@article {DOI10.1007/s10844-014-0304-9, title = {The human is the loop: new directions for visual analytics}, journal = {Journal of Intelligent Information Systems}, volume = {43}, year = {2014}, pages = {411-435}, publisher = {Springer US}, abstract = {Visual analytics is the science of marrying interactive visualizations and analytic algorithms to support exploratory knowledge discovery in large datasets. We argue for a shift from a {\textquoteleft}human in the loop{\textquoteright} philosophy for visual analytics to a {\textquoteleft}human is the loop{\textquoteright} viewpoint, where the focus is on recognizing analysts{\textquoteright} work processes, and seamlessly fitting analytics into that existing interactive process. We survey a range of projects that provide visual analytic support contextually in the sensemaking loop, and outline a research agenda along with future challenges.}, keywords = {clustering, Semantic interaction, Spatialization, Storytelling, Visual Analytics}, issn = {0925-9902}, doi = {10.1007/s10844-014-0304-9}, author = {Endert, Alex and Hossain, M. Shahriar and Ramakrishnan, Naren and North, Chris and Fiaux, Patrick and Andrews, Christopher} } @conference {Endert:2012:SIV:2207676.2207741, title = {Semantic interaction for visual text analytics}, booktitle = {Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems}, series = {CHI {\textquoteright}12}, year = {2012}, pages = {473{\textendash}482}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {Visual analytics emphasizes sensemaking of large, complex datasets through interactively exploring visualizations generated by statistical models. For example, dimensionality reduction methods use various similarity metrics to visualize textual document collections in a spatial metaphor, where similarities between documents are approximately represented through their relative spatial distances to each other in a 2D layout. This metaphor is designed to mimic analysts{\textquoteright} mental models of the document collection and support their analytic processes, such as clustering similar documents together. However, in current methods, users must interact with such visualizations using controls external to the visual metaphor, such as sliders, menus, or text fields, to directly control underlying model parameters that they do not understand and that do not relate to their analytic process occurring within the visual metaphor. In this paper, we present the opportunity for a new design space for visual analytic interaction, called semantic interaction, which seeks to enable analysts to spatially interact with such models directly within the visual metaphor using interactions that derive from their analytic process, such as searching, highlighting, annotating, and repositioning documents. Further, we demonstrate how semantic interactions can be implemented using machine learning techniques in a visual analytic tool, called ForceSPIRE, for interactive analysis of textual data within a spatial visualization. Analysts can express their expert domain knowledge about the documents by simply moving them, which guides the underlying model to improve the overall layout, taking the user{\textquoteright}s feedback into account.}, keywords = {interaction, Visual Analytics, visualization}, isbn = {978-1-4503-1015-4}, doi = {10.1145/2207676.2207741}, url = {http://doi.acm.org/10.1145/2207676.2207741}, author = {Endert, Alex and Fiaux, Patrick and North, Chris} } @conference {123, title = {Unifying the Sensemaking Loop with Semantic Interaction}, booktitle = {IEEE Workshop on Interactive Visual Text Analytics for Decision Making at VisWeek 2011}, year = {2011}, month = {10/2011}, address = {Providence, RI}, keywords = {Visual Analytics}, author = {Endert, Alex and Fiaux, Patrick and North, Chris} }