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Sensemaking is the process through which humans put together understanding of related information. Sensemaking has been said to involve changes in cognitive representations during a human information processing task. Collection sensemaking involves understanding a collection of media entities, as a whole. One example of a sensemaking task is to compare the damage from Hurricane Katrina to homes, personal effects, and community buildings in different areas of New Orleans. Connected visual and semantic representations provide perspective to support users involved in collection sensemaking tasks. A zoomable map organizes images based on location at varying scales. Multiscale clusters based on zoom level organize images associated with events. The clusters afford contextualized thumbnail browsing and also maintain uniform information density on the map. Metadata enhances context and memory in the process of collection sensemaking.

Sensemaking systems don't only help people find stuff faster. That's just the information retrieval part. The bigger story is about augmenting and amplifying our abilities to make sense. Sensemaking adds things like skimming, power reading, organizing, spotting patterns, tracing social networks, taking notes, summarizing, drilling for details, and flagging biases. Reading an article is different from reading a book, and that's different from reading from a collection or stream. Radically new forms of human-information interaction are being enabled by these new technologies. Sensemaking systems not only have front ends (visualization), but also back ends (content analytics and reasoning).

In the process of knowledge discovery, workers examine available information in order to make sense of it. By sensemaking, we mean interacting with and operating on the information with a variety of information processing mechanisms [3,18]. Previously, we introduced a concept that uses the spreadsheet metaphor with cells containing visualizations of complex data. In this paper, we extend and apply a cognitive model called "visual sensemaking " to the Visualization Spreadsheet. We use the task of making sense of a large Web site as a concrete example through out the paper for demonstration. Using a variety of visualization techniques, such as the Disk Tree and Cone Tree, we show that the interactions of the Visualization Spreadsheet help users draw conclusions from the overall relationships of the entire information set.

This is a resource page for CCL's Visual Explorer™ with descriptions of the tool and its multiple uses for creative conversations and dialogue. VE™ supports strategy making, visioning, culture transformation, creative problem solving, coaching, classroom facilitation, teambuilding, visual sensemaking, resolving complex challenges, and leadership development.

This paper is based on a study of personal experience narratives told by witnesses of the September 11th attacks in calls to C-SPAN. Drawing on research on narratives of ordinary and extraordinary experiences and witnessing, the author offers a framework for analyzing the structure and function of eyewitness accounts. Analysis focuses on methods callers use to show and tell the audience where they were, what they were doing, and what they were thinking at the time of the attacks. Verbal, visual, and structural features of these narratives are highlighted, with particular attention given to orientation and ideation components of the narratives. The design of these components and their location within the callers' stories are shown to construct the narratives as eyewitness accounts, position the callers and audience members as witnesses, and engage all in a therapeutic sensemaking process.

The present research analyses the 'social visualization' tool Sense.us, a commercial interactive Web application in which U.S. Census data are visualized. Sense.us was developed as a tool for social data exploration and interaction, in which it would be worthwhile to pay attention to the socio-cultural values that have driven the collection and categorization of the underlying U.S. Census datasets. It is argued that closer attention to value driven U.S. Census statistics would greatly enhance the social appeal of Sense.us, and would be a logical next step in the development of online social visualization tools. In order to allow for explicit socio-cultural values of statistics in online visualizations, three strategies are offered: pro-active annotation; more attention to visual aesthetics; and, a tighter integration of user profiles and represented data.

Using segments of rich media makes it possible to aggregate context and meaning on these chunks by using a number of different mechanisms. Starting with a granular node -- be it a sound bite, visual clip or written fact -- it is possible to aggregate contextual metadata through a series of steps that emergently progress from: * Starting with thousands of defined Audio Sound Bites & visual clips * Rating sound bites and clustering them with folksonomy tags * Sequencing audio sound bites within playlists * Collaboratively building larger sequences with nested playlists * Independently controlling the video & audio tracks with 2-dimensional nested playlists * Evaluating Multiple Storylines and Hypotheses with a 2-dimensional playlist matrix * Visualizing complex networks by mapping out feedback loop relationships between nodes

understanding this content and making decisions based on it (especially in mission-critical situations) is not just a simple matter of consuming information. To effectively "make sense" of large, heterogeneous, and often unstructured content collections requires: - efficient, accurate, and context-based ways of extracting, filtering, and summarizing information; - better and more meaningful ways of organizing, visualizing, and interacting with the information; - faster, more objective methods for investigating hypotheses, detecting trends or patterns across multiple sources, and otherwise analyzing or interpreting information.

VE can be used in a wide variety of ways depending on the context. Here are the five basic steps for using VE to facilitate a group conversation around a shared question. These steps can be altered or elaborated for particular situations as described in the VE Guidebook. 1. Frame 2. Browse 3. Reflect 4. Share 5. Extend

Jigsaw provides a collection of visualizations that each portray different aspects of the documents. We particularly focus on presenting the identifiable important entities (people, places, organizations, etc.) and their direct or indirect connections. Textual processing extracts the important entities from the documents and then the visualizations help an analyst to explore the relationships and connections among the entities. The system includes graph, calendar, scatterplot and and tabular connections-based views, as well as views of individual document's text and the report collections as a whole. Jigsaw essentially acts as a visual index onto the document collection, helping analysts identify particular documents to read and examine next.

TagCrowd is a web application for visualizing word frequencies in any user-supplied text by creating what is popularly known as a tag cloud or text cloud. TagCrowd is taking tag clouds far beyond their original function: * as topic summaries for speeches and written works * as blog tool or website analysis for search engine optimization (SEO) * for visual analysis of survey data * as brand clouds that let companies see how they are perceived by the world * for data mining a text corpus * for helping writers and students reflect on their work * as name tags for conferences, cocktail parties or wherever new collaborations start * as resumes in a single glance * as visual poetry

TagMaps is a toolkit to visualize text (well, tags) geographically on a map.

The scholarly literature forms a vast network of academic papers connected to one another by citations in bibliographies and footnotes [1]. The structure of this network reflects millions of decisions by individual scholars about which papers are important and relevant to their own work. Therefore within the structure of this network is a wealth of information about the relative influence of individual journals, and also about the patterns of relations among academic disciplines. Our aim at eigenfactor.org is develop ways of extracting this information.

Picturing to Learn (PtL) is founded on the following core premises: one From a student's perspective: undergraduate students can clarify their own understanding of scientific concepts and processes by creating drawings that explain these concepts to non-experts. two From a teacher's perspective: drawings can be useful as: * assessment tools, allowing instructors to identify students' scientific understanding and pinpoint their misconceptions * educational tools, to help inform instructors' lecture preparation

Welcome to the National Center for Biomedical Ontology's BioPortal. BioPortal is a Web-based application for accessing and sharing biomedical ontologies. New features in BioPortal 2.0 include: * Full ontology navigation using Flash visualization * Web-service access to BioPortal content and capabilities, which enables developers to use our BioPortal services in their tools. * Ability to add Marginal Notes to classes in BioPortal ontologies, a feature that enables the community to comment on ontologies and to discuss their contents * Ability to create Point to Point Mappings between concepts in different BioPortal ontologies * Bulk export of ontology-to-ontology mappings in RDF format * Navigation of multiple ontologies, which enables users to have several ontologies opened simultaneously in different tabs in the user interface * URIs for all ontology content, which enable developers to access and share BioPortal content from their applications * Improved support through Protégé for ontologies in OWL format

ESSENCE is an immersive internet experiment, and a face-face conference. It invites human-centred technologists, climate scientists, policymakers, and any other stakeholder with a view on some part of the climate change debate, to experience and reflect on a new generation of software tools. Build, structure, summarise and navigate the science and policy arguments underpinning climate challenge. Think of it as a visual Wikipedia, a collective intelligence, to organise the key issues, options and arguments.

A new web tool is being used to help foster sensible debate about the conflict in Gaza. Debategraph is a browser-based web application that gives a visual representation of the intricate arguments and issues in a heated debate - more recently being used to create order from the chaos surrounding the crisis in Gaza.

World Wind lets you zoom from satellite altitude into any place on Earth. Leveraging Landsat satellite imagery and Shuttle Radar Topography Mission data, World Wind lets you experience Earth terrain in visually rich 3D, just as if you were really there.

A semantic web experiment with a focus on Ontology Visualisation and Querying.

The Network Workbench Community Wiki is the part of Network Workbench (NWB) project. It provides descriptions for algorithms and datasets that have been integrated in the NWB Tool. It is also a place for users of the NWB Tool, the Cyberinfrastructure Shell, or any other CIShell based program to get, upload, and request algorithms & datasets to be used in the tool. This site is a sounding board to be used by the community to work together and create a tool which will meet their needs and the needs of the scientific community at large.