parke Godfrey, Univ of York, Canada
Michael Gubanov, Univ of Texas at San Antonio, USA
Silu Huang, Microsoft
Christophe Hurter, Ecole Nationale de l’Aviation Civile, France
Eser Kandogan, IBM
James Klosowski, AT&T Research
Zhicheng Liu, Adobe
Steffen Lohmann, Fraunhofer, Germany
Ioana Manolescu, INRIA & Ecole Polytechnique, France
Marios Meimaris, ATHENA Research Center, Greece
Silvia Miksch, Vienna University of Technology, Austria
Davide Mottin, Hasso Plattner Institute, Germany
Martin Nöllenburg, Vienna Univ of Technology, Austria
Olga Papaemmanouil, Brandeis Univ, USA
Paul Parsons, Purdue Univ, USA
Laura Po, Unimore, Italy
Giuseppe Polese, University of Salerno, Italy
Alexander Rind, St. Pölten Univ of Applied Sciences, Austria
Gerik Scheuermann, Univ of Leipzig, Germany
Heidrun Schumann, Univ of Rostock, Germany
Michael Sedlmair, Univ of Stuttgart, Germany
Thibault Sellam, Columbia Univ, USA
Bettina Speckmann, Eindhoven Univ of Technology, Netherlands
Kostas Stefanidis, Univ of Tampere, Finland
Cagatay Turkay, Univ of Warwick, UK
Panos Vassiliadis, Univ of Ioannina, Greece
Junpeng Wang, Visa Research
Chaoli Wang, Univ of Notre Dame, USA
Panpan Xu, Bosch Research
Kai Xu, Middlesex Univ, UK
Hongfeng Yu, Univ of Nebraska-Lincoln, USA

[[Category: News]][[Category: 2019/10]]

Template:News

2019-10-17T19:14:26Z

Bikakis:

2019-10-17: CFP: CFP: BigVis 2020 : 3rd International Workshop on Big Data Visual Exploration and Analytics, Copenhagen, Denmark

2019-10-17T19:13:49Z

Bikakis:

2019-10-17: CFP: CFP: BigVis 2020 : 3rd International Workshop on Big Data Visual Exploration and Analytics, Copenhagen, Denmark

2019-10-17T19:12:41Z

Bikakis:

BigVis 2020 Call for Papers

BigVis 2020 :: 3rd International Workshop on Big Data Visual Exploration and Analytics

https://bigvis.imsi.athenarc.gr/bigvis2020

Held in conjunction with the 23rd Intl. Conference on Extending Database Technology & 23rd Intl. Conference on Database Theory (EDBT/ICDT 2020)

Information Visualization is nowadays one of the cornerstones of Data Science, turning the abundance of Big Data being produced through modern systems into actionable knowledge. Indeed, the Big Data era has realized the availability of voluminous datasets that are dynamic, noisy and heterogeneous in nature. 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. Thus, the area of data visualization, visual exploration and analysis has gained great attention recently, calling for joint action from different research areas from the HCI, Computer graphics and Data management and mining communities.

In this respect, several traditional problems from these communities such as efficient data storage, querying & indexing for enabling visual analytics, new ways for visual presentation of massive data, efficient interaction and personalization techniques that can fit to different user needs are revisited. The modern exploration and visualization systems should nowadays offer scalable techniques to efficiently handle billion objects datasets, limiting the visual response in a few milliseconds along with 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 offer self-service visual analytics, i.e. enable data scientists and business analysts to visually 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, exploration & analytics techniques for various data types; e.g., stream, spatial, high-dimensional, graph
- Human-in-the-loop processing
- Human-centered databases
- Data modeling, storage, indexing, caching, prefetching & query processing for interactive applications
- Interactive machine learning
- Interactive data mining
- User-oriented visualization; e.g., recommendation, assistance, personalization
- Visualization & knowledge; e.g., storytelling
- Progressive analytics
- In-situ visual exploration & analytics
- Novel interface & interaction paradigms
- Visual representation techniques; e.g., aggregation, sampling, multi-level, filtering
- Scalable visual operations; e.g., zooming, panning, linking, brushing
- Scientific visualization; e.g., volume visualization
- Analytics in the fields of scholarly data, digital libraries, multimedia, scientific data, social data, etc.
- Immersive visualization
- Interactive computer graphics
- Setting-oriented visualization; e.g., display resolution/size, smart phones, visualization over networks
- High performance, distributed & parallel techniques
- Visualization hardware & acceleration techniques
- Linked Data & ontologies visualization
- Benchmarks for data visualization & analytics
- Case & user studies
- Systems & tools

Submissions
------------------------------------
Regular/Short Research papers [up to 8/4 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 5, 2020
Notification: January 24, 2020
Camera-ready: January 29, 2020
Workshop: March 30, 2020

Organizing Committee
------------------------------------
David Auber, University Bordeaux, France
Nikos Bikakis, University of Ioannina, Greece
Panos Chrysanthis, University of Pittsburgh, USA
George Papastefanatos, ATHENA Research Center, Greece
Mohamed Sharaf, United Arab Emirates University, UAE

Special Issue
------------------------------------
Extended versions of the best papers of BigVis 2020 will be invited for submission in a special issue of an international journal.

Program Committee
------------------------------------
James Abello, Rutgers Univ, USA
Gennady Andrienko, Fraunhofer, Germany
Rick Cole, Tableau
Alfredo Cuzzocrea, ICAR-CNR & Univ of Calabria, Italy
Danyel Fisher, Honeycomb.io
Steffen Frey, Univ of Stuttgart, Germany
Giorgos Giannopoulos, ATHENA Research Center, Greece
Parke Godfrey, Univ of York, Canada
Michael Gubanov, Univ of Texas at San Antonio, USA
Silu Huang, Microsoft
Christophe Hurter, Ecole Nationale de l’Aviation Civile, France
Eser Kandogan, IBM
James Klosowski, AT&T Research
Zhicheng Liu, Adobe
Steffen Lohmann, Fraunhofer, Germany
Ioana Manolescu, INRIA & Ecole Polytechnique, France
Marios Meimaris, ATHENA Research Center, Greece
Silvia Miksch, Vienna University of Technology, Austria
Davide Mottin, Hasso Plattner Institute, Germany
Martin Nöllenburg, Vienna Univ of Technology, Austria
Olga Papaemmanouil, Brandeis Univ, USA
Paul Parsons, Purdue Univ, USA
Laura Po, Unimore, Italy
Giuseppe Polese, University of Salerno, Italy
Alexander Rind, St. Pölten Univ of Applied Sciences, Austria
Gerik Scheuermann, Univ of Leipzig, Germany
Heidrun Schumann, Univ of Rostock, Germany
Michael Sedlmair, Univ of Stuttgart, Germany
Thibault Sellam, Columbia Univ, USA
Bettina Speckmann, Eindhoven Univ of Technology, Netherlands
Kostas Stefanidis, Univ of Tampere, Finland
Cagatay Turkay, Univ of Warwick, UK
Panos Vassiliadis, Univ of Ioannina, Greece
Junpeng Wang, Visa Research
Chaoli Wang, Univ of Notre Dame, USA
Panpan Xu, Bosch Research
Kai Xu, Middlesex Univ, UK
Hongfeng Yu, Univ of Nebraska-Lincoln, USA

[[Category: News]][[Category: 2019/10]]

2019-10-17: CFP: CFP: BigVis 2020 : 3rd International Workshop on Big Data Visual Exploration and Analytics, Copenhagen, Denmark

2019-10-17T19:11:26Z

Bikakis: Created page with " BigVis 2020 Call for Papers BigVis 2020 :: 3rd International Workshop on Big Data Visual Exploration and Analytics https://bigvis.imsi.athenarc.gr/bigvis2020 He..."

Template:News

2019-10-17T19:06:02Z

Bikakis:

2018-09-29: CFP: BigVis 2019 :: 2nd International Workshop on Big Data Visual Exploration and Analytics

2018-09-29T12:43:54Z

Bikakis: Created page with "BigVis 2019 Call for Papers BigVis 2019 :: 2nd International Workshop on Big Data Visual Exploration and Analytics Home: https://bigvis.imsi.athenarc.gr/bigvis2019 Held in..."

BigVis 2019 Call for Papers

BigVis 2019 :: 2nd International Workshop on Big Data Visual Exploration and Analytics

Home: https://bigvis.imsi.athenarc.gr/bigvis2019

Held in conjunction with the 22nd Intl. Conference on Extending Database Technology & 22nd Intl. Conference on Database Theory (EDBT/ICDT 2019), Lisbon, Portugal

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, identify 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: December 30, 2018
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

Template:News

2018-09-29T12:39:41Z

Bikakis:

<h1 style="padding: 5px, margin-top: 0px !important">'''Latest News'''</h1>
[[Help:How_To_Enter_News|How to enter news?]]












*[[2018-09-29: CFP: BigVis 2019 :: 2nd International Workshop on Big Data Visual Exploration and Analytics]]
*[[2018-09-28: Award: CVAST submission earns 3rd place at GD 2018 contest]]
*[[2018-09-28: CFP: EuroVIS 2019 - Deadline (Abstract) Dec. 5, 2018]]
*[[2018-09-20: CFP: ACM Intelligent User Interfaces 2019 - Deadline Oct. 1, 2018]]
*[[2018-09-07: CFP: IEEE PacificVis 2019 - Deadline (Abstract) Sept. 28, 2018]]
*[[2018-09-01: CFPosters: 4th International Symposium on Big Data Visual and Immersive Analytics (BDVA 2018) - Deadline Sept. 9, 2018)]]
*[[2018-08-24: CFPosters: VIS Workshop on Visualization for Communication (VISCOMM 2018 - Deadline Sept. 3, 2018)]]
*[[2018-07-23: ACM Intelligent User Interfaces (IUI 2019): Call for tutorial proposals]]
*[[2018-07-19: CFPosters: 26th Int. Symposium on Graph Drawing and Network Visualisation 2018 (Abstract Deadline: August 12, 2018)]]
*[[2018-07-18: PhD, Post-Doc: 1 PhD and 1 Post-Doc Open Positions in Visual Analytics at TU Wien]]
*[[2018-07-18: CFP: IEEE Pacific Visualisation 2019 (Abstract Deadline: September 28, 2018)]]
*[[2018-07-17: CFP: ACM Intelligent User Interfaces - IUI 2019 ]]
*[[2018-07-17: DL Extension: DSIA 2018 Deadline Extended]]
*[[2018-07-16: DL Extension: VisGuides 2018 Deadline Extended]]
*[[2018-07-12: Job: Full-Time Faculty Position in Visualization, HCI at Sabanci University, Istanbul ]]
*[[2018-07-12: DL Extension: VizSec 2018 Deadline Extended]]
*[[2018-07-06: Post-Doc: 2 Immersive Technologies/Learning Post Doc Opportunities at Pennsylvania State University]]
*[[2018-07-04: CFP: IEEE VIS 2018 3rd Workshop on Data Systems for Interactive Analysis (DSIA)]]
*[[2018-06-27: CFP Deadline Extension: IEEE VIS 2018 Workshop on Machine Learning from User Interaction for Visualization and Analytics]]
*[[2018-06-25: CFW: IUI 2019 CALL FOR WORKSHOP PROPOSALS]]
*[[2018-06-21: CFP: International Symposium on Visual Information Communication and Interaction]]

[[:Category:News|'''News Archive...''']]

[https://infovis-wiki.net/w/index.php?title=Special:Newpages&namespace=104&feed=rss News as RSS feed]
 [[InfoVis:Wiki_RSS_Feeds|List of all available RSS feeds]]

BigVis 2019

2018-09-29T12:36:40Z

Bikakis: Created page with " *'''Title''': 2nd International Workshop on Big Data Visual Exploration and Analytics *'''Date:''' March 26, 2019 *'''Location:''' Lisbon, wikipedia..."

*'''Title''': 2nd International Workshop on Big Data Visual Exploration and Analytics
*'''Date:''' March 26, 2019
*'''Location:''' [[wikipedia:Lisbon|Lisbon]], [[wikipedia:Portugal|Portugal]]
*'''Homepage:''' https://bigvis.imsi.athenarc.gr/bigvis2019

*'''Paper Submission Deadline:''' December 30, 2018

Held in conjunction with the 22nd Intl. Conference on Extending Database Technology & 22nd Intl. Conference on Database Theory (EDBT/ICDT 2019)

[[Category:Conferences]]

Template:Conferences

2018-09-29T12:32:42Z

Bikakis:

<h1 style="padding: 5px">Upcoming/Recent Events</h1>
[[Help:How_To_Enter_Events|How to enter events?]]
*'''[[BDVA 2018]]''': October 17–19, Konstanz, Germany. The 4th International Symposium on '''Big Data Visual and Immersive Analytics'''
*'''[[VIS 2018|IEEE VIS 2018]]''': October 21–26, Berlin, Germany. IEEE '''Visual Analytics Science and Technology''', IEEE '''Information Visualization''', and IEEE '''Scientific Visualization'''
*'''[[Information+ 2018]]''': October 19–21, Potsdam, Germany. '''Interdisciplinary practices in information design & visualization'''
*'''[[VisGuides 2018]]''': October 21 (or 22), Berlin, Germany. '''2nd IEEE VIS 2018 Workshop on the Creation, Curation, Critique and Conditioning of Principles and Guidelines in Visualization'''
*'''[[VISAP'18]]''': October 23-26, Berlin, Germany. '''IEEE VIS 2018 Arts Program'''.
*'''[[IVAPP 2019]]''': Feb 25-27, Prague, Czech Republic. International Conference on '''Information Visualization Theory and Applications'''
*'''[[PacificVIS 2019]]''': April 23-26, Bangkok, Thailand. '''IEEE Pacific Visualization 2019'''
*'''[[BigVis 2019]]''': March 26, Lisbon, Portugal. '''International Workshop on Big Data Visual Exploration and Analytics '''

[[Category:Conferences]]

2017-11-29: Special Issue CFP: Special Issue on Big Data Exploration, Visualization and Analytics, Big Data Research, Elsevier (Deadline: August 1, 2018)

2017-11-29T14:50:46Z

Bikakis:

*'''Title''': Special Issue on Big Data Exploration, Visualization and Analytics, Big Data Research, Elsevier
*'''Homepage:''' https://www.journals.elsevier.com/big-data-research/call-for-papers/special-issue-on-big-data-exploration-visualization-and-anal
*'''Paper Submission Deadline:''' August 1, 2018

 

One the major challenges of the Big Data era is that it has realized the availability of a great amount and variety of massive datasets for analysis by non-corporate data analysts, such as research scientists, data journalists, policy makers, SMEs and individuals. A major characteristic of these datasets is that they are: 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. The visualization techniques, used in a variety of modern systems, provide users with intuitive means to interactively explore the content of the data, identify interesting patterns, infer correlations and causalities, and supports sense-making activities that are not always possible with traditional data 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.

This special issue aims to publish work on multidisciplinary research areas spanning from Data Management and Mining to Information Visualization and Human-Computer Interaction. In addition to the normal submissions, the special issue also considers to select some of the best papers (substantially extended and re-reviewed) from the International Workshop on Big Data Visual Exploration and Analytics (held in conjunction with the 21th Intl. Conference on Extending Database Technology & 21th Intl. Conference on Database Theory - EDBT/ICDT 2018) available here: http://bigvis2018.imis.athena-innovation.gr/

'''Special Issue 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
* Raw data visual exploration and analytics
* Incremental and adaptive processing
* 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)
* 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

'''Important Dates'''

Submission Deadline: August 1, 2018 
Author Notification: November 1, 2018 
Revised Manuscript Due: January 10, 2019 
Notification of Acceptance: February 10, 2019 
Final Manuscript Due: February 25, 2019 
Tentative Publication Date: May, 2019

'''Guest Editors'''

Nikos Bikakis, ATHENA Research Center, Greece 
George Papastefanatos, ATHENA Research Center, Greece 
Olga Papaemmanouil, Brandeis University, USA

[[Category:News]]
[[Category:2017/10]]

2017-10-16: CFP: International Workshop on Big Data Visual Exploration and Analytics, Vienna, Austria (Deadline: December 25, 2017)

2017-11-29T14:48:49Z

Bikakis:

*'''Title''': BigVis 2018 :: International Workshop on Big Data Visual Exploration and Analytics
*'''Date:''' March 26, 2018
*'''Location:''' [[wikipedia:Vienna|Vienna]], [[wikipedia:Austria|Austria]]
*'''Homepage:''' http://bigvis2018.imis.athena-innovation.gr
*'''Paper Submission Deadline:''' December 25, 2017

 
Held in conjunction with the 21th Intl. Conference on Extending Database Technology & 21th Intl. Conference on Database Theory (EDBT/ICDT 2018)

One the major challenges of the Big Data era is that it has realized the availability of a great amount and variety of massive datasets for analysis by non-corporate data analysts, such as research scientists, data journalists, policy makers, SMEs and individuals. A major characteristic of these datasets is that they are: 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. The visualization techniques, used in a variety of modern systems, provide users with intuitive means to interactively explore the content of the data, identify 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
* Raw data visual exploration and analytics
* Incremental and adaptive processing
* 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)
* 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: December 25, 2017 
Notification: January 22, 2018 
Camera-ready: January 29, 2018 
Deadlines expire at 5pm PT 
Workshop: March 26, 2018

'''Organizing Committee'''

Nikos Bikakis, ATHENA Research Center, Greece 
George Papastefanatos, ATHENA Research Center, Greece 
Olga Papaemmanouil, Brandeis University, USA

[[Category:News]]
[[Category:2017/10]]

2017-10-16: CFP: International Workshop on Big Data Visual Exploration and Analytics, Vienna, Austria (Deadline: December 25, 2017)

2017-11-29T14:46:33Z

Bikakis:

2017-11-29: Special Issue CFP: Special Issue on Big Data Exploration, Visualization and Analytics, Big Data Research, Elsevier (Deadline: August 1, 2018)

2017-11-29T14:42:58Z

Bikakis: Created page with "*'''Title''': Special Issue on Big Data Exploration, Visualization and Analytics, Big Data Research, Elsevier *'''Homepage:''' https://www.journals.elsevier.com/big-data-res..."

*'''Title''': Special Issue on Big Data Exploration, Visualization and Analytics, Big Data Research, Elsevier
*'''Homepage:''' https://www.journals.elsevier.com/big-data-research/call-for-papers/special-issue-on-big-data-exploration-visualization-and-anal
*'''Paper Submission Deadline:''' August 1, 2018

 

One the major challenges of the Big Data era is that it has realized the availability of a great amount and variety of massive datasets for analysis by non-corporate data analysts, such as research scientists, data journalists, policy makers, SMEs and individuals. A major characteristic of these datasets is that they are: 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. The visualization techniques, used in a variety of modern systems, provide users with intuitive means to interactively explore the content of the data, identify interesting patterns, infer correlations and causalities, and supports sense-making activities that are not always possible with traditional data 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.

This special issue aims to publish work on multidisciplinary research areas spanning from Data Management and Mining to Information Visualization and Human-Computer Interaction. In addition to the normal submissions, the special issue also considers to select some of the best papers (substantially extended and re-reviewed) from the International Workshop on Big Data Visual Exploration and Analytics (held in conjunction with the 21th Intl. Conference on Extending Database Technology & 21th Intl. Conference on Database Theory - EDBT/ICDT 2018) available here: http://bigvis2018.imis.athena-innovation.gr/

'''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
* Raw data visual exploration and analytics
* Incremental and adaptive processing
* 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)
* 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

'''Important Dates'''

Submission Deadline: August 1, 2018 
Author Notification: November 1, 2018 
Revised Manuscript Due: January 10, 2019 
Notification of Acceptance: February 10, 2019 
Final Manuscript Due: February 25, 2019 
Tentative Publication Date: May, 2019

'''Guest Editors'''

Nikos Bikakis, ATHENA Research Center, Greece 
George Papastefanatos, ATHENA Research Center, Greece 
Olga Papaemmanouil, Brandeis University, USA

[[Category:News]]
[[Category:2017/10]]

2017-10-16: CFP: International Workshop on Big Data Visual Exploration and Analytics, Vienna, Austria (Deadline: December 25, 2017)

2017-11-29T14:38:06Z

Bikakis: details added

*'''Title''': Special Issue on Big Data Exploration, Visualization and Analytics, Big Data Research, Elsevier
*'''Homepage:''' https://www.journals.elsevier.com/big-data-research/call-for-papers/special-issue-on-big-data-exploration-visualization-and-anal
*'''Paper Submission Deadline:''' August 1, 2018

 

One the major challenges of the Big Data era is that it has realized the availability of a great amount and variety of massive datasets for analysis by non-corporate data analysts, such as research scientists, data journalists, policy makers, SMEs and individuals. A major characteristic of these datasets is that they are: 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. The visualization techniques, used in a variety of modern systems, provide users with intuitive means to interactively explore the content of the data, identify interesting patterns, infer correlations and causalities, and supports sense-making activities that are not always possible with traditional data 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.

This special issue aims to publish work on multidisciplinary research areas spanning from Data Management and Mining to Information Visualization and Human-Computer Interaction. In addition to the normal submissions, the special issue also considers to select some of the best papers (substantially extended and re-reviewed) from the International Workshop on Big Data Visual Exploration and Analytics (held in conjunction with the 21th Intl. Conference on Extending Database Technology & 21th Intl. Conference on Database Theory - EDBT/ICDT 2018) available here: http://bigvis2018.imis.athena-innovation.gr/

'''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
* Raw data visual exploration and analytics
* Incremental and adaptive processing
* 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)
* 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

'''Important Dates'''

Submission Deadline: August 1, 2018 
Author Notification: November 1, 2018 
Revised Manuscript Due: January 10, 2019 
Notification of Acceptance: February 10, 2019 
Final Manuscript Due: February 25, 2019 
Tentative Publication Date: May, 2019

'''Guest Editors'''

Nikos Bikakis, ATHENA Research Center, Greece 
George Papastefanatos, ATHENA Research Center, Greece 
Olga Papaemmanouil, Brandeis University, USA

[[Category:News]]
[[Category:2017/10]]

Template:News

2017-11-29T14:31:38Z

Bikakis:

*[[2017-11-29: Special Issue CFP: Special Issue on Big Data Exploration, Visualization and Analytics, Big Data Research, Elsevier (Deadline: August 1, 2018)]]
*[[2017-10-16: CFP: 2nd ACM IUI Workshop on Exploratory Search and Interactive Data Analytics (ESIDA), Tokyo, Japan (Deadline: December 17, 2017)]]
*[[2017-10-16: CFP: International Workshop on Big Data Visual Exploration and Analytics, Vienna, Austria (Deadline: December 25, 2017)]]
*[[2017-10-16: Job: Full-time postdoctoral researcher at the School of Computer Science, Bangor University, UK. (Deadline: October 31, 2017)]]
*[[2017-09-22: Job: PhD Position in Visual Analytics for Engineering Smarter Systems, Linnaeus University, Växjö, Sweden. (Deadline: November 1, 2017)]]
*[[2017-09-10: Job: Lecturer/Senior Lecturer in Computer Graphics and Visualization at Victoria University of Wellington, New Zealand. (Deadline: October. 2, 2017)]]
*[[2017-07-20: CFP: Forum Media Technology 2017. St. Poelten, Austria. Nov 29-30, 2017. (Deadline: Sept. 6, 2017)]]
*[[2017-06-25: CFP: IVAPP 2018 - 9th International Conference on Information Visualization Theory and Applications (Deadline: July 31, 2017)]]
*[[2017-06-15: Call for Papers: VizSec 2017 Call for Papers (Deadline: July 18, 2017)]]
*[[2017-05-24: Job: University Assistant / PhD Position in Visualization and Human-Computer Interaction, TU Wien, Austria]]
*[[2017-04-18: Job: PhD Position in Immersive analytics, Nantes University, Nantes, France]]
*[[2017-03-01: Call for Papers: Graph Drawing and Network Visualization GD 2017 (Deadline: June 11, 2017)]]
*[[2017-02-23: CFP: Special Issue on Coupling Computation and Human Cognition through Interaction Design (Deadline: May 31, 2017)]]
*[[2017-01-25: CFP: TAProViz 2017 : 6th International Workshop on Theory and Application of Visualizations and Human-centric Aspects in Processes]]
*[[2017-01-03: Job: Three Positions as Research Associate in "Visualization" at University of Duisburg-Essen, Germany]]

[[:Category:News|'''News Archive...''']]

[http://www.infovis-wiki.net/index.php?title=Special:Newpages&namespace=104&feed=rss News as RSS feed]
 [[InfoVis:Wiki_RSS_Feeds|List of all available RSS feeds]]

2017-10-16: CFP: International Workshop on Big Data Visual Exploration and Analytics, Vienna, Austria (Deadline: December 25, 2017)

2017-10-16T14:10:30Z

Bikakis: bigvis cfp edit

2017-10-16: CFP: International Workshop on Big Data Visual Exploration and Analytics, Vienna, Austria (Deadline: December 25, 2017)

2017-10-16T14:08:53Z

Bikakis: bigvis cfp

*'''Title''': International Workshop on Big Data Visual Exploration and Analytics
*'''Date:''' March 26, 2018
*'''Location:''' [[wikipedia:Vienna|Vienna]], [[wikipedia:Austria|Austria]]
*'''Homepage:''' http://bigvis2018.imis.athena-innovation.gr
*'''Paper Submission Deadline:''' December 25, 2017

 
Held in conjunction with the 21th Intl. Conference on Extending Database Technology & 21th Intl. Conference on Database Theory (EDBT/ICDT 2018)

'''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
* Raw data visual exploration and analytics
* Incremental and adaptive processing
* 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)
* 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: December 25, 2017 
Notification: January 22, 2018 
Camera-ready: January 29, 2018 
Deadlines expire at 5pm PT 
Workshop: March 26, 2018

'''Organizing Committee'''

Nikos Bikakis, ATHENA Research Center, Greece 
George Papastefanatos, ATHENA Research Center, Greece 
Olga Papaemmanouil, Brandeis University, USA

[[Category:News]]
[[Category:2017/10]]

BigVis 2018

2017-10-16T14:06:22Z

Bikakis: bigvis entry

Template:News

2017-10-16T13:55:45Z

Bikakis: BigVis CFP

*[[2017-10-16: CFP: International Workshop on Big Data Visual Exploration and Analytics, Vienna, Austria (Deadline: December 25, 2017)]]
*[[2017-10-16: Job: Full-time postdoctoral researcher at the School of Computer Science, Bangor University, UK. (Deadline: October 31, 2017)]]
*[[2017-09-22: Job: PhD Position in Visual Analytics for Engineering Smarter Systems, Linnaeus University, Växjö, Sweden. (Deadline: November 1, 2017)]]
*[[2017-09-10: Job: Lecturer/Senior Lecturer in Computer Graphics and Visualization at Victoria University of Wellington, New Zealand. (Deadline: October. 2, 2017)]]
*[[2017-07-20: CFP: Forum Media Technology 2017. St. Poelten, Austria. Nov 29-30, 2017. (Deadline: Sept. 6, 2017)]]
*[[2017-06-25: CFP: IVAPP 2018 - 9th International Conference on Information Visualization Theory and Applications (Deadline: July 31, 2017)]]
*[[2017-06-15: Call for Papers: VizSec 2017 Call for Papers (Deadline: July 18, 2017)]]
*[[2017-05-24: Job: University Assistant / PhD Position in Visualization and Human-Computer Interaction, TU Wien, Austria]]
*[[2017-04-18: Job: PhD Position in Immersive analytics, Nantes University, Nantes, France]]
*[[2017-03-01: Call for Papers: Graph Drawing and Network Visualization GD 2017 (Deadline: June 11, 2017)]]
*[[2017-02-23: CFP: Special Issue on Coupling Computation and Human Cognition through Interaction Design (Deadline: May 31, 2017)]]
*[[2017-01-25: CFP: TAProViz 2017 : 6th International Workshop on Theory and Application of Visualizations and Human-centric Aspects in Processes]]
*[[2017-01-03: Job: Three Positions as Research Associate in "Visualization" at University of Duisburg-Essen, Germany]]

[[:Category:News|'''News Archive...''']]

[http://www.infovis-wiki.net/index.php?title=Special:Newpages&namespace=104&feed=rss News as RSS feed]
 [[InfoVis:Wiki_RSS_Feeds|List of all available RSS feeds]]

BigVis 2018

2017-10-16T13:49:33Z

Bikakis: BIGVIS DETAILS

Template:Conferences

2017-10-16T13:34:49Z

Bikakis: BigVis event added

*'''[[VINCI 2017]]''': Aug. 14-16, Bangkok, Thailand. International Symposium on Visual Information Communication and Interaction
*'''[[TAProViz 2017]]''': Sep 11, Barcelona, Spain. 6th International Workshop on '''Theory and Application of Visualizations and Human-centric Aspects in Processes''' in conjunction with the 15th International Conference on Business Process Management
*'''[[VCBM 2017]]''': September 7-8, Bremen, Germany. Eurographics Workshop on '''Visual Computing for Biology and Medicine'''
*'''[[VISSOFT 2017]]''': September 18-19, Shanghai, China. IEEE Working Conference on '''Software Visualization'''
*'''[[GD 2017]]''': September 25-27, Boston, USA. The 25nd International Symposium on '''Graph Drawing and Network Visualization'''
*'''[[BioVis 2017]]''': October 2, Phoenix, USA. IEEE/ISMB Symposium on '''Biological Data Visualization '''
*'''[[LDAV 2017]]''': October 2, 2017, Phoenix, USA. IEEE Symposium on '''Large-Scale Data Analysis and Visualization'''
*'''[[VIS 2017|IEEE VIS 2017]]''': October 1-6, Phoenix, USA. IEEE '''Visual Analytics Science and Technology''', IEEE '''Information Visualization''', and IEEE '''Scientific Visualization'''
*'''[[FMT 2017]]''': November 29-30, St. Pölten, Austria. Forum '''Media Technology''', Deadline: 2017-09-06
*'''[[IVAPP 2018]]''': Jan 27-29, Funchal, Madeira - Portugal. International Conference on '''Information Visualization Theory and Applications'''
*'''[[PacificVis 2018]]''': April 10-13, Kobe, Japan. Pacific '''Visualization''' Symposium
*'''[[BigVis 2018]]''': March 26, 2018, Vienna, Austria. International Workshop on '''Big Data Visual Exploration and Analytics'''
*'''[[EuroVis 2018]]''': June 4-8, Brno, Czech Republic. The Eurographics/IEEE Conference on '''Visualization'''
*'''[[Diagrams 2018]]''': June 18-22, Edinburgh, UK. The 10th international conference on the '''Theory and Application of Diagrams'''
*'''[[VIS 2018|IEEE VIS 2018]]''': October 21–26, Berlin, Germany. IEEE '''Visual Analytics Science and Technology''', IEEE '''Information Visualization''', and IEEE '''Scientific Visualization'''