@article {17487,
	title = {Visual Exploration across Biomedical Databases},
	journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
	volume = {8},
	year = {2011},
	month = {2011/04//March},
	pages = {536 - 550},
	abstract = {Though biomedical research often draws on knowledge from a wide variety of fields, few visualization methods for biomedical data incorporate meaningful cross-database exploration. A new approach is offered for visualizing and exploring a query-based subset of multiple heterogeneous biomedical databases. Databases are modeled as an entity-relation graph containing nodes (database records) and links (relationships between records). Users specify a keyword search string to retrieve an initial set of nodes, and then explore intra- and interdatabase links. Results are visualized with user-defined semantic substrates to take advantage of the rich set of attributes usually present in biomedical data. Comments from domain experts indicate that this visualization method is potentially advantageous for biomedical knowledge exploration.},
	keywords = {Bioinformatics, Biomedical computing, biomedical databases, cross-database exploration, Data exploration and discovery, Data visualization, database management systems, Databases, Factual, DNA, graph theory, Information Storage and Retrieval, information visualization., Keyword search, medical computing, natural language processing, Proteins, semantic networks, semantics, sequences, text mining, User-Computer Interface, user-defined semantics, visual databases},
	isbn = {1545-5963},
	doi = {10.1109/TCBB.2010.1},
	author = {Lieberman,M.D. and Taheri, S. and Guo,Huimin and Mirrashed,F. and Yahav,I. and Aris,A. and Shneiderman, Ben}
}
@article {17397,
	title = {Temporal Summaries: Supporting Temporal Categorical Searching, Aggregation and Comparison},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	volume = {15},
	year = {2009},
	month = {2009/12//Nov},
	pages = {1049 - 1056},
	abstract = {When analyzing thousands of event histories, analysts often want to see the events as an aggregate to detect insights and generate new hypotheses about the data. An analysis tool must emphasize both the prevalence and the temporal ordering of these events. Additionally, the analysis tool must also support flexible comparisons to allow analysts to gather visual evidence. In a previous work, we introduced align, rank, and filter (ARF) to accentuate temporal ordering. In this paper, we present temporal summaries, an interactive visualization technique that highlights the prevalence of event occurrences. Temporal summaries dynamically aggregate events in multiple granularities (year, month, week, day, hour, etc.) for the purpose of spotting trends over time and comparing several groups of records. They provide affordances for analysts to perform temporal range filters. We demonstrate the applicability of this approach in two extensive case studies with analysts who applied temporal summaries to search, filter, and look for patterns in electronic health records and academic records.},
	keywords = {Aggregates, Collaborative work, Computational Biology, Computer Graphics, Data analysis, data visualisation, Data visualization, Databases, Factual, Displays, Event detection, Filters, Heparin, History, Human computer interaction, Human-computer interaction, HUMANS, Information Visualization, Interaction design, interactive visualization technique, Medical Records Systems, Computerized, Pattern Recognition, Automated, Performance analysis, Springs, temporal categorical data visualization, temporal categorical searching, temporal ordering, temporal summaries, Thrombocytopenia, Time factors},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2009.187},
	author = {Wang,T. D and Plaisant, Catherine and Shneiderman, Ben and Spring, Neil and Roseman,D. and Marchand,G. and Mukherjee,V. and Smith,M.}
}
@article {17250,
	title = {Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	volume = {14},
	year = {2008},
	month = {2008/10//Sept},
	pages = {999 - 1014},
	abstract = {Databases often contain uncertain and imprecise references to real-world entities. Entity resolution, the process of reconciling multiple references to underlying real-world entities, is an important data cleaning process required before accurate visualization or analysis of the data is possible. In many cases, in addition to noisy data describing entities, there is data describing the relationships among the entities. This relational data is important during the entity resolution process; it is useful both for the algorithms which determine likely database references to be resolved and for visual analytic tools which support the entity resolution process. In this paper, we introduce a novel user interface, D-Dupe, for interactive entity resolution in relational data. D-Dupe effectively combines relational entity resolution algorithms with a novel network visualization that enables users to make use of an entity{\textquoteright}s relational context for making resolution decisions. Since resolution decisions often are interdependent, D-Dupe facilitates understanding this complex process through animations which highlight combined inferences and a history mechanism which allows users to inspect chains of resolution decisions. An empirical study with 12 users confirmed the benefits of the relational context visualization on the performance of entity resolution tasks in relational data in terms of time as well as users{\textquoteright} confidence and satisfaction.},
	keywords = {algorithms, Computer Graphics, D-Dupe, data visualisation, database management systems, Databases, Factual, graphical user interface, Graphical user interfaces, human-centered computing, Image Interpretation, Computer-Assisted, Information Storage and Retrieval, Information Visualization, interactive entity resolution, relational context visualization, Relational databases, relational entity resolution algorithm, User interfaces, user-centered design, User-Computer Interface, visual analytic tool},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2008.55},
	author = {Kang,Hyunmo and Getoor, Lise and Shneiderman, Ben and Bilgic,M. and Licamele,L.}
}
