- Infovis - infovis.org

Identifying Important and Difficult Concepts to Learn in Information Visualization
by Parsons, Paul 11 Jun '17

11 Jun '17

Dear Colleagues, We are soliciting assistance with a research study on information visualization education. Details of the study are provided below. If you agree to participate in and complete the study, you will be entered into a draw for one of two Amazon Gift cards (US$50 value). The odds of winning will depend on the number of participants, but we estimate that they should not be lower than 1/50. Please let us know at your earliest convenience if you are able to participate by completing the following 10-minute survey: https://purdue.qualtrics.com/jfe/form/SV_7TWT2e3iLPoqKYR. Thank you for your time and consideration, Paul Parsons, Vetria Byrd, and Camilo Vieira Purdue University Interest in information visualization (InfoVis) has been growing in recent years, leading to growth in InfoVis training in both academic and non-academic contexts. As a result, InfoVis pedagogy has become an important topic for research and discussion. Little scholarship has focused directly on InfoVis education, however, and research informing curriculum design is underdeveloped. This research study aims to identify InfoVis concepts that are both important and difficult to learn. The results from this study can be used to support the curriculum development process for InfoVis programs, and to inform educational research and pedagogical practices. We are inviting you to participate in this research because you are part of a community of InfoVis educators, researchers, and practitioners. We are specifically interested in your input based on your experience teaching, learning, and/or practicing InfoVis. Your participation in this study consists of three rounds of data collection that are explained below. Throughout the three rounds your identity will be kept anonymous to other respondents (though not to the researchers). That is, you will not directly interact with other respondents and you will not know who they are, nor they will be able to identify you. Only the researchers will be able to connect your identity with your responses. Please note that all data (with and without identifiers) will be kept permanently and will be stored in a hard drive by Dr. Vieira in a locked cabinet within his office at Purdue University. Each round is expected to take approximately 10 to 15 minutes. Further, it is anticipated that there will be several weeks between each round to collate all responses, revise the instrument for the next iteration, and provide feedback to you. At the close of the third round, you will be offered the choice to receive a copy of the final report. The Delphi process provides an interactive communication structure between researchers and subject matter experts (SMEs) to develop themes, needs, and directions about a topic. This Delphi process will consist of three anonymous, iterative rounds as follows: Goal Round 1: To identify important and difficult concepts to learn in InfoVis education. Goal Round 2: To rank different levels of relevance and difficulty for each of the InfoVis concepts provided on a consolidated list. Goal Round 3: To revise the collective responses and gain consensus among the respondents. There are no foreseeable risks associated with this project, nor are there any direct benefits to participants. This project has been reviewed by the Purdue University IRB office and approved as IRB #1704019129. We apologize for the length of this introductory message; however, this message fulfills the requirements for the Delphi Method and of our Human Subjects protocol. If you have any questions or concerns, please contact us: Dr. Paul Parsons, Purdue University at parsonsp(a)purdue.edu or 765-494-0511; Dr. Vetria Byrd, Purdue University at vbyrd(a)purdue.edu or 765-494-6335; and Dr. Camilo Vieira, Purdue University at cvieira(a)purdue.edu or 765-775-0430. Paul Parsons, PhD | Assistant Professor Computer Graphics Technology | Purdue University parsonsp(a)purdue.edu | web.ics.purdue.edu/~parsonsp

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Submission Deadline June 15: Call for Papers: Interactive Visual Analytics and Visualization for Decision Making - Proceedings in IEEE Digital Library
by David S. Ebert 07 Jun '17

07 Jun '17

We are soliciting papers in interactive visualization and analytics for decision making and scientific discovery as part of the Interactive Visual Analytics and Visualization for Decision Making: Making Sense of Big Data minitrack of the Decision Analytics Track at HICSS 50. Accepted paper will appear in the proceedings as well as the IEEE Digital Library. HICSS is always one of the top conferences for downloads in the IEEE Digital Library! A description of the paper topics is below, the minitrack RFP is below, and the conference RFP is available at http://www.hicss.org/#!authors/ccjp. Please contact us with any questions. We look forward to receiving your submissions by June 15, David, Brian, Kelly David Ebert Brian Fisher Kelly Gaither ---------------------------------------------------------------------------- -------------------------------- Dr. David S. Ebert, Silicon Valley Professor of ECE, Purdue University Director, Visual Analytics for Command, Control, and Interoperability Environments http://www.VisualAnalytics-CCI.org <http://www.visualanalytics-cci.org/> Director, Purdue Visualization and Analytics Center, www.purvac.org <http://www.purvac.org/> ebertd(a)purdue.edu http://www.ece.purdue.edu/~ebertd ---------------------------------------------------------------------------- -------------------------------- CFP: Interactive Visual Analytics and Visualization for Decision Making supports human decision making through interaction with data and statistical and machine learning processes, with applications in a broad range of situations where human expertise must be brought to bear on problems characterized by massive datasets and data that are uncertain in fact, relevance, location in space and position in time. Current applications include environmental science and technologies, natural resources and energy, health and related life sciences, precision medicine, safety and security and business processes. Submissions are encouraged that extend the areas of use to new analytic tasks in science and technology, public health, business intelligence, financial analysis, social sciences, and other domains. Particular emphasis will be given to submissions that use visual analytics for social change discovery, analysis and communication. Submissions may include studies of visual analytics and decision support in the context of an organization (e.g., communication between analysts and policy-makers), perceptual and cognitive aspects of the analytic task, Interactive Machine Learning, and collaborative analysis using visual information systems. We are also seeking submissions on analytical methods and technologies that use interactive visualization to meet challenges posed by data, platforms, and applications for decision making and risk-based decision making: . Visualization and Analysis of datasets of varying size and complexity from archives and real-time streams . Collaborative visual analysis and operational coordination within and across organizations. . Interactive and Visual Risk-based decision making . Interactive Machine Learning methods . Cross-platform interoperability, from mobiles to data walls . Managing response time of complex analytical tasks . Effective deployment and case studies of success from deployed visualization and analytics experiences . Social media and streaming data visual analytics . Visualization and analytics for data-driven policy making and decision support . Business intelligence, organizational, financial, and economic decision making visual analytics . Issues and Challenges of evaluation of visual decision making . Cognitive and social science aspects of visual decision-making environments For HICSS 2018, we encourage authors to address these themes from their own research perspectives. Authors are encouraged to bring the lens of their own background and expertise to focus on the analytics of the data itself and coordination of multiple levels of analysis, decision-making and operations to the design and evaluation of effective presentations for stakeholders. Both algorithmic "data sciences" approaches and human-centered "visualization" and "visual analytics" human-computer interface methods hold great promise for operationalizing massive datasets and streaming data in support of a broad range of human activities. Applications in basic scientific research, business analytics, health sciences, environmental science and engineering R&D explore the implications of these methods for advancement of knowledge and strategic planning. Applications in coordination, command, and control of complex human activities such as crowd and traffic management, disaster relief, law enforcement, and national and cyber security add the constraints of real-time performance and distribution of planning to the challenges faced. For this mintrack we invite computational, cognitive, and organizational perspectives on advanced data processing and interactive visualization across a range of human endeavors. We also invite participation from researchers who are looking at scaling issues and multiscale issues, whether these scales refer to the time of decision making, the form-factor and operational constraints of mobile devices, the number of decision makers or the more traditional notion of multiscale simulation and real world scales of data. We are particularly interested in approaches that combine computational and interactive analytics in "mixed initiative" or Interactive Machine Learning systems, decision support in the context of an organization (e.g. communication between analysts and policy-makers), perceptual and cognitive aspects of the analytic task, and collaborative analysis using visual information systems. ---------------------------------------------------------------------------- -------------------------------- Dr. David S. Ebert, Silicon Valley Professor of ECE, Purdue University Director, Visual Analytics for Command, Control, and Interoperability Environments <http://www.visualanalytics-cci.org/> http://www.VisualAnalytics-CCI.org Director, Purdue Visualization and Analytics Center, <http://www.purvac.org/> www.purvac.org <mailto:ebertd@purdue.edu> ebertd(a)purdue.edu <http://www.ece.purdue.edu/~ebertd> http://www.ece.purdue.edu/~ebertd ---------------------------------------------------------------------------- --------------------------------

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CFP: Data Systems for Interactive Analysis (DSIA 2017)
by Remco Chang 06 Jun '17

06 Jun '17

CALL FOR PAPERS The 2nd Workshop on Data Systems for Interactive Analysis (DSIA 2017) http://www.interactive-analysis.org/ Monday, October 1st or 2nd, 2017. Phoenix, AZ. In conjunction with IEEE VIS 2017. *** Submission Deadline: July 31st, 2017 *** In its first edition in Chicago, DSIA drew more than 150 attendees for an exciting session with a keynote talk by Joe Hellerstein (UC Berkeley, Trifacta) and publications from both the visualization and data management communities. We’re looking forward to a vibrant program and discussion this year. DSIA brings together researchers at the intersection of databases, machine learning, and interactive visualization. These three areas have important things to say to each other. Modern data visualization depends on the cutting edge of both database and machine learning research: database researchers are exploring techniques for storing and querying massive amounts of data; machine learning techniques provide ways to discover unexpected patterns and to automate and scale well-defined analysis procedures. This workshop explores the idea that the next generation of database, machine learning, and interactive visualization systems should not be designed in isolation. For example, machine learning techniques might recommend improved data transformation and visual encoding decisions. Or, database query optimizers might take advantage of perceptual constraints, while prefetching methods reduce latency by modeling likely interactions. This workshop seeks to increase cross-pollination between these fields. LIST OF TOPICS This workshop will focus on interactive systems: techniques, methods, architecture, systems that enable the user to interactively explore and analyze large amounts of data in the back end with little or no latency. We encourage late-breaking work, research in progress, and position papers in interactive analysis, broadly construed. For example, topics of interest to the workshop include (but are not limited to): * design of database architectures for interactive analysis * novel database applications for interactive analysis * novel database techniques based on perceptual constraints and human-centered design * evaluation of database systems for interactive analysis * identify unique characteristics of database for supporting vis * communication protocols between front and back ends * techniques for data storage, retrieval, compression, transformation, sampling, and streaming * techniques for metadata generation * front-end architectures that exploit these novel back-end capabilities We are interested, more generally, in the questions that arise at the *intersection* of these systems. PAPER FORMAT AND SUBMISSION Submitted papers should be formatted according to TVCG guidelines. ( http://junctionpublishing.org/vgtc/Tasks/camera_tvcg.html) Papers are limited to 4 pages plus 1 additional page for references. Papers should be submitted through the Precision Conference System ( http://precisionconference.com/~vgtc, under "New Submissions" and "VIS Workshops 2017"). Accepted submissions will be archived at IEEE Xplore. IMPORTANT DATES * Submission Deadline: July 31st, 2017 * Notification Date: August 15th, 2017 * Final Version Due: August 25th, 2017 WORKSHOP ORGANIZERS * Remco Chang, Tufts University * Carlos Scheidegger, University of Arizona * Danyel Fisher, Microsoft Research * Jeffrey Heer, University of Washington CONTACT website: http://www.interactive-analysis.org email: organizers(a)interactive-analysis.org Remco -- Remco Chang Associate Professor Department of Computer Science Tufts University http://www.cs.tufts.edu/~remco (office) 617-627-3681 (lab) 617-627-6514

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VINCI 2017 Call For Posters
by Yina Li 05 Jun '17

05 Jun '17

VINCI 2017 The 10th International Symposium on Visual Information Communication and Interaction Bangkok, Thailand, 14-16 August 2017 Poster submission deadline 12 June 2017 vinci-conf.org ============================================================ Visual communication through graphical or sign languages has long been conducted among human beings of different backgrounds or cultures, and in recent decades between human and machine. In today's digital world, visual information is typically encoded with various metaphors commonly used in daily life to facilitate rapid comprehension and easy analysis during the communication process. Visual information communication generally encompasses information visualization, graphical user-interfaces, visual analytics, and visual languages. Visual information is increasingly being used to facilitate human-human communication through the Internet and mobile devices. The Symposium on Visual Information Communication and Interaction (VINCI) (vinci-conf.org) is the premier international forum for researchers and industrial practitioners to discuss the state-of-the-art in visual communication theories, designs, and applications. The 10th International Symposium on Visual Information Communication and Interaction (VINCI'17) will be held during 14-16 August 2017, in Bangkok, Thailand. All accepted posters will be published by ACM Press and made available in the ACM Digital Library (EI indexed). ============================================================ 1. SCOPES AND TOPICS We solicit original, unpublished research posters that focus on all aspects of visual information communication and interaction, either via images, computer graphics, animations, virtual reality, web, or other media. Research papers may address cognitive and design aspects, underlying theories, taxonomies, implementation work, tool support, and case studies. Topics of interest include but are not limited to the following: Cognitive aspects of visual information comprehension Empirical studies of novel visual metaphor Visual interaction through multimodality Visual approaches for knowledge discovery Computational aesthetics Visual analytics Graph drawing and (multivariate) network visualization Information visualization Graphical user interface design Aesthetics in visual communication Influence of visual arts and design Visual modeling languages and UML Visual communication metaphors Visual programming languages Visualization on mobile devices Applications like SoftVis, BioVis, GeoVis, ... Sketching Human-computer interaction 2. POSTER SUBMISSION Submissions that address research and development, as well as experience reports and tool demonstrations on the above and other related topics are strongly encouraged. All accepted posters will appear in the proceedings of VINCI 2017 published by ACM Press and made available in the ACM Digital Library (EI indexed). Posters are up to two ACM double-column pages,and should be submitted through easychair.org. 3. KEYNOTE SPEECH Keynote speech 1 Learning through Overcoming Inconsistencies, Prof. Du Zhang, (Macau University of Science and Technology) Du Zhang is Professor and Dean of the Faculty of Information Technology, Macau University of Science and Technology, Macau, China. He received his Ph.D. and M.S. degrees, both in computer science, from the University of Illinois and Nanjing University, China, respectively. Previously he was a Professor and Chair of the Computer Science Department at California State University, Sacramento. He has research affiliations with numerous universities in the USA, UK, Hong Kong, China, Czech Republic, and Mexico. Professor Zhang's current research interests include machine learning (inconsistency-induced perpetual learning), knowledge-based systems, big data analytics, and software engineering. He has over 200 publications in these and other areas. He has served in various roles on numerous international conferences, and is editor or editorial board member for several journals in the areas of artificial intelligence, software engineering and knowledge engineering, big data, and applied mathematics. Professor Zhang is a senior member of both the IEEE and ACM, a board member of the Society of Information Reuse and Integration, and a member of Upsilon Pi Epsilon and Phi Beta Delta. Keynote speech 2 Michael CohenSpatial Media and Visualization, Prof. Michael Cohen (University of Aizu, Japan) Michael Cohen received an Sc.B. in EE from Brown University (Providence, Rhode Island) in 1980, M.S. in CS from the University of Washington (Seattle) in 1988, and Ph.D. in EECS from Northwestern University (Evanston, Illinois) in 1991. He has worked at the Air Force Geophysics Lab (Hanscom Field, Massachusetts), Weizmann Institute (Rehovot; Israel), Teradyne (Boston, Massachusetts), BBN (Cambridge, Massachusetts and Stuttgart; Germany), Bellcore (Morristown and Red Bank, New Jersey), the Human Interface Technology Lab (Seattle, Washington), and the Audio Media Research Group at the NTT Human Interface Lab (Musashino and Yokosuka; Japan). He is currently a Professor in the Human Interface Lab at the University of Aizu (Aizu-Wakamatsu, Japan). He has research interests in user interfaces for telecommunications, groupware and CSCW (computer-supported collaborative work), stereotelephonics, digital typography and electronic publishing, hypermedia, ubicomp (ubiquitous computing) and virtual reality. Besides teaching various undergraduate courses including Information Theory, he co-teaches graduate-level courses in Acoustic Modeling, and Computer Music. He is a member of the ACM, IEEE, 3D-Forum, TUG (TeX Users Group), and VRSJ (Virtual Reality Society of Japan). 4. IMPORTANT DATES Poster submission deadline: June 12, 2017 (23:59 PST) Notification of decision: June 19, 2017 (23:59 PST) 5. ORGANIZATION General Chair Robert P. Biuk-Aghai, University of Macau, Macau Program Chairs Shigeo Takahashi, University of Aizu, Japan Jie Li, Tianjin University, China Local Chair Vithida Chongsuphajaisiddhi, King Mongkut’s University of Technology Thonburi, Thailand Finance Chair Vajirasak Vanijja, King Mongkut’s University of Technology Thonburi, Thailand Publicity Chair Yi-Na Li Texas A&M University, USA 6. PROGRAM COMMITTEE Benjamin Bach, Harvard University Rita Borgo, King's College London Paolo Bottoni, Sapienza University of Rome Paul Bourke, University of New South Wales Stephen Brooks, Dalhousie University Michael Burch, University of Stuttgart Vetria Byrd, Purdue University Daniel Cernea, AGT International Wei Chen, Zhejiang University Gennaro Costagliola, Università di Salerno Achim Ebert, University of Kaiserslautern Mai Elshehaly, Virginia Tech Vittorio Fuccella, Università di Salerno Liang Gou, Visa Research Denis Gracanin, Virginia Tech Jiquan Han, Huawei Technologies Jiangen He, Drexel University Masahito Hirakawa, Shimane University Seok-Hee Hong, University of Sydney Xiaodi Huang, Charles Sturt University Weidong Huang, University of Tasmania Takayuki Itoh, Ochanomizu University Andreas Kerren, Linnaeus University Karsten Klein, University of Konstanz Jun Kong, North Dakota State University Robert S. Laramee, Swansea University Yina Li, Nankai University Zhanping Liu, Kentucky State University Zhipeng Liu, Huawei Technologies Aidong Lu, UNC Charlotte Kresimir Matkovic, VRVis Research Center John McGhee, UNSW Australia Kazuo Misue, University of Tsukuba Chris Muelder, University of California at Davis Quang Vinh Nguyen, University of Western Sydney Patrick Pang, The University of Melbourne Margit Pohl, Vienna University of Technology Francois Poulet, IRISA Martin R?hlig, University of Rostock Raimondo Schettini, Università degli Studi di Milano-Bicocca Kamran Sedig, The University of Western Ontario Guanglei Song, Twitter Arcot Sowmya, University of New South Wales Changming Sun, CSIRO Ioannis G. Tollis, University of Crete Cagatay Turkay, City University London Gualtiero Volpe, DIBRIS-University of Genova Sai-Keung Wong, The National Chiao Tung University Hsiang-Yun Wu, Keio University Jie Wu, Tongji University Yingcai Wu, Zhejiang University Yu-Bin Yang, Nanjing University Kang Zhang, University of Texas at Dallas Ye Zhao, Kent State University Jianlong Zhou, CSIRO Hong Zhou, Shenzhen University

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2nd Call for Papers -- Workshop on Visualization For Machine Learning And Knowledge Extraction at CD-MAKE 2017 -- Deadline June 12 !
by Turkay, Cagatay 05 Jun '17

05 Jun '17

Dear Colleagues, Below is the 2nd Call for Papers for the following workshop titled “Visualization For Machine Learning And Knowledge Extraction” at CD-MAKE 2017, deadline is JUNE 12 !! We invite submissions to this workshop titled “Visualization For Machine Learning And Knowledge Extraction” <https://cd-make.net/special-sessions/make-vis> which is organized as a special session within the “CD-MAKE 2017 -- International Cross Domain Conference for Machine Learning & Knowledge Extraction” Conference <https://cd-make.net<https://cd-make.net/>> taking place between ** August 29 – September 1, 2017 ** in Reggio di Calabria, Italy. This workshop calls for contributions that demonstrate the role and the value of visualization within the whole data science process. The central goal of this workshop is to bring together experts from machine learning and visualization, and also practitioners and researchers from both academia and industry to spark discussion through reflections on cross-domain problems and on the use of diverse techniques from various fields. Accepted papers will be published in Lecture Notes in Artificial Intelligence (LNAI) by Springer <http://www.springer.com/series/1244> and selected papers will be invited to a special issue of the Information Visualization journal by Sage <http://journals.sagepub.com/home/ivi> following the event. The deadline for submission is: ** DEADLINE June 12, 2017 ** For further details, please refer to the CFP below, and for questions feel free to contact Cagatay Turkay <Cagatay.Turkay.1(a)city.ac.uk> and Bob Laramee <r.s.laramee(a)swansea.ac.uk>. CD-MAKE Visualisation Organizing Committee, Cagatay TURKAY, City, University of London, UK Robert S. LARAMEE, Swansea University, UK Chaomei CHEN, Drexel University, USA Andreas HOLZINGER, Graz University of Technology, Austria ==== CALL FOR PAPERS ===== VISUALIZATION FOR MACHINE LEARNING AND KNOWLEDGE EXTRACTION A Special Session at CD-MAKE 2017 -- International Cross Domain Conference for Machine Learning & Knowledge Extraction <https://cd-make.net/> AIM & SCOPE ------------------------- The central goal of this workshop is to bring together experts from machine learning and visualization. Machine learning and Knowledge extraction is an enormously increasing field with many practical applications. Whilst algorithm development is surely at the center of the whole pipeline, it is the visualization which ultimately makes the results accessible to the end user. Visualization thus can be seen as a mapping from arbitrarily high-dimensional spaces to the lower dimensions and plays a central and critical role in interacting with machine learning algorithms, and particularly with interactive machine learning (iML) with the human-in-the-loop. BACKGROUND ------------------------- The unprecedented increase in the amount, variety and value of data has been significantly transforming the way that scientific research is carried out and businesses operate. Knowledge generated from data drives innovation in almost all application domains, including health, transport, cyber security, manufacturing, digital services, and also scientific domains such as biology, medicine, environmental and physical sciences, the humanities and social sciences to name a few. Within data science, which has emerged as a practice to enable this data-intensive innovation by gathering together and advancing the knowledge from fields such as statistics, machine learning, knowledge extraction, data management, and visualization, visualization plays a unique and maybe the ultimate role as an approach to facilitate the human and computer cooperation, and to particularly enable the analysis of diverse and heterogeneous data using complex computational methods where algorithmic results are challenging to interpret and operationalize. Visual data science approaches not only support the abstraction and communication of findings, but also enable new forms of investigation and exploration that can lead to novel and better-informed observations and data-driven inferences. CALL FOR CONTRIBUTIONS ------------------------- This workshop calls for contributions that demonstrate the role and value of visualization for machine learning and knowledge extraction but also within the whole data science process. Methods that exemplify the value of the synergy between visualization and fields such as machine learning, statistics or data mining, and examples of applications where such visual data science approaches deliver new ways of extracting knowledge are highly encouraged. The workshop aims to bring together practitioners and researchers from both academia and industry, and aims to spark discussion and cross-breeding through reflections on cross-domain-driven problems and on the use of diverse techniques from various fields. SUGGESTED TOPICS FOR PAPERS INCLUDE, BUT ARE NOT LIMITED TO: ------------------------- -- Novel visual representations and interaction techniques to facilitate human-involved interactive machine learning and knowledge extraction processes -- Methods and tools for the presentation, production, and visual dissemination of analytical findings -- Data management and knowledge representation including scalable data representations -- Applications of visual data science that demonstrate the value of such a hybrid approach in a given application domain -- Methods related to clustering, subspace visualization, dimensionality reduction -- Visual analytics and konowledge discovery -- Applications of visual analytics -- Graph and Network Visualization -- Algebraic and Computational Topology and Visualization SUBMISSION FORMAT ------------------------- Accepted papers, 6-20 pages (even page numbers!) – please consult the general CD-MAKE submission guidelines<https://cd-make.net/authors-area/submission/> – will be published in the CD-MAKE Springer Volume of Lecture Notes in Artificial Intelligence (LNAI). Selected papers will be invited to a special issue of the Information Visualization (Sage) journal following the event (separate information will be provided soon). JOURNAL INFORMATION: ------------------------- Sage Information Visualization, SCI IF (2015) = 0.639 http://journals.sagepub.com/home/ivi http://dblp.uni-trier.de/db/journals/ivs Information Visualization is essential reading for researchers and practitioners of information visualization and is of interest to computer scientists and data analysts working on related specialisms. This journal is an international, peer-reviewed journal publishing articles on fundamental research and applications of information visualization. The journal acts as a dedicated forum for the theories, methodologies, techniques and evaluations of information visualization and its applications. The journal is a core vehicle for developing a generic research agenda for the field by identifying and developing the unique and significant aspects of information visualization. Emphasis is placed on interdisciplinary material and on the close connection between theory and practice. DATES: ------------------------- *** Submission deadline: June 12, 2017 *** Notifications: July 3, 2017 *** Camera-Ready deadline: July, 9, 2017 (hard deadline – no extensions possible) *** Workshop: August 29 – September 1, 2017 ORGANIZING COMMITTEE: ------------------------- Cagatay TURKAY, City, University of London, UK Robert S. LARAMEE, Swansea University, UK Chaomei CHEN,Drexel University, USA Andreas HOLZINGER, Graz University of Technology, Austria TECHNICAL COMMITTEE: ------------------------- Colleagues from the main CD-MAKE committee<https://cd-make.net/committees>

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Final Call for Papers: Graph Drawing and Network Visualization GD 2017
by Fabrizio Frati 03 Jun '17

03 Jun '17

=========================================================================== Final Call for Papers GD 2017 25th International Symposium on Graph Drawing and Network Visualization September 25-27, 2017 - Boston, MA, U.S.A. http://graphdrawing.org/gd2017 =========================================================================== PDF version: https://gd2017.ccis.northeastern.edu/files/2017/02/GD2017CFP.pdf =========================================================================== Graph Drawing is concerned with the geometric representation of graphs and constitutes the algorithmic core of Network Visualization. Graph Drawing and Network Visualization are motivated by applications where it is crucial to visually analyze and interact with relational datasets. Examples of such application areas include data science, social sciences, Web computing, information systems, biology, geography, business intelligence, information security and software engineering. GD has been the main annual event in this area for more than 20 years. Its focus is on combinatorial and algorithmic aspects of graph drawing as well as the design of network visualization systems and interfaces. GD 2017 will take place September 25-27, 2017 at the Northeastern University in Boston, Massachusetts, USA. Researchers and practitioners working on any aspects of graph drawing and network visualization are invited to contribute papers and posters and to participate in the symposium and the graph drawing contest. PAPERS ------ We invite authors to submit papers describing original research of theoretical or practical significance to graph drawing and network visualization. Regular papers must be submitted explicitly to one of two distinct tracks. Papers submitted to one track will not compete with papers submitted to the other track. Track 1: Combinatorial and algorithmic aspects ---------------------------------------------- This track is mainly devoted to fundamental graph drawing advances, such as combinatorial aspects and algorithm design. The range of topics for this track includes (but is not limited to): • Design and analysis of graph drawing algorithms • Geometric graph theory • Geometric computing • Planarity and topological graph theory • Optimization on graphs Track 2: Experimental, applied, and network visualization aspects ----------------------------------------------------------------- This track is mainly devoted to the practical aspects of graph drawing, such as the development of network visualization systems and interfaces in different application areas. The range of topics for this track includes (but is not limited to): • Visualization of graphs and networks in real world applications, including big data • Engineering of network visualization algorithms and systems • Experimental results in graph theory and algorithms • Benchmarks and experimental studies of network visualization systems and user interfaces • Cognitive studies on graph drawing readability and user interaction • Interfaces and methods for interacting with graphs Short papers ------------ In addition to the above two tracks, there will be a separate category for short papers, describing theoretical or applied contributions of shorter length. Papers in this category will be assigned a shorter time for presentation during the conference. Demos ----- Authors of applied papers will have the opportunity to show a demo of their software/system during the poster session. Submission format ----------------- All submissions must be formatted using the LaTeX style file for the conference series Lecture Notes in Computer Science (LNCS) provided by Springer. The default margins and fonts must not be modified; in particular, the use of packages such as times.sty is not allowed. Submissions that do not comply with this format risk rejection without consideration of their merits. The length of regular papers is limited to 12 pages (excluding references), while the length of short papers is limited to 6 pages (excluding references). The claims of the paper should be fully substantiated, including full proofs or appropriate experimental data. If this information does not fit within the page limits, the authors should include it in a clearly marked appendix, whose length is not constrained and which the reviewers may read at their own discretion. POSTERS ------- Submissions of posters on graph drawing, network visualization, and related areas are solicited. The poster session will provide a forum for the communication of late-breaking research results (which may also appear elsewhere) to the GD community. Authors of posters should prepare an abstract (up to 2 pages in the LNCS style) that must be submitted together with the poster itself. CONTEST ------- Details about the traditional Graph Drawing Contest held at the conference will be provided on the conference Web site. PUBLICATION ----------- All accepted papers (including the two-page poster abstracts) will appear in the conference proceedings, published by Springer in the Lecture Notes in Computer Science (LNCS) series. Twelve pages (excluding references) will be allocated for regular papers and six pages (excluding references) for short papers. The LNCS proceedings will be made freely accessible to the GD community upon publication and openly accessible to anyone after four years. Authors will be required to submit their accepted papers to the arXiv repository, in order to provide immediate and unrestricted open access to them. The self-archived arXiv papers shall consist of an identical copy of the LNCS proceedings plus an optional clearly marked appendix, possibly containing a long version of the entire paper or proofs that have been omitted from the main text. Subsequent submissions of different versions of the paper to the arXiv (known as arXiv ``replacements’’) are allowed. Upon submission of the camera-ready version of an accepted paper, the authors will be required to specify the arXiv identifier associated with the paper for inclusion in a conference index, which will be also published in the ArXiv repository. Failure to comply with these guidelines will impede the publication of the paper. Each paper must be presented at the conference by an author (baring unforeseen circumstances), otherwise the paper will not be included in the proceedings. Should any visa restriction prevent an author from attending the conference and presenting a paper, he/she will be given ways to participate and give the talk via electronic means. Selected papers from both tracks will be invited for submission to a special issue of the Journal of Graph Algorithms and Applications (JGAA). The authors of the best paper in Track 2 will be invited to submit a substantially extended and enhanced version of their work to IEEE Transactions on Visualization and Computer Graphics (TVCG). AWARDS ------ For each of the two tracks, the Program Committee of GD 2017 will give a Best Paper Award. In addition, to recognize the effort of participants to present their work and to prepare their posters in a clear and elegant way, there will be a Best Presentation Award and a Best Poster Award voted on by the GD 2017 attendees. IMPORTANT DATES --------------- • Paper submission deadline: June 11 (23:59 PDT) – Updates possible until June 13 (23:59 PDT) • Notification of paper acceptance: July 28 • Poster submission deadline August 17 (23:59 PDT) • Notification of poster acceptance August 28 • Final versions due September 3 • Contest submission deadline September 13 • Symposium September 25-27 INVITED SPEAKERS ---------------- Timothy M. Chan, University of Illinois at Urbana-Champaign, USA Alessandro Vespignani, Northeastern University, US PROGRAM COMMITTEE ----------------- Daniel Archambault, Swansea University, GB Benjamin Bach, University of Edinburgh, GB Fabian Beck, Universität Duisburg-Essen, DE Michael Bekos, Universität Tübingen, DE Therese Biedl, University of Waterloo, CA Giordano Da Lozzo, UC Irvine, US Vida Dujmovic, University of Ottawa, CA Stephane Durocher, University of Manitoba, CA Tim Dwyer, Monash University, AU Fabrizio Frati (co-chair), Università Roma Tre, IT Martin Gronemann, Universität zu Köln, DE John Alexis Guerra Gómez, Universidad de los Andes, CO Michael Hoffmann, ETH Zürich, CH Yifan Hu, Yahoo Research, US Takayuki Itoh, Ochanomizu University, JP Anna Lubiw, University of Waterloo, CA Kwan-Liu Ma (co-chair), UC Davis, US Fabrizio Montecchiani, Università degli Studi di Perugia, IT Martin Nöllenburg, Technische Universität Wien, AT Arnaud Sallaberry, LIRMM, FR Andrew Suk, University of Illinois at Chicago, US Antonios Symvonis, National Technical University of Athens, GR Ioannis Tollis, University of Crete, GR Csaba Tóth, California State University Northridge, US Alexander Wolff, Universität Würzburg, DE Jian Zhao, FX Palo Alto Laboratory, US ORGANIZING COMMITTEE -------------------- Cody Dunne (co-chair), Northeastern University, US Alan Keahey (co-chair), Conversant, US CONTEST COMMITTEE ----------------- Philipp Kindermann, Universität Würzburg, DE Maarten Löffler (chair), Utrecht University, NL Ignaz Rutter, Karlsruhe Institute of Technology, DE

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CFP: 2017 IEEE VIS Workshop on Visual Analytics for Deep Learning
by Jaegul Choo 31 May '17

31 May '17

CFP: VADL: 2017 IEEE VIS Workshop on Visual Analytics for Deep Learning Arizona, Phoenix, 1 or 2 October 2017 https://vadl2017.github.io/ Recently, deep neural networks have been achieving breakthroughs in various major artificial intelligence tasks such as machine translation, image understanding, speech recognition, and so on. In these tasks, deep neural networks reached the level of an accuracy comparable to or even better than humans’ performance. However, understanding the deep neural networks is challenging due to their complicated inner workings. VADL, the workshop on visual analytics for deep learning, is a half-day workshop held in conjunction with IEEE VIS 2017 in Phoenix, AZ. The primary goal of the workshop is to bridge the gap by bringing together researchers from both machine learning and visual analytics fields, which allows us to push the boundary of deep learning. The workshop should provide an opportunity to discuss and explore ways to harmonize the power of automated techniques and exploratory nature of interactive visualization. Topics of Interest: In this call, we look for papers related to visual analytics for deep learning. Topics of interest include, but are not limited to: - User-adaptive approaches to deep neural networks - Coupling of deep learning-based systems with interactive visualization - Visualization to improve deep learning algorithms and models - Coordinated visualizations for deep learning - Systems, languages, and architectures for interactive deep learning - Collaborative analysis of deep network networks - Real-time visualization of streaming data handling in deep learning - Visualization of uncertainty in deep neural networks - Domain-specific applications of visual analysis of deep neural networks (e.g. retail, healthcare, government, etc.) - Studies and evaluation of deep learning visualization techniques, systems, metrics, and benchmarks Submission Information: All papers will be peer reviewed, single-blinded. We welcome many kinds of papers, including (but not limited to): - Novel research papers - Demo papers - Work-in-progress papers - Visionary papers (white papers) - Position papers - Relevant work that has been previously published - Work that will be presented at the main conference of IEEE VIS’17 Authors should clearly indicate in their abstracts the kinds of submissions, to help reviewers better understand their contributions. Submissions must be in PDF, written in English, no more than 10 pages long — shorter papers such as 2 to 4 pages are welcome — and formatted using the IEEE “Conference Style” template. The accepted papers will be posted on the workshop website and will be included in the IEEE VIS’17 electronic proceedings USB stick. For accepted papers, at least one author must attend the workshop to present the work. Important Dates: - Submission: July 21, 2017 - Author notification: August 4, 2017 - Camera-ready: August 18, 2015 - Workshop date: October 1 or 2

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Postdoctoral Fellow - Augmented Reality for Decision Support
by Matt.Adcock＠csiro.au 31 May '17

31 May '17

Postdoctoral Fellow - Augmented Reality for Decision Support * Are you a highly motivated PhD graduate? * Do you have a passion for developing novel interactive Augmented Reality (AR) applications? * This is a great opportunity to have substantial impact in Aquaculture and Agriculture! Future Science Platforms (FSPs) are a major new CSIRO initiative. FSPs are multi-year investments in frontier science that will reinvent and create new industries for Australia. Digiscape is the FSP that is creating next-generation decision tools to transform the agriculture and land management sector. To achieve this aim, Digiscape is bringing to bear cutting edge climate science; new sources of locally and remotely sensed data; informatics for agro-ecosystems; rigorous analysis of uncertainties; and innovation in both the ICT and social dimensions of systems integration. The successful candidate will join a cohort of early-career researchers and engineers who will combine their individual disciplinary contributions into mission-focussed R&D. Part of the Digiscape vision is that Augmented Reality technologies (such as Microsoft HoloLens) will play a key role in supporting individual and team decision making, both in the field and in the office. In the aquaculture domain these tools will assist operators on the ground and/or in the office to visualise pond conditions and access short-term pond predictions across multiple ponds. They will be a primary method for accessing the data management and modelling frameworks developed in related projects. Your success in this role will be underpinned by your record of science innovation and creativity, plus your ability and willingness to incorporate novel ideas and approaches into scientific investigations. The successful applicant will implement and evaluate prototype systems, while making use of the Advanced Augmented Reality and Virtual Reality (VR) facilities in the Data61 Immersive Environments Lab in Canberra. To be considered you will have (or expect to imminently complete) a PhD in Computer Science, Engineering or a directly related field. You will have experience conducting research in interactive 3D graphics and/or computer vision in Virtual Reality, Augmented Reality and/or Web3D. You will also have the ability to work effectively as part of a multi-disciplinary, regionally dispersed research team and carry out tasks autonomously. To view the full position details and selection criteria for this role please go to www.jobs.csiro.au and search for reference number 29563 Location: Canberra, ACT Salary: $78K - $88K p.a. plus up to 15.4% superannuation Professional Development Budget: Yes Tenure: 3 year term Reference: 29563 How to Apply: Please upload one document containing your CV/resume and cover letter. Please ensure you provide enough information relevant to the selection criteria for this position (as described in the Position Details Document) to enable the assessment panel to determine your suitability. Who we are: The Commonwealth Scientific and Industrial Research Organisation (CSIRO) As Australia's national science agency, we've been pushing the edge of what's possible for almost 90 years. Today we have thousands of talented people working across Australia and internationally. Our people work closely with industry and communities to leave a lasting legacy. Collectively, our innovation and excellence places us in the top ten applied research agencies in the world. Applications will remain open until filled, however we encourage you to submit your application before 12 June 2017 as we will interview suitable candidates from that date onwards.

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Postdoctoral Fellowship with Sheelagh Carpendale and Wesley Willett in Interactions lab at University of Calgary
by Soren Knudsen 29 May '17

29 May '17

The Interactions Lab in the Department of Computer Science in the Faculty of Science at the University of Calgary is accepting applications for a Postdoctoral Fellow in Information Visualization Design. Job Description: The Innovations in Visualization (led by Sheelagh Carpendale) and the Data Experience (led by Wesley Willett) labs are looking for a Post Doctoral Fellow in Information Visualization, Design, and/or Interaction Design. The project is an open data initiative that is focused on developing advanced, interactive data visualizations that will help make Canada's energy data publically accessible, transparent and understandable. The successful candidate will be deeply involved in the research in the lab, working closely with domain experts and stakeholders, creating new design ideas, developing new visual representations, fine tuning designs, and creating prototypes and communicating these designs to relevant team members. They will also be involved in mentoring students who are working on the project. The successful candidate's work will include participating in various outreach activities - including designing and running workshops and providing formal and informal demonstrations to appropriate stakeholders. The successful candidate's work will focus explicitly on designing novel interactive visualizations and interaction techniques and will include opportunities to publish that work at visualization venues. Qualifications: PhD or equivalent degree in Computer Science, Informatics, Design, or a related field. A background in information visualization and with extensive experience designing and developing interactive visualizations is important. This position will also call upon the candidate's ability to understand and apply data analysis approaches in a broad range of domains. We are interested in candidates with an ability to bridge the gap between scientific endeavors and real-world applications, producing results with high external validity. Experience designing and conducting both qualitative and quantitative studies are also strongly preferred. Application details: Please apply by email to Claudia Maurer, claudia.maurer(a)ucalgary.ca<mailto:claudia.maurer@ucalgary.ca> Please send your CV, a short cover letter and the names of two people who can serve as references. Sheelagh Carpendale, http://innovis.cpsc.ucalgary.ca/ Wesley Willett, http://dataexperience.cpsc.ucalgary.ca/

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Postdoc in Graph Drawing and related areas at Roma Tre University
by Fabrizio Frati 25 May '17

25 May '17

Expressions of interest are invited for a postdoc position in graph drawing and related areas at the graph drawing research group led by Prof. Giuseppe Di Battista at the Department of Engineering at Roma Tre University. The research group includes Fabrizio Frati, Maurizio Patrignani, and Maurizio Pizzonia as permanent members, together with several postdocs and PhD students. The postdoc position is funded by the PRIN (Research Projects of National Interest) Project "MODE" - Morphing graph drawings efficiently. The ideal candidate for the position should have a PhD in Mathematics or Computer Science and should have a background in algorithms, theoretical computer science and/or discrete mathematics, preferably with an interest in graph drawing, graph theory, and/or combinatorial geometry. Should any candidate be considered fit for the postdoc position, a call for applications will be opened. The postdoc appointment is to begin at any time during 2017 (or early 2018), the sooner the better. The position is for one year, renewable for a second year. The position is full-time and research-only. The position is open to candidates of any nationality; in particular, no knowledge of Italian is required. The gross salary is 27K, which will result in ~1650 net per month. Travel funding will be available. The reply to this call should consist of an email, sent to frati(a)dia.uniroma3.it, containing: (1) a curriculum vitae, including a list of publications; and (2) the names and contact details of at least two references. Expressions of interest should be sent no later than the 15th of July, 2017.

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