Geotime for a Patrol
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Geotime As an Adjunct Analysis Tool for Social Media Threat Analysis and Investigations for the Boston Police Department Offeror: Uncharted Software Inc
GeoTime as an Adjunct Analysis Tool for Social Media Threat Analysis and Investigations for the Boston Police Department Offeror: Uncharted Software Inc. 2 Berkeley St, Suite 600 Toronto ON M5A 4J5 Canada Business Type: Canadian Small Business Jurisdiction: Federally incorporated in Canada Date of Incorporation: October 8, 2001 Federal Tax Identification Number: 98-0691013 ATTN: Jenny Prosser, Contract Manager, [email protected] Subject: Acquiring Technology and Services of Social Media Threats for the Boston Police Department Uncharted Software Inc. (formerly Oculus Info Inc.) respectfully submits the following response to the Technology and Services of Social Media Threats RFP. Uncharted accepts all conditions and requirements contained in the RFP. Uncharted designs, develops and deploys innovative visual analytics systems and products for analysis and decision-making in complex information environments. Please direct any questions about this response to our point of contact for this response, Adeel Khamisa at 416-203-3003 x250 or [email protected]. Sincerely, Adeel Khamisa Law Enforcement Industry Manager, GeoTime® Uncharted Software Inc. [email protected] 416-203-3003 x250 416-708-6677 Company Proprietary Notice: This proposal includes data that shall not be disclosed outside the Government and shall not be duplicated, used, or disclosed – in whole or in part – for any purpose other than to evaluate this proposal. If, however, a contract is awarded to this offeror as a result of – or in connection with – the submission of this data, the Government shall have the right to duplicate, use, or disclose the data to the extent provided in the resulting contract. GeoTime as an Adjunct Analysis Tool for Social Media Threat Analysis and Investigations 1. -
Arcgis® + Geotime®: GIS Technology to Support the Analysis Of
® ® In many application areas, this is not enough: Geo- spatial and temporal correlations between the data ArcGIS + GeoTime : GIS technology should be studied, so that, on the basis of this insight, the available data - more and more numerous - can to support the analysis of telephone be translated into knowledge and therefore in appropriate decisions . In the area of security, to name an example, all this results in the predictive traffic data analysis of the spatial-temporal occurrence of crimes. Lastly, a technologically advanced GIS platform must Giorgio Forti, Miriam Marta, Fabrizio Pauri ® ensure data sharing and enable the world of mobile devices (system of engagement). ® There are several ways to share data / information, all supported by ArcGIS, such as: sharing within a single Historical mobile phone traffic billboards analysis is organization, according to the profiles assigned becoming increasingly important in investigative Figure 2: Sample data representation of two (identity); the sharing of multiple organizations that activities of public security organizations around the cellphone users in GeoTime may / should share confidential data (a very common world, and leading technology companies have been situation in both Public Security and Emergency trying to respond to the strong demand for the most Other predefined analysis features are already Management); public communication, open to all (for suitable tools for supporting such activities. available (automatic cluster search, who attends sites example, to report investigative success, or to of investigation interest, mobility compatibility with communicate to citizens unsafe areas for the Originally developed as a project funded in the United participation in events, etc.), allowing considerable frequency of criminal offenses). -
Stories in Geotime
Stories in GeoTime Ryan Eccles, Thomas Kapler, Robert Harper, William Wright Information Visualization ( 2008 ) © Stefan John 2008 Summer term 2008 1 Introduction • Story a powerful abstraction − Used by intelligence analysts to conceptualize threats and understand patterns − Part of the analytical process • Oculus Info’s GeoTime™ − Geo-temporal event visualization tool − Augmented with story system − Narratives, hypertext-linked visualizations, visual annotations, and pattern detection − Environment for analytic exploration and communication − Detects geo-temporal patterns − Integrates story narration to increase analytic sense-making cohesion Summer term 2008 2 1 Introduction • Assisting the analyst in: − Identifying, − Extracting, − Arranging, and − Presenting stories within the data • Story system − Lets analysts operate at story level − Higher level abstractions of data (behaviors and events) − Staying connected to the evidence − Developed in collaboration with analysts • Formal evaluation showed high utility and usability Summer term 2008 3 Overview • Storytelling • Related Work • Geo-Temporal Visualization in GeoTime • Stories in GeoTime • Evaluation Summer term 2008 4 2 Storytelling • First described in Aristotle’s Poetics − Objects of a tragedy (story): - Plot -> arrangements of incidents -Character - Thought -> processes of reasoning leading characters to their respective behavior • Narrative theory suggests: − People are essentially storytellers − Implicit ability to evaluate a story for: - Consistency -Detail - Structure Summer -
Harvard University Center for Geographic Analysis Newsletter November 2009
Harvard University Center for Geographic Analysis Newsletter November 2009 CENTER FOR GEOGRAPHIC ANALYSIS NEWSLETTER November 2009 ******************************************************************************** HIGHLIGHTS • CGA 2010 Conference Announcement: Research on Religion • Getty Thesaurus of Geographic Names available for Harvard Use • GeoTime Software Available for Trial • Harvard University Web Map • HealthMap on the iPhone • UCGIS 2010 Winter Meeting • Call for Papers: GIScience Research Track • 2010 GeoDesign Summit • Geography of a Recession • WorldView-2 Satellite Launch • Cartography 2.0 • Reverse Geocoding • Whatever Map • Satellite Image Search Tool • ScanEx Oil Spill Monitoring Project • Diversitydata.org • Google’s Free Navigation Service for Cellphones More... ******************************************************************************** CGA NEWS *CGA 2010 Conference Announcement: Research on Religion* The CGA is pleased to announce our co-sponsored 2010 conference: “New Technologies and Interdisciplinary Research on Religion” to be held March 12-13, 2010. The conference is organized by the Political Economy of Religion Program, Taubman Center, Harvard Kennedy School of Government, and co- sponsored by the Center for Geographic Analysis, Institute for Quantitative Social Science, Harvard University, as well as the Sigma Xi Harvard Chapter. Conference presentations will focus on combining the content of research on religion with database design, geo-referencing, social network analysis, text-mining, remote-sensing, -
An Interview with Visualization Pioneer Ben Shneiderman
6/23/2020 The purpose of visualization is insight, not pictures: An interview with visualization pioneer Ben Shneiderman The purpose of visualization is insight, not pictures: An interview with visualization pioneer Ben Shneiderman Jessica Hullman Follow Mar 12, 2019 · 13 min read Few people in visualization research have had careers as long and as impactful as Ben Shneiderman. We caught up with Ben over email in between his travels to get his take on visualization research, what’s worked in his career, and his advice for practitioners and researchers. Enjoy! Multiple Views: One of the main purposes of this blog is to explain to people what visualization research is to practitioners and, possibly, laypeople. How would you answer the question “what is visualization research”? Ben S: First let me define information visualization and its goals, then I can describe visualization research. Information visualization is a powerful interactive strategy for exploring data, especially when combined with statistical methods. Analysts in every field can use interactive information visualization tools for: more effective detection of faulty data, missing data, unusual distributions, and anomalies deeper and more thorough data analyses that produce profounder insights, and richer understandings that enable researchers to ask bolder questions. Like a telescope or microscope that increases your perceptual abilities, information visualization amplifies your cognitive abilities to understand complex processes so as to support better decisions. In our best -
Poster Summary
Grand Challenge Award 2008: Support for Diverse Analytic Techniques - nSpace2 and GeoTime Visual Analytics Lynn Chien, Annie Tat, Pascale Proulx, Adeel Khamisa, William Wright* Oculus Info Inc. ABSTRACT nSpace2 allows analysts to share TRIST and Sandbox files in a GeoTime and nSpace2 are interactive visual analytics tools that web environment. Multiple Sandboxes can be made and opened were used to examine and interpret all four of the 2008 VAST in different browser windows so the analyst can interact with Challenge datasets. GeoTime excels in visualizing event patterns different facets of information at the same time, as shown in in time and space, or in time and any abstract landscape, while Figure 2. The Sandbox is an integrating analytic tool. Results nSpace2 is a web-based analytical tool designed to support every from each of the quite different mini-challenges were combined in step of the analytical process. nSpace2 is an integrating analytic the Sandbox environment. environment. This paper highlights the VAST analytical experience with these tools that contributed to the success of these The Sandbox is a flexible and expressive thinking environment tools and this team for the third consecutive year. where ideas are unrestricted and thoughts can flow freely and be recorded by pointing and typing anywhere [3]. The Pasteboard CR Categories: H.5.2 [Information Interfaces & Presentations]: sits at the bottom panel of the browser and relevant information User Interfaces – Graphical User Interfaces (GUI); I.3.6 such as entities, evidence and an analyst’s hypotheses can be [Methodology and Techniques]: Interaction Techniques. copied to it and then transferred to other Sandboxes to be assembled according to a different perspective for example. -
Treemap Art Project
EVERY ALGORITHM HAS ART IN IT Treemap Art Project By Ben Shneiderman Visit Exhibitions @ www.cpnas.org 2 tree-structured data as a set of nested rectangles) which has had a rippling impact on systems of data visualization since they were rst conceived in the 1990s. True innovation, by denition, never rests on accepted practices but continues to investigate by nding new In his book, “Visual Complexity: Mapping Patterns of perspectives. In this spirit, Shneiderman has created a series Information”, Manuel Lima coins the term networkism which of prints that turn our perception of treemaps on its head – an he denes as “a small but growing artistic trend, characterized eort that resonates with Lima’s idea of networkism. In the by the portrayal of gurative graph structures- illustrations of exhibition, Every AlgoRim has ART in it: Treemap Art network topologies revealing convoluted patterns of nodes and Project, Shneiderman strips his treemaps of the text labels to links.” Explaining networkism further, Lima reminds us that allow the viewer to consider their aesthetic properties thus the domains of art and science are highly intertwined and that laying bare the fundamental property that makes data complexity science is a new source of inspiration for artists and visualization eective. at is to say that the human mind designers as well as scientists and engineers. He states that processes information dierently when it is organized visually. this movement is equally motivated by the unveiling of new In so doing Shneiderman seems to daringly cross disciplinary is exhibit is a project of the knowledge domains as it is by the desire for the representation boundaries to wear the hat of the artist – something that has Cultural Programs of the National Academy of Sciences of complex systems. -
The Eyes Have It: a Task by Data Type Taxonomy for Information Visualizations
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations Ben Shneiderman Department of Computer Science, Human-Computer Interaction Laboratory, and Institute for Systems Research University of Maryland College Park, Maryland 20742 USA ben @ cs.umd.edu keys), are being pushed aside by newer notions of Abstract information gathering, seeking, or visualization and data A useful starting point for designing advanced graphical mining, warehousing, or filtering. While distinctions are user interjaces is the Visual lnformation-Seeking Mantra: subtle, the common goals reach from finding a narrow set overview first, zoom and filter, then details on demand. of items in a large collection that satisfy a well-understood But this is only a starting point in trying to understand the information need (known-item search) to developing an rich and varied set of information visualizations that have understanding of unexpected patterns within the collection been proposed in recent years. This paper offers a task by (browse) (Marchionini, 1995). data type taxonomy with seven data types (one-, two-, Exploring information collections becomes three-dimensional datu, temporal and multi-dimensional increasingly difficult as the volume grows. A page of data, and tree and network data) and seven tasks (overview, information is easy to explore, but when the information Zoom, filter, details-on-demand, relate, history, and becomes the size of a book, or library, or even larger, it extracts). may be difficult to locate known items or to browse to gain an overview, Designers are just discovering how to use the rapid and Everything points to the conclusion that high resolution color displays to present large amounts of the phrase 'the language of art' is more information in orderly and user-controlled ways. -
Christopher L. North – Curriculum Vitae (Updated Sept 2014)
Christopher L. North – Curriculum Vitae (updated Sept 2014) Department of Computer Science (540) 231-2458 114 McBryde Hall (540) 231-9218 fax Virginia Tech north @ vt . edu Blacksburg, VA 24061-0106 http://www.cs.vt.edu/~north/ Google Scholar: • http://scholar.google.com/citations?user=yBZ7vtkAAAAJ • h-index = 35 Short Bio: Dr. Chris North is a Professor of Computer Science at Virginia Tech. He is Associate Director of the Discovery Analytics Center, and leads the Visual Analytics research group. He is principle architect of the GigaPixel Display Laboratory, one of the most advanced display and interaction facilities in the world. He also participates in the Center for Human-Computer Interaction, and the Hume Center for National Security, and is a member of the DHS supported VACCINE Visual Analytics Center of Excellence. He was awarded Faculty Fellow of the College of Engineering in 2007, and the Dean’s Award for Research Excellence in 2014. He earned his Ph.D. at the University of Maryland, College Park, in 2000. He has served as General Co-Chair of IEEE VisWeek 2009, and as Papers Chair of the IEEE Information Visualization (InfoVis) and IEEE Visual Analytics Science and Technology (VAST) Conferences. He has served on the editorial boards of IEEE Transactions on Visualization and Computer Graphics (TVCG), the Information Visualization journal, and Foundations and Trends in HCI. He has been awarded over $6M in grants, co-authored over 100 peer-reviewed publications, and delivered 3 keynote addresses at symposia in the field. He has graduated 8 Ph.D. and 14 M.S. thesis students, 4 receiving outstanding research awards at Virginia Tech, and advised over 70 undergraduate research students including several award winners at Virginia Tech’s annual undergraduate research symposium. -
Geotime Product Evaluation Lex Berman, CGA 12 Dec 09 Abstract
GeoTime Product Evaluation Lex Berman, CGA 12 Dec 09 Abstract: GeoTime is a stand-alone spatio-temporal browser with built-in queries for analyzing imported datasets containing events with defined spatial and temporal footprints. Events can be viewed as discrete points in a 3D space- time cube (with the the z-value representing the time axis), or can be viewed as entities (which are comprised of multiple location-events). The current version of GeoTime can directly load tables and flat files (including KML), but must be used together with ESRI ArcGIS to load from shapefiles and layers. Installation : The installation package for GeoTime includes an executable installer (for Windows only), a license file, and a third-party map library application, called MapMan. For GeoTime to run with ESRI files, both ArcGIS 9.2 or 9.3 must be installed, along with .NET, and Excel. Installation on ArcGIS 9.3 worked as expected during testing, but failed to completely integrate with ArcGIS 9.2 (due to an error with ESRI .NET assemblies). On the ArcGIS 9.3 install, the application worked for the administrator user profile only. It was not clear how to install the application for all user profiles. There are some options for installing the application with a license server, presumably to run as a keyed application over a limited subnet group of machines. However, since we are using the trial-period stand-alone client we don't know the level of difficulty in getting the license server (third-party software) to run. The MapMan package, included with GeoTime, takes considerably longer than GeoTime to install. -
Human-Centered Artificial Intelligence: Three Fresh Ideas
AIS Transactions on Human-Computer Interaction Volume 12 Issue 3 Article 1 9-30-2020 Human-Centered Artificial Intelligence: Three Fresh Ideas Ben Shneiderman University of Maryland, [email protected] Follow this and additional works at: https://aisel.aisnet.org/thci Recommended Citation Shneiderman, B. (2020). Human-Centered Artificial Intelligence: Three Fresh Ideas. AIS Transactions on Human-Computer Interaction, 12(3), 109-124. https://doi.org/10.17705/1thci.00131 DOI: 10.17705/1thci.00131 This material is brought to you by the AIS Journals at AIS Electronic Library (AISeL). It has been accepted for inclusion in AIS Transactions on Human-Computer Interaction by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact [email protected]. Transactions on Human-Computer Interaction 109 Transactions on Human-Computer Interaction Volume 12 Issue 3 9-2020 Human-Centered Artificial Intelligence: Three Fresh Ideas Ben Shneiderman Department of Computer Science and Human-Computer Interaction Lab, University of Maryland, College Park, [email protected] Follow this and additional works at: http://aisel.aisnet.org/thci/ Recommended Citation Shneiderman, B. (2020). Human-centered artificial intelligence: Three fresh ideas. AIS Transactions on Human- Computer Interaction, 12(3), pp. 109-124. DOI: 10.17705/1thci.00131 Available at http://aisel.aisnet.org/thci/vol12/iss3/1 Volume 12 pp. 109 – 124 Issue 3 110 Transactions on Human-Computer Interaction Transactions on Human-Computer Interaction Research Commentary DOI: 10.17705/1thci.00131 ISSN: 1944-3900 Human-Centered Artificial Intelligence: Three Fresh Ideas Ben Shneiderman Department of Computer Science and Human-Computer Interaction Lab, University of Maryland, College Park [email protected] Abstract: Human-Centered AI (HCAI) is a promising direction for designing AI systems that support human self-efficacy, promote creativity, clarify responsibility, and facilitate social participation. -
Visual Analytics for Maritime Domain Awareness
Visual Analytics for Maritime Domain Awareness Valérie Lavigne, Denis Gouin Michael Davenport Defence R&D Canada - Valcartier Salience Analytics Inc. Québec (QC), Canada Vancouver (BC), Canada Abstract—Maintaining situation awareness in the maritime domain is a challenging mandate. Task analysis activities were III. VISUAL ANALYTICS conducted to identify where visual analytics science and Thomas and Cook define VA as “the science of analytical technology could improve maritime domain awareness and reasoning facilitated by interactive visual interfaces” [3]. The reduce information overload. Three promising opportunities goal of VA is to facilitate high-quality human judgement with a were identified: the visualization of normal maritime behaviour, limited investment of the analyst’s time. According to them, anomaly detection, and the collaborative analysis of a vessel of people use VA tools and techniques to: interest. In this paper, we describe the result of our user studies along with potential visual analytics solutions and features • “synthesize information and derive insight from considered for a maritime analytics prototype. massive, dynamic, ambiguous and often conflicting data; Keywords-visual analytics; maritime domain awareness; anomaly detection; situation analysis; collaborative work. • detect the expected and discover the unexpected; • provide timely, defensible, and understandable I. INTRODUCTION assessments; In this paper, we report on the results of work conducted by • Defence R&D Canada (DRDC) in the exploration of Visual communicate assessment effectively for action.” [3] Analytics (VA) solutions to real world maritime challenges and VA can help analyze entity behaviour, known patterns, and describe the design of a Maritime Analytics Prototype (MAP) the links between them. implementing VA features that will enable better situation understanding.