@article {16273,
	title = {Hawkeye and AMOS: Visualizing and Assessing the Quality of Genome Assemblies},
	journal = {Briefings in Bioinformatics},
	year = {2011},
	month = {2011/12/23/},
	abstract = {Since its launch in 2004, the open-source AMOS project has released several innovative DNA sequence analysis applications including: Hawkeye, a visual analytics tool for inspecting the structure of genome assemblies; the Assembly Forensics and FRCurve pipelines for systematically evaluating the quality of a genome assembly; and AMOScmp, the first comparative genome assembler. These applications have been used to assemble and analyze dozens of genomes ranging in complexity from simple microbial species through mammalian genomes. Recent efforts have been focused on enhancing support for new data characteristics brought on by second- and now third-generation sequencing. This review describes the major components of AMOS in light of these challenges, with an emphasis on methods for assessing assembly quality and the visual analytics capabilities of Hawkeye. These interactive graphical aspects are essential for navigating and understanding the complexities of a genome assembly, from the overall genome structure down to individual bases. Hawkeye and AMOS are available open source at http://amos.sourceforge.net.},
	keywords = {assembly forensics, DNA Sequencing, genome assembly, visual analytics},
	isbn = {1467-5463, 1477-4054},
	doi = {10.1093/bib/bbr074},
	url = {http://bib.oxfordjournals.org/content/early/2011/12/23/bib.bbr074},
	author = {Schatz,Michael C and Phillippy,Adam M and Sommer,Daniel D and Delcher,Arthur L. and Puiu,Daniela and Narzisi,Giuseppe and Salzberg,Steven L. and Pop, Mihai}
}
@conference {17423,
	title = {The state of visual analytics: Views on what visual analytics is and where it is going},
	booktitle = {2010 IEEE Symposium on Visual Analytics Science and Technology (VAST)},
	year = {2010},
	month = {2010/10/25/26},
	pages = {257 - 259},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In the 2005 publication "Illuminating the Path" visual analytics was defined as "the science of analytical reasoning facilitated by interactive visual interfaces." A lot of work has been done in visual analytics over the intervening five years. While visual analytics started in the United States with a focus on security, it is now a worldwide research agenda with a broad range of application domains. This is evidenced by efforts like the European VisMaster program and the upcoming Visual Analytics and Knowledge Discovery (VAKD) workshop, just to name two.There are still questions concerning where and how visual analytics fits in the large body of research and applications represented by the VisWeek community. This panel will present distinct viewpoints on what visual analytics is and its role in understanding complex information in a complex world. The goal of this panel is to engender discussion from the audience on the emergence and continued advancement of visual analytics and its role relative to fields of related research. Four distinguished panelists will provide their perspective on visual analytics focusing on what it is, what it should be, and thoughts about a development path between these two states. The purpose of the presentations is not to give a critical review of the literature but rather to give a review on the field and to provide a contextual perspective based on the panelists{\textquoteright} years of experience and accumulated knowledge.},
	keywords = {analytical reasoning, Data analysis, data mining, data visualisation, European VisMaster program, interactive visual interfaces, knowledge discovery, United States, visual analytics, VisWeek community},
	isbn = {978-1-4244-9488-0},
	doi = {10.1109/VAST.2010.5649078},
	author = {May,R. and Hanrahan,P. and Keim,D. A and Shneiderman, Ben and Card,S.}
}
@article {16059,
	title = {Advancing User-Centered Evaluation of Visual Analytic Environments Through Contests},
	journal = {Information VisualizationInformation Visualization},
	volume = {8},
	year = {2009},
	month = {2009/09/21/},
	pages = {230 - 238},
	abstract = {In this paper, the authors describe the Visual Analytics Science and Technology (VAST) Symposium contests run in 2006 and 2007 and the VAST 2008 and 2009 challenges. These contests were designed to provide researchers with a better understanding of the tasks and data that face potential end users. Access to these end users is limited because of time constraints and the classified nature of the tasks and data. In that respect, the contests serve as an intermediary, with the metrics and feedback serving as measures of utility to the end users. The authors summarize the lessons learned and the future directions for VAST Challenges.},
	keywords = {metrics, synthetic data, user-centered evaluation, visual analytics},
	isbn = {1473-8716, 1473-8724},
	doi = {10.1057/ivs.2009.16},
	url = {http://ivi.sagepub.com/content/8/3/230},
	author = {Costello,Loura and Grinstein,Georges and Plaisant, Catherine and Scholtz,Jean}
}
@conference {17168,
	title = {First Steps to Netviz Nirvana: Evaluating Social Network Analysis with NodeXL},
	booktitle = {International Conference on Computational Science and Engineering, 2009. CSE {\textquoteright}09},
	volume = {4},
	year = {2009},
	month = {2009/08/29/31},
	pages = {332 - 339},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Social Network Analysis (SNA) has evolved as a popular, standard method for modeling meaningful, often hidden structural relationships in communities. Existing SNA tools often involve extensive pre-processing or intensive programming skills that can challenge practitioners and students alike. NodeXL, an open-source template for Microsoft Excel, integrates a library of common network metrics and graph layout algorithms within the familiar spreadsheet format, offering a potentially low-barrier-to-entry framework for teaching and learning SNA. We present the preliminary findings of 2 user studies of 21 graduate students who engaged in SNA using NodeXL. The majority of students, while information professionals, had little technical background or experience with SNA techniques. Six of the participants had more technical backgrounds and were chosen specifically for their experience with graph drawing and information visualization. Our primary objectives were (1) to evaluate NodeXL as an SNA tool for a broad base of users and (2) to explore methods for teaching SNA. Our complementary dual case-study format demonstrates the usability of NodeXL for a diverse set of users, and significantly, the power of a tightly integrated metrics/visualization tool to spark insight and facilitate sense-making for students of SNA.},
	keywords = {Computer science, computer science education, data visualisation, Data visualization, Educational institutions, graph drawing, graph layout algorithm, Information services, Information Visualization, Internet, Libraries, Microsoft Excel open-source template, MILC, multi-dimensional in-depth long-term case studies, Netviz Nirvana, NodeXL, Open source software, Programming profession, SNA, social network analysis, Social network services, social networking (online), spreadsheet programs, structural relationship, teaching, visual analytics, visualization tool, Web sites},
	isbn = {978-1-4244-5334-4},
	doi = {10.1109/CSE.2009.120},
	author = {Bonsignore,E. M and Dunne,C. and Rotman,D. and Smith,M. and Capone,T. and Hansen,D. L and Shneiderman, Ben}
}
@article {17238,
	title = {Integrating Statistics and Visualization for Exploratory Power: From Long-Term Case Studies to Design Guidelines},
	journal = {IEEE Computer Graphics and Applications},
	volume = {29},
	year = {2009},
	month = {2009/06//May},
	pages = {39 - 51},
	abstract = {Evaluating visual-analytics systems is challenging because laboratory-based controlled experiments might not effectively represent analytical tasks. One such system, Social Action, integrates statistics and visualization in an interactive exploratory tool for social network analysis. This article describes results from long-term case studies with domain experts and extends established design goals for information visualization.},
	keywords = {case studies, Control systems, Data analysis, data mining, data visualisation, Data visualization, data-mining, design guidelines, Employment, exploration, Filters, Guidelines, Information Visualization, insights, laboratory-based controlled experiments, Performance analysis, social network analysis, Social network services, social networking (online), social networks, SocialAction, statistical analysis, Statistics, visual analytics, visual-analytics systems, Visualization},
	isbn = {0272-1716},
	doi = {10.1109/MCG.2009.44},
	author = {Perer,A. and Shneiderman, Ben}
}
@article {17272,
	title = {Knowledge discovery in high-dimensional data: case studies and a user survey for the rank-by-feature framework},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	volume = {12},
	year = {2006},
	month = {2006/06//May},
	pages = {311 - 322},
	abstract = {Knowledge discovery in high-dimensional data is a challenging enterprise, but new visual analytic tools appear to offer users remarkable powers if they are ready to learn new concepts and interfaces. Our three-year effort to develop versions of the hierarchical clustering explorer (HCE) began with building an interactive tool for exploring clustering results. It expanded, based on user needs, to include other potent analytic and visualization tools for multivariate data, especially the rank-by-feature framework. Our own successes using HCE provided some testimonial evidence of its utility, but we felt it necessary to get beyond our subjective impressions. This paper presents an evaluation of the hierarchical clustering explorer (HCE) using three case studies and an e-mail user survey (n=57) to focus on skill acquisition with the novel concepts and interface for the rank-by-feature framework. Knowledgeable and motivated users in diverse fields provided multiple perspectives that refined our understanding of strengths and weaknesses. A user survey confirmed the benefits of HCE, but gave less guidance about improvements. Both evaluations suggested improved training methods},
	keywords = {case study, Computer aided software engineering, Computer Society, Data analysis, data mining, data visualisation, Data visualization, database management systems, e-mail user survey, Genomics, Helium, Hierarchical Clustering Explorer, hierarchical clustering explorer., high-dimensional data, Histograms, Information visualization evaluation, interactive systems, interactive tool, knowledge discovery, multivariate data, Rank-by-feature framework, Scattering, Testing, user interface, User interfaces, user survey, visual analytic tools, visual analytics, visualization tools},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2006.50},
	author = {Seo,Jinwook and Shneiderman, Ben}
}
