Information Technologies Considered Important for Counterterrorism

Size: px
Start display at page:

Download "Information Technologies Considered Important for Counterterrorism"

Transcription

1 EXHIBIT W8.1 Information Technology Biometrics Categorization, Clustering Database Processing Event Detection and Notification Geospatial Information Exploitation Information Management and Filtering Infrastructure Knowledge Management, Context Development Predictive Modeling Publishing Searching Semantic Consistency, Resolving Terms Chapter Eight 1 Information Technologies Considered Important for Counterterrorism Description Identity and/or verify human terrorist (or watchlist) subjects using 2D and 3D modeling approaches over a variety of biometric signatures: face, gait, iris, fingerprint, voice. Also exploit multiple sensor modalities, EQ, IR, radar, hyper-spectral. Employ numerous technical approaches (natural language processing, AI, machine learning, pattern recognition, statistical analysis, probabilistic techniques) to automatically extract meaning and key concepts from (un)structured data and categorize via an information model (taxonomy, ontology). Cluster documents with similar content. Ensure platform, syntactic and semantic consistency, and interoperability of multiple types of data stored on multiple storage media (disk, optical, tape) and across multiple database management systems. Desirable aspects include flexible middleware for: data location transparency and uncertainty management, linguistically relevant querying tuned for knowledge discovery and monitoring scalability and mediation, scheme evolution and metadata management, and structuring unstructured data. Monitor simple and complex events and notify users (or applications) in real time of their detection. Monitoring can be scheduled a priori, or placed on an ad hoc basis driven by user demands. When an event is detected, automatic notifications can range from simple actions (sending an alert, page, or ) to more complex ones (feeding information into an analytics system). Fuse, overlay, register, search, analyze, annotate, and visualize high-resolution satellite and aerial imagery, elevation data, GPS coordinates, maps, demographics, land masses, and political boundaries to deliver a streaming 3D map of the entire globe. Collect, ingest, index, store, retrieve, extract, integrate, analyze, aggregate, display, and distribute semantically enhanced information from a wide variety of sources. Allow for simultaneous search of any number of information sources, sorting and categorizing various items of information according to query relevance. Provide an overall view of the different topics related to the request, along with the ability to visualize the semantic links relating the various items of information to each other. Provide comprehensive infrastructure for capturing, managing, and transferring knowledge and business processes that link enterprise software packages, legacy systems, databases, workflows, and Web services, both within and across enterprises. Important technologies include Web services, service-oriented grid-computing concepts, extensible component-based modules, P2P techniques, and platforms ranging from enterprise servers to wireless PDAs, Java, and Microsoft.net implementations. Use Semantic Web, associative memory, and related technologies to model and make explicit (expose via Web services) an analyst s personal preferences, intellectual capital, multidimensional knowledge, and tacit understanding of a problem domain. Predict future terrorist behaviors, events, and attacks, based on past examples and by exploiting a variety of promising approaches, including neural networks, AI, behavioral sciences techniques, subject matter expertise, and red teams. Generate concise accurate summaries of recent newsworthy items, ensuring users see topics only once, regardless of how many times the item appears in data or in the press. Allow users to perform more complete and meaningful searches (free text, semantic, similarity, partial or exact match) across a multitude of geographically dispersed, multilingual, and diverse (un)structured information repositories within and across enterprises (any document type located on file servers, groupware systems, databases, document management systems, Web servers). Exploit ontologies, taxonomies, and definitions for words, phrases, and acronyms using a variety of schemes so users have a common and consistent understanding of the meaning of words in a specific context. Resolve semantic heterogeneity by capitalizing on Semantic Web technologies.

2 2 Part 4 EXHIBIT W8.1 Information Technology Video Processing Visualization Workflow Management Description Analyze, detect, extract, and digitally enhance (reduce noise, improve image color and contrast, and increase resolution in selected areas) user-specified behaviors or activities in video (suspicious terrorist-related activities). Provide graphical displays, information landscapes, time-based charts, and built-in drill-down tools to help analysts and investigators discover, discern, and visualize networks of interrelated information (associations between words, concepts, people, places, or events) or visually expose nonobvious patterns, relationships, and anomalies from large data sets. Create optimized workflows and activities-based business process maps using techniques such as intelligent AI engines by watching, learning, and recording/logging the activities of multiple users using multiple applications in multiple sessions. Source: Popp, R., et al. Countering Terrorism Through Information Technology. Communications of the ACM, March AMC, Inc. Used with permission.

3 EXHIBIT W8.2 Chapter Eight 3 Classification of Dimensions of Virtual Learning Environments (VLEs) Dimension Definition Comparison Time The timing of instruction. VLEs free When instruction is delivered asynchronously in a VLE, participants participant from time constraints. retain control as to when they engage in the learning experience. Learners determine the time and pace of instruction. Place The physical location of instruction. Participants access the learning material and communicate with VLEs free participants from geographical classmates and instructors through networked resources and a constraints. computer-based interface, rather than face-to-face in a classroom. Space The collection of materials and resources While it is feasible to expand the traditional model of classroomavailable to the learner. VLEs provide based instruction to include the variety of resources available in access to a wide array of resources. VLEs (Leidner and Jarvenpaa 1993, 1995), generally these materials remain only a secondary resource in instructor-led classroom education. Technology The collection of tools used to deliver In VLEs technology is used to deliver learning material and to learning material and to facilitate facilitate many-to-many communication among distributed communication among participants. participants. Text, hypertext, graphics, streaming audio and video, computer animations and simulations, embedded tests, and dynamic content are some examples of delivery technology. Electronic mail, online threaded discussion boards, synchronous chat, and desktop videoconferencing are some examples of communication technology. Interaction The degree of contact and educational VLEs rely on information and communication technology to create exchange among learners and between the venue of knowledge transfer and learning progress. Unlike learners and instructors. computer microworlds, VLEs are open systems that allow for communication and interaction among the participants. Unlike traditional classroom education, VLEs support student-to-student and student-to-instructor connectivity throughout the learning experience in a technology-mediated setting. Control The extent to which the learner can A certain degree of learner control can be built into traditional control the instructional presentation. classroom instruction, but VLEs have the potential to provide far Control is a continuum enabling the greater personalization of instruction and a much higher degree of design of varying degrees of learner learner control than traditional classroom education. Traditional control. learning environments allow students, when outside of the classroom, to control the pace and sequence of material, and the time and place of their study. VLEs, however, provide this flexibility during instruction as well. Source: Table 1 from G. Piccoli, R. Ahmad, and B. Ives, et al. Classifications of E-Learning Environments, MIS Quarterly, (25:4), 2001, pp Copyright 2001 by the Regents of the University of Minnesota. Reprinted with permission.

4 4 Part 4 EXHIBIT W8.3 Knowledge Principles Knowledge Is Not Merely Data Descriptive data are not enough for purposes of decision making. Analysis is required to turn data into patterns (insights) and understanding. Knowledge Needs to Change as the World Changes Knowledge, as stock, rarely remains stagnant: beliefs and assumptions change over time. We need to keep what we know in sync with change in the world around us. Knowledge Processes Require Reasoning Transforming data into patterns (insight) requires inferences and judgments in short, thinking. There is a need to organize and aid how individuals and groups engage in thinking, etc. Knowledge Is Often Implicit or Tacit We know more about customers, technology, etc., than we can articulate. A lot of know-how remains tacit but is critical to what we do and how we do it. Knowledge Cannot Be Separated from the Knowers We cannot separate what we know from the individuals who know it. It is largely impossible to separate what we know from what we do in our day-today work and lives. Knowing and doing are intimately interconnected (to the point that it is terribly difficult to disentangle how they influence each other). Knowledge Is Difficult and Often Impossible to Manage Directly We can only manage knowledge through influencing the knower. We can manage knowledge indirectly by managing the organization: its culture, people, technologies, structures, and systems, strategies, etc. By managing these factors, we can indirectly manage knowledge stock (what individuals and groups know) and knowledge flow (how knowledge moves between and among individuals and groups). KM-Enabling Technologies Knowledge Methods and Tools Mentoring: Communicates the organization s values, norms, and practices; exposes tacit understanding of how the world works. Training and Development: Convey explicit knowledge in many different types of settings; expose shared tacit viewpoints. Comprise groups of individuals, often from multiple disciplines or silos, who come together to share what they know, to learn together. A Knowledge Project: Brings a group of individuals together with a declared and visible focus and intent to generate a stock of required knowledge. A Knowledge Repository: Provides a central location for various knowledge products such as best practices, or analysis of different topics; individuals and groups develop products for the repository, and they in turn provide inputs for further discussion and reflection on the part of others. Communities of Practice: Make up a group of individuals who share the same values and intent, work on a collective project or endeavor, and share openly and critically with each other. Intermediary Roles: Are held by one or more individuals who take responsibility for developing a specific stock of knowledge, a plan to share it with others, etc. Storytelling: Is done by developing a story about how some things happen around here or what we did in this project as a way to communicate a sense of purpose, to espouse shared values, and to get at more implicit forms of knowledge. Collaboration: Formally gets a set of individuals to come together around a specific task or project so that they can learn from each other. Social Network Analysis: Identifies and communicates who speaks to whom, and how information is transmitted from one individual to another, or from one group or department to another. Scenarios: Brings individuals both from inside and outside the organization to develop explicit stocks of knowledge about the future (such as how an industry might evolve or how a set of technologies might converge over time). Knowledge Mapping: Identifies who knows what, how stocks of knowledge are related to each other, how the information is stored and where, etc. Experiments: Allow one or more individuals to do something on a small scale that otherwise would not be done as a means to learn about (for example) how electronic connections might work, what data they might generate, or how customers or others might engage with different forms of electronic connections.

5 Chapter Eight 5 EXHIBIT W8.3 Knowledge Principles Knowledge Types: Can be explicit, meaning objective, documented and clear. Or it can be tacit, which is subjective, stored insights and experiences. Knowledge Methods Knowledge Server: Contains KM software, including knowledge repository, and provides access to knowledge. Enterprise Knowledge Portal: A single access point into a KM system; organizes unstructured information and knowledge. Knowledge-Harvesting Tools: Capture organizational knowledge unobtrusively. Electronic Document Management: Allows user to access documents over the Internet; allows electronic collaboration on document creation, revision, or sharing. Source: Fahey, L., et al. Linking E-Business and Operating Processes: The Role of KM. IBM Systems Journals 40, no. 4 (2001). EXHIBIT W8.4 Summary of the P2P Business and Service Models Performance Measurement P2P Service Model Success Factors Customer Base Revenues Layer 3: Business Model Create and maximize revenues Customer Acquisition Revenue Generation Content Selection (variety and quality) Transaction Volume Implementation of P2P Function Degree of User Friendliness Layer 2: Community Share as much useful content as possible Layer 1: Technology Allow users to communicate and exchange content Value Creation Value Distribution Technical Feasibility Usability Source: Kwok, S. H., et al. Peer-to-Peer Technology Business and Service Models: Risks and Opportunities. Electronic Markets 12, no. 3 (2002). Courtesy of Taylor & Francis Ltd., tandf.co.uk.journals.

Session Two. Organizational Knowledge Management

Session Two. Organizational Knowledge Management Knowledge Management Session Two Organizational Knowledge Management Intellectual capital Intellectual capital is combination of the Intellectual property (IP) held by a business and the people in that

More information

The Future of Business Analytics is Now! 2013 IBM Corporation

The Future of Business Analytics is Now! 2013 IBM Corporation The Future of Business Analytics is Now! 1 The pressures on organizations are at a point where analytics has evolved from a business initiative to a BUSINESS IMPERATIVE More organization are using analytics

More information

Lotus and IBM Knowledge Management Strategy

Lotus and IBM Knowledge Management Strategy Lotus and IBM Knowledge Management Strategy An Overview September 2000 A Lotus Development Corporation White Paper Copyright 2000 Lotus Development Corporation. All rights reserved. Not for reproduction

More information

A Systemic Artificial Intelligence (AI) Approach to Difficult Text Analytics Tasks

A Systemic Artificial Intelligence (AI) Approach to Difficult Text Analytics Tasks A Systemic Artificial Intelligence (AI) Approach to Difficult Text Analytics Tasks Text Analytics World, Boston, 2013 Lars Hard, CTO Agenda Difficult text analytics tasks Feature extraction Bio-inspired

More information

What do Big Data & HAVEn mean? Robert Lejnert HP Autonomy

What do Big Data & HAVEn mean? Robert Lejnert HP Autonomy What do Big Data & HAVEn mean? Robert Lejnert HP Autonomy Much higher Volumes. Processed with more Velocity. With much more Variety. Is Big Data so big? Big Data Smart Data Project HAVEn: Adaptive Intelligence

More information

Knowledge Management System Architecture For Organizational Learning With Collaborative Environment

Knowledge Management System Architecture For Organizational Learning With Collaborative Environment Proceedings of the Postgraduate Annual Research Seminar 2005 1 Knowledge Management System Architecture For Organizational Learning With Collaborative Environment Rusli Haji Abdullah δ, Shamsul Sahibuddin

More information

Text Mining - Scope and Applications

Text Mining - Scope and Applications Journal of Computer Science and Applications. ISSN 2231-1270 Volume 5, Number 2 (2013), pp. 51-55 International Research Publication House http://www.irphouse.com Text Mining - Scope and Applications Miss

More information

Course 803401 DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

Course 803401 DSS. Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Oman College of Management and Technology Course 803401 DSS Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization CS/MIS Department Information Sharing

More information

IO Informatics The Sentient Suite

IO Informatics The Sentient Suite IO Informatics The Sentient Suite Our software, The Sentient Suite, allows a user to assemble, view, analyze and search very disparate information in a common environment. The disparate data can be numeric

More information

PSG College of Technology, Coimbatore-641 004 Department of Computer & Information Sciences BSc (CT) G1 & G2 Sixth Semester PROJECT DETAILS.

PSG College of Technology, Coimbatore-641 004 Department of Computer & Information Sciences BSc (CT) G1 & G2 Sixth Semester PROJECT DETAILS. PSG College of Technology, Coimbatore-641 004 Department of Computer & Information Sciences BSc (CT) G1 & G2 Sixth Semester PROJECT DETAILS Project Project Title Area of Abstract No Specialization 1. Software

More information

How To Use Data Mining For Knowledge Management In Technology Enhanced Learning

How To Use Data Mining For Knowledge Management In Technology Enhanced Learning Proceedings of the 6th WSEAS International Conference on Applications of Electrical Engineering, Istanbul, Turkey, May 27-29, 2007 115 Data Mining for Knowledge Management in Technology Enhanced Learning

More information

Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

More information

Sustainable Development with Geospatial Information Leveraging the Data and Technology Revolution

Sustainable Development with Geospatial Information Leveraging the Data and Technology Revolution Sustainable Development with Geospatial Information Leveraging the Data and Technology Revolution Steven Hagan, Vice President, Server Technologies 1 Copyright 2011, Oracle and/or its affiliates. All rights

More information

BUSINESS VALUE OF SEMANTIC TECHNOLOGY

BUSINESS VALUE OF SEMANTIC TECHNOLOGY BUSINESS VALUE OF SEMANTIC TECHNOLOGY Preliminary Findings Industry Advisory Council Emerging Technology (ET) SIG Information Sharing & Collaboration Committee July 15, 2005 Mills Davis Managing Director

More information

Managing Large Imagery Databases via the Web

Managing Large Imagery Databases via the Web 'Photogrammetric Week 01' D. Fritsch & R. Spiller, Eds. Wichmann Verlag, Heidelberg 2001. Meyer 309 Managing Large Imagery Databases via the Web UWE MEYER, Dortmund ABSTRACT The terramapserver system is

More information

KEY KNOWLEDGE MANAGEMENT TECHNOLOGIES IN THE INTELLIGENCE ENTERPRISE

KEY KNOWLEDGE MANAGEMENT TECHNOLOGIES IN THE INTELLIGENCE ENTERPRISE KEY KNOWLEDGE MANAGEMENT TECHNOLOGIES IN THE INTELLIGENCE ENTERPRISE RAMONA-MIHAELA MATEI Ph.D. student, Academy of Economic Studies, Bucharest, Romania ramona.matei1982@gmail.com Abstract In this rapidly

More information

HYPER MEDIA MESSAGING

HYPER MEDIA MESSAGING Email based document interchange known as messaging service and contribute to corporate productivity in following ways 1. it strengthens the automation of documentation life cycle 2. It allows document

More information

Virtual Team Collaboration Glossary

Virtual Team Collaboration Glossary Virtual Team Collaboration Glossary Steve Prahst, Rhonda Arterberrie, and Dennis Kay Knowledge Management and Collaborative Technologies Branch NASA Glenn Research Center Introduction Most NASA projects

More information

可 视 化 与 可 视 计 算 概 论. Introduction to Visualization and Visual Computing 袁 晓 如 北 京 大 学 2015.12.23

可 视 化 与 可 视 计 算 概 论. Introduction to Visualization and Visual Computing 袁 晓 如 北 京 大 学 2015.12.23 可 视 化 与 可 视 计 算 概 论 Introduction to Visualization and Visual Computing 袁 晓 如 北 京 大 学 2015.12.23 2 Visual Analytics Adapted from Jim Thomas s slides 3 Visual Analytics Definition Visual Analytics is the

More information

Important dimensions of knowledge Knowledge is a firm asset: Knowledge has different forms Knowledge has a location Knowledge is situational Wisdom:

Important dimensions of knowledge Knowledge is a firm asset: Knowledge has different forms Knowledge has a location Knowledge is situational Wisdom: Southern Company Electricity Generators uses Content Management System (CMS). Important dimensions of knowledge: Knowledge is a firm asset: Intangible. Creation of knowledge from data, information, requires

More information

Delivering Smart Answers!

Delivering Smart Answers! Companion for SharePoint Topic Analyst Companion for SharePoint All Your Information Enterprise-ready Enrich SharePoint, your central place for document and workflow management, not only with an improved

More information

Integrating Business Intelligence Module into Learning Management System

Integrating Business Intelligence Module into Learning Management System Integrating Business Intelligence Module into Learning Management System Mario Fabijanić and Zoran Skočir* Cognita Address: Radoslava Cimermana 64a, 10020 Zagreb, Croatia Telephone: 00 385 1 6558 440 Fax:

More information

ORACLE BUSINESS INTELLIGENCE SUITE ENTERPRISE EDITION PLUS

ORACLE BUSINESS INTELLIGENCE SUITE ENTERPRISE EDITION PLUS ORACLE BUSINESS INTELLIGENCE SUITE ENTERPRISE EDITION PLUS PRODUCT FACTS & FEATURES KEY FEATURES Comprehensive, best-of-breed capabilities 100 percent thin client interface Intelligence across multiple

More information

GEOG 482/582 : GIS Data Management. Lesson 10: Enterprise GIS Data Management Strategies GEOG 482/582 / My Course / University of Washington

GEOG 482/582 : GIS Data Management. Lesson 10: Enterprise GIS Data Management Strategies GEOG 482/582 / My Course / University of Washington GEOG 482/582 : GIS Data Management Lesson 10: Enterprise GIS Data Management Strategies Overview Learning Objective Questions: 1. What are challenges for multi-user database environments? 2. What is Enterprise

More information

Oracle Business Intelligence 11g Business Dashboard Management

Oracle Business Intelligence 11g Business Dashboard Management Oracle Business Intelligence 11g Business Dashboard Management Thomas Oestreich Chief EPM STrategist Tool Proliferation is Inefficient and Costly Disconnected Systems; Competing Analytic

More information

ORACLE BUSINESS INTELLIGENCE SUITE ENTERPRISE EDITION PLUS

ORACLE BUSINESS INTELLIGENCE SUITE ENTERPRISE EDITION PLUS Oracle Fusion editions of Oracle's Hyperion performance management products are currently available only on Microsoft Windows server platforms. The following is intended to outline our general product

More information

ORACLE FINANCIAL SERVICES ANALYTICAL APPLICATIONS INFRASTRUCTURE

ORACLE FINANCIAL SERVICES ANALYTICAL APPLICATIONS INFRASTRUCTURE ORACLE FINANCIAL SERVICES ANALYTICAL APPLICATIONS INFRASTRUCTURE KEY FEATURES Rich and comprehensive business metadata allows business users to interact with financial services data model to configure

More information

How To Make Sense Of Data With Altilia

How To Make Sense Of Data With Altilia HOW TO MAKE SENSE OF BIG DATA TO BETTER DRIVE BUSINESS PROCESSES, IMPROVE DECISION-MAKING, AND SUCCESSFULLY COMPETE IN TODAY S MARKETS. ALTILIA turns Big Data into Smart Data and enables businesses to

More information

Master big data to optimize the oil and gas lifecycle

Master big data to optimize the oil and gas lifecycle Viewpoint paper Master big data to optimize the oil and gas lifecycle Information management and analytics (IM&A) helps move decisions from reactive to predictive Table of contents 4 Getting a handle on

More information

Knowledge Management

Knowledge Management Knowledge Management Management Information Code: 164292-02 Course: Management Information Period: Autumn 2013 Professor: Sync Sangwon Lee, Ph. D D. of Information & Electronic Commerce 1 00. Contents

More information

Data Isn't Everything

Data Isn't Everything June 17, 2015 Innovate Forward Data Isn't Everything The Challenges of Big Data, Advanced Analytics, and Advance Computation Devices for Transportation Agencies. Using Data to Support Mission, Administration,

More information

MEDICAL DATA MINING. Timothy Hays, PhD. Health IT Strategy Executive Dynamics Research Corporation (DRC) December 13, 2012

MEDICAL DATA MINING. Timothy Hays, PhD. Health IT Strategy Executive Dynamics Research Corporation (DRC) December 13, 2012 MEDICAL DATA MINING Timothy Hays, PhD Health IT Strategy Executive Dynamics Research Corporation (DRC) December 13, 2012 2 Healthcare in America Is a VERY Large Domain with Enormous Opportunities for Data

More information

Adobe Insight, powered by Omniture

Adobe Insight, powered by Omniture Adobe Insight, powered by Omniture Accelerating government intelligence to the speed of thought 1 Challenges that analysts face 2 Analysis tools and functionality 3 Adobe Insight 4 Summary Never before

More information

CLOUD BASED SEMANTIC EVENT PROCESSING FOR

CLOUD BASED SEMANTIC EVENT PROCESSING FOR CLOUD BASED SEMANTIC EVENT PROCESSING FOR MONITORING AND MANAGEMENT OF SUPPLY CHAINS A VLTN White Paper Dr. Bill Karakostas Bill.karakostas@vltn.be Executive Summary Supply chain visibility is essential

More information

Proceedings of the 7th WSEAS International Conference on Distance Learning and Web Engineering, Beijing, China, September 15-17, 2007 310

Proceedings of the 7th WSEAS International Conference on Distance Learning and Web Engineering, Beijing, China, September 15-17, 2007 310 Proceedings of the 7th WSEAS International Conference on Distance Learning and Web Engineering, Beijing, China, September 15-17, 2007 310 E-learning Grid - An Online Learning Network FH CHOO, KL GAY, H

More information

Business Intelligence and Decision Support Systems

Business Intelligence and Decision Support Systems Chapter 12 Business Intelligence and Decision Support Systems Information Technology For Management 7 th Edition Turban & Volonino Based on lecture slides by L. Beaubien, Providence College John Wiley

More information

Chapter 5. Warehousing, Data Acquisition, Data. Visualization

Chapter 5. Warehousing, Data Acquisition, Data. Visualization Decision Support Systems and Intelligent Systems, Seventh Edition Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization 5-1 Learning Objectives

More information

Flattening Enterprise Knowledge

Flattening Enterprise Knowledge Flattening Enterprise Knowledge Do you Control Your Content or Does Your Content Control You? 1 Executive Summary: Enterprise Content Management (ECM) is a common buzz term and every IT manager knows it

More information

How Information Technology (IT) Can Support Knowledge- Sharing and Collaboration

How Information Technology (IT) Can Support Knowledge- Sharing and Collaboration How Information Technology (IT) Can Support Knowledge- Sharing and Collaboration Brian D. Murrow BDMurrow@us.ibm.com Agenda What is collaborative software? What are some of the common features? What products

More information

Data and Knowledge Management

Data and Knowledge Management Topic 7 Data and Knowledge Management LEARNING OUTCOMES By the end of this topic, you should be able to: 1. Differentiate between data, information and knowledge. 2. List the four sources of data and the

More information

Big Data and Analytics: Challenges and Opportunities

Big Data and Analytics: Challenges and Opportunities Big Data and Analytics: Challenges and Opportunities Dr. Amin Beheshti Lecturer and Senior Research Associate University of New South Wales, Australia (Service Oriented Computing Group, CSE) Talk: Sharif

More information

Building Effective Blended Learning Programs. Harvey Singh

Building Effective Blended Learning Programs. Harvey Singh Building Effective Blended Learning Programs Harvey Singh Introduction The first generation of e-learning or Web-based learning programs focused on presenting physical classroom-based instructional content

More information

Transforming the Telecoms Business using Big Data and Analytics

Transforming the Telecoms Business using Big Data and Analytics Transforming the Telecoms Business using Big Data and Analytics Event: ICT Forum for HR Professionals Venue: Meikles Hotel, Harare, Zimbabwe Date: 19 th 21 st August 2015 AFRALTI 1 Objectives Describe

More information

9. Technology in KM. ETL525 Knowledge Management Tutorial Four. 16 January 2009. K.T. Lam lblkt@ust.hk

9. Technology in KM. ETL525 Knowledge Management Tutorial Four. 16 January 2009. K.T. Lam lblkt@ust.hk 9. Technology in KM ETL525 Knowledge Management Tutorial Four 16 January 2009 K.T. Lam lblkt@ust.hk Last updated: 15 January 2009 Technology is KM Enabler Technology is one of the Four Pillars of KM, which

More information

An Enterprise Framework for Business Intelligence

An Enterprise Framework for Business Intelligence An Enterprise Framework for Business Intelligence Colin White BI Research May 2009 Sponsored by Oracle Corporation TABLE OF CONTENTS AN ENTERPRISE FRAMEWORK FOR BUSINESS INTELLIGENCE 1 THE BI PROCESSING

More information

UTILIZING COMPOUND TERM PROCESSING TO ADDRESS RECORDS MANAGEMENT CHALLENGES

UTILIZING COMPOUND TERM PROCESSING TO ADDRESS RECORDS MANAGEMENT CHALLENGES UTILIZING COMPOUND TERM PROCESSING TO ADDRESS RECORDS MANAGEMENT CHALLENGES CONCEPT SEARCHING This document discusses some of the inherent challenges in implementing and maintaining a sound records management

More information

E-Business Technologies for the Future

E-Business Technologies for the Future E-Business Technologies for the Future Michael B. Spring Department of Information Science and Telecommunications University of Pittsburgh spring@imap.pitt.edu http://www.sis.pitt.edu/~spring Overview

More information

Training Management System for Aircraft Engineering: indexing and retrieval of Corporate Learning Object

Training Management System for Aircraft Engineering: indexing and retrieval of Corporate Learning Object Training Management System for Aircraft Engineering: indexing and retrieval of Corporate Learning Object Anne Monceaux 1, Joanna Guss 1 1 EADS-CCR, Centreda 1, 4 Avenue Didier Daurat 31700 Blagnac France

More information

A Business Process Services Portal

A Business Process Services Portal A Business Process Services Portal IBM Research Report RZ 3782 Cédric Favre 1, Zohar Feldman 3, Beat Gfeller 1, Thomas Gschwind 1, Jana Koehler 1, Jochen M. Küster 1, Oleksandr Maistrenko 1, Alexandru

More information

Knowledge Management Enabling technologies

Knowledge Management Enabling technologies Knowledge Management Enabling technologies ICT support to KM Types of knowledge enabling technologies 3Cs of Knowledge Enabling Technologies References 1 According to Despres and Chauvel (2000), KM is

More information

Preservation for a Safer World

Preservation for a Safer World Preservation and Archiving Special Interest Group (PASIG) Preservation for a Safer World Hong-Eng Koh Senior Director (Global Lead) Justice & Public Safety A Very Fragmented World

More information

The SEEMP project Single European Employment Market-Place An e-government case study

The SEEMP project Single European Employment Market-Place An e-government case study The SEEMP project Single European Employment Market-Place An e-government case study 1 Scenario introduction Several e-government projects have been developed in the field of employment with the aim of

More information

Increase Agility and Reduce Costs with a Logical Data Warehouse. February 2014

Increase Agility and Reduce Costs with a Logical Data Warehouse. February 2014 Increase Agility and Reduce Costs with a Logical Data Warehouse February 2014 Table of Contents Summary... 3 Data Virtualization & the Logical Data Warehouse... 4 What is a Logical Data Warehouse?... 4

More information

How To Create An Insight Analysis For Cyber Security

How To Create An Insight Analysis For Cyber Security IBM i2 Enterprise Insight Analysis for Cyber Analysis Protect your organization with cyber intelligence Highlights Quickly identify threats, threat actors and hidden connections with multidimensional analytics

More information

Keywords Big Data; OODBMS; RDBMS; hadoop; EDM; learning analytics, data abundance.

Keywords Big Data; OODBMS; RDBMS; hadoop; EDM; learning analytics, data abundance. Volume 4, Issue 11, November 2014 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Analytics

More information

IBM Software Enabling business agility through real-time process visibility

IBM Software Enabling business agility through real-time process visibility IBM Software Enabling business agility through real-time process visibility IBM Business Monitor 2 Enabling business agility through real-time process visibility Highlights Understand the big picture of

More information

COLLABORATIVE PORTAL MODEL FOR INTERCULTURAL TEAMS KNOWLEDGE MANAGEMENT

COLLABORATIVE PORTAL MODEL FOR INTERCULTURAL TEAMS KNOWLEDGE MANAGEMENT COLLABORATIVE PORTAL MODEL FOR INTERCULTURAL TEAMS KNOWLEDGE MANAGEMENT Abstract Claudiu Brandas 1 In the multinational organizations, more groups of individuals are being involved in the process of knowledge

More information

W H I T E P A P E R. Security & Defense Solutions Intelligent Convergence with EdgeFrontier

W H I T E P A P E R. Security & Defense Solutions Intelligent Convergence with EdgeFrontier W H I T E P A P E R Security & Defense Solutions Intelligent Convergence with EdgeFrontier Contents 1. Introduction... 2 2. The Need for Intelligent Convergence... 3 2.1 Security Convergence with EdgeFrontier...

More information

Global Data Integration with Autonomous Mobile Agents. White Paper

Global Data Integration with Autonomous Mobile Agents. White Paper Global Data Integration with Autonomous Mobile Agents White Paper June 2002 Contents Executive Summary... 1 The Business Problem... 2 The Global IDs Solution... 5 Global IDs Technology... 8 Company Overview...

More information

Introduction. A. Bellaachia Page: 1

Introduction. A. Bellaachia Page: 1 Introduction 1. Objectives... 3 2. What is Data Mining?... 4 3. Knowledge Discovery Process... 5 4. KD Process Example... 7 5. Typical Data Mining Architecture... 8 6. Database vs. Data Mining... 9 7.

More information

A Grid Architecture for Manufacturing Database System

A Grid Architecture for Manufacturing Database System Database Systems Journal vol. II, no. 2/2011 23 A Grid Architecture for Manufacturing Database System Laurentiu CIOVICĂ, Constantin Daniel AVRAM Economic Informatics Department, Academy of Economic Studies

More information

Trends and Research Opportunities in Spatial Big Data Analytics and Cloud Computing NCSU GeoSpatial Forum

Trends and Research Opportunities in Spatial Big Data Analytics and Cloud Computing NCSU GeoSpatial Forum Trends and Research Opportunities in Spatial Big Data Analytics and Cloud Computing NCSU GeoSpatial Forum Siva Ravada Senior Director of Development Oracle Spatial and MapViewer 2 Evolving Technology Platforms

More information

Knowledge Management in Public Health. Nancy Dubois, NCCMT Consultant dubfit@rogers.com 519.446.3636

Knowledge Management in Public Health. Nancy Dubois, NCCMT Consultant dubfit@rogers.com 519.446.3636 Knowledge Management in Public Health Nancy Dubois, NCCMT Consultant dubfit@rogers.com 519.446.3636 CPHA Conference, June 2009 Overview The four essential elements of Knowledge Management: Culture, Content,

More information

Information Services for Smart Grids

Information Services for Smart Grids Smart Grid and Renewable Energy, 2009, 8 12 Published Online September 2009 (http://www.scirp.org/journal/sgre/). ABSTRACT Interconnected and integrated electrical power systems, by their very dynamic

More information

National Data Sharing and Accessibility Policy (NDSAP)

National Data Sharing and Accessibility Policy (NDSAP) Draft National Data Sharing and Accessibility Policy (NDSAP) 1. Introduction 1.1 Data are recognized at all levels as a valuable resource that should be made publicly available and maintained over time

More information

TACOMA POWER UTILITY TECHNOLOGY SERVICES

TACOMA POWER UTILITY TECHNOLOGY SERVICES TACOMA POWER UTILITY TECHNOLOGY SERVICES REQUEST FOR INFORMATION NATURAL RESOURCES OPERATIONAL ANALYTICS SPECIFICATION NO. PS16-0021F City of Tacoma Tacoma Power / Utility Technology Services REQUEST FOR

More information

ElegantJ BI. White Paper. The Enterprise Option Reporting Tools vs. Business Intelligence

ElegantJ BI. White Paper. The Enterprise Option Reporting Tools vs. Business Intelligence ElegantJ BI White Paper The Enterprise Option Integrated Business Intelligence and Reporting for Performance Management, Operational Business Intelligence and Data Management www.elegantjbi.com ELEGANTJ

More information

Threat intelligence visibility the way forward. Mike Adler, Senior Product Manager Assure Threat Intelligence

Threat intelligence visibility the way forward. Mike Adler, Senior Product Manager Assure Threat Intelligence Threat intelligence visibility the way forward Mike Adler, Senior Product Manager Assure Threat Intelligence The modern challenge Today, organisations worldwide need to protect themselves against a growing

More information

Oracle Fusion Accounting Hub Reporting Cloud Service

Oracle Fusion Accounting Hub Reporting Cloud Service Oracle Fusion Accounting Hub Reporting Cloud Service Oracle Fusion Accounting Hub (FAH) Reporting Cloud Service is available in the cloud as a reporting platform that offers extended reporting and analysis

More information

Chapter Managing Knowledge in the Digital Firm

Chapter Managing Knowledge in the Digital Firm Chapter Managing Knowledge in the Digital Firm Essay Questions: 1. What is knowledge management? Briefly outline the knowledge management chain. 2. Identify the three major types of knowledge management

More information

HOW TO DO A SMART DATA PROJECT

HOW TO DO A SMART DATA PROJECT April 2014 Smart Data Strategies HOW TO DO A SMART DATA PROJECT Guideline www.altiliagroup.com Summary ALTILIA s approach to Smart Data PROJECTS 3 1. BUSINESS USE CASE DEFINITION 4 2. PROJECT PLANNING

More information

Integration of E-education and Knowledge Management

Integration of E-education and Knowledge Management Integration of E-education and Knowledge Management Liyong Wan 1, Chengling Zhao 2, and Wei Guo 2 1 College of Humanity and Social Science, Wuhan University of Science and Engineering,Wuhan,China,wanliyongccnu@yahoo.com.cn

More information

The Scientific Data Mining Process

The Scientific Data Mining Process Chapter 4 The Scientific Data Mining Process When I use a word, Humpty Dumpty said, in rather a scornful tone, it means just what I choose it to mean neither more nor less. Lewis Carroll [87, p. 214] In

More information

Towards unstructured and just-in-time learning: the Virtual ebms e-learning system

Towards unstructured and just-in-time learning: the Virtual ebms e-learning system Towards unstructured and just-in-time learning: the Virtual ebms e-learning system G. Elia 1, G. Secundo, C. Taurino e-business Management Section, Scuola Superiore ISUFI, University of Lecce, via per

More information

Intelligent Search for Answering Clinical Questions Coronado Group, Ltd. Innovation Initiatives

Intelligent Search for Answering Clinical Questions Coronado Group, Ltd. Innovation Initiatives Intelligent Search for Answering Clinical Questions Coronado Group, Ltd. Innovation Initiatives Search The Way You Think Copyright 2009 Coronado, Ltd. All rights reserved. All other product names and logos

More information

ElegantJ BI. White Paper. Achieve a Complete Business Picture with a Business Intelligence (BI) Dashboard

ElegantJ BI. White Paper. Achieve a Complete Business Picture with a Business Intelligence (BI) Dashboard ElegantJ BI White Paper Achieve a Complete Business Picture with a Business Intelligence (BI) Dashboard Integrated Business Intelligence and Reporting for Performance Management, Operational Business Intelligence

More information

ENVI THE PREMIER SOFTWARE FOR EXTRACTING INFORMATION FROM GEOSPATIAL IMAGERY.

ENVI THE PREMIER SOFTWARE FOR EXTRACTING INFORMATION FROM GEOSPATIAL IMAGERY. ENVI THE PREMIER SOFTWARE FOR EXTRACTING INFORMATION FROM GEOSPATIAL IMAGERY. ENVI Imagery Becomes Knowledge ENVI software uses proven scientific methods and automated processes to help you turn geospatial

More information

10 Building Blocks for Securing File Data

10 Building Blocks for Securing File Data hite Paper 10 Building Blocks for Securing File Data Introduction Securing file data has never been more important or more challenging for organizations. Files dominate the data center, with analyst firm

More information

Copyright 2013 Splunk Inc. Introducing Splunk 6

Copyright 2013 Splunk Inc. Introducing Splunk 6 Copyright 2013 Splunk Inc. Introducing Splunk 6 Safe Harbor Statement During the course of this presentation, we may make forward looking statements regarding future events or the expected performance

More information

Forward Thinking for Tomorrow s Projects Requirements for Business Analytics

Forward Thinking for Tomorrow s Projects Requirements for Business Analytics Seilevel Whitepaper Forward Thinking for Tomorrow s Projects Requirements for Business Analytics By: Joy Beatty, VP of Research & Development & Karl Wiegers, Founder Process Impact We are seeing a change

More information

GRAPHICAL USER INTERFACE, ACCESS, SEARCH AND REPORTING

GRAPHICAL USER INTERFACE, ACCESS, SEARCH AND REPORTING MEDIA MONITORING AND ANALYSIS GRAPHICAL USER INTERFACE, ACCESS, SEARCH AND REPORTING Searchers Reporting Delivery (Player Selection) DATA PROCESSING AND CONTENT REPOSITORY ADMINISTRATION AND MANAGEMENT

More information

Introduction to Data Mining

Introduction to Data Mining Introduction to Data Mining Jay Urbain Credits: Nazli Goharian & David Grossman @ IIT Outline Introduction Data Pre-processing Data Mining Algorithms Naïve Bayes Decision Tree Neural Network Association

More information

Wrangling Actionable Insights from Organizational Data

Wrangling Actionable Insights from Organizational Data Wrangling Actionable Insights from Organizational Data Koverse Eases Big Data Analytics for Those with Strong Security Requirements The amount of data created and stored by organizations around the world

More information

ENHANCING INTELLIGENCE SUCCESS: DATA CHARACTERIZATION Francine Forney, Senior Management Consultant, Fuel Consulting, LLC May 2013

ENHANCING INTELLIGENCE SUCCESS: DATA CHARACTERIZATION Francine Forney, Senior Management Consultant, Fuel Consulting, LLC May 2013 ENHANCING INTELLIGENCE SUCCESS: DATA CHARACTERIZATION, Fuel Consulting, LLC May 2013 DATA AND ANALYSIS INTERACTION Understanding the content, accuracy, source, and completeness of data is critical to the

More information

How To Protect Your Network From Attack From A Network Security Threat

How To Protect Your Network From Attack From A Network Security Threat Cisco Security Services Cisco Security Services help you defend your business from evolving security threats, enhance the efficiency of your internal staff and processes, and increase the return on your

More information

Knowledge Management: A tool for Improving Government Performance

Knowledge Management: A tool for Improving Government Performance Knowledge Management: A tool for Improving Government Performance Page 1 of 5 Knowledge Management: A tool for Improving Government Performance by Brian D. Murrow and Victoria Adams What is Knowledge Management?

More information

The premier software for extracting information from geospatial imagery.

The premier software for extracting information from geospatial imagery. Imagery Becomes Knowledge ENVI The premier software for extracting information from geospatial imagery. ENVI Imagery Becomes Knowledge Geospatial imagery is used more and more across industries because

More information

Three Fundamental Techniques To Maximize the Value of Your Enterprise Data

Three Fundamental Techniques To Maximize the Value of Your Enterprise Data Three Fundamental Techniques To Maximize the Value of Your Enterprise Data Prepared for Talend by: David Loshin Knowledge Integrity, Inc. October, 2010 2010 Knowledge Integrity, Inc. 1 Introduction Organizations

More information

Considering Third Generation ediscovery? Two Approaches for Evaluating ediscovery Offerings

Considering Third Generation ediscovery? Two Approaches for Evaluating ediscovery Offerings Considering Third Generation ediscovery? Two Approaches for Evaluating ediscovery Offerings Developed by Orange Legal Technologies, Providers of the OneO Discovery Platform. Considering Third Generation

More information

Framework for Data warehouse architectural components

Framework for Data warehouse architectural components Framework for Data warehouse architectural components Author: Jim Wendt Organization: Evaltech, Inc. Evaltech Research Group, Data Warehousing Practice. Date: 04/08/11 Email: erg@evaltech.com Abstract:

More information

Business Intelligence and Service Oriented Architectures. An Oracle White Paper May 2007

Business Intelligence and Service Oriented Architectures. An Oracle White Paper May 2007 Business Intelligence and Service Oriented Architectures An Oracle White Paper May 2007 Note: The following is intended to outline our general product direction. It is intended for information purposes

More information

Government Technology Trends to Watch in 2014: Big Data

Government Technology Trends to Watch in 2014: Big Data Government Technology Trends to Watch in 2014: Big Data OVERVIEW The federal government manages a wide variety of civilian, defense and intelligence programs and services, which both produce and require

More information

Moving from Traditional to Online Instruction: Considerations for Improving Trainer and Instructor Performance

Moving from Traditional to Online Instruction: Considerations for Improving Trainer and Instructor Performance Moving from Traditional to Online Instruction: Considerations for Improving Trainer and Instructor Performance R. Lance Hogan, Ph.D., Assistant Professor, Eastern Illinois University Mark A. McKnight,

More information

Date: May 1, 2009. Unified Communications Building Blocks

Date: May 1, 2009. Unified Communications Building Blocks Date: May 1, 2009 Unified Communications Building Blocks Date: January, 2012 Table Of Contents 1. Executive Summary... 2 2. Unified Communications Building Blocks... 3 3. Converged IP Network... 4 4. IP

More information

Enhancing Sales and Operations Planning with Forecasting Analytics and Business Intelligence WHITE PAPER

Enhancing Sales and Operations Planning with Forecasting Analytics and Business Intelligence WHITE PAPER Enhancing Sales and Operations Planning with Forecasting Analytics and Business Intelligence WHITE PAPER Table of Contents Introduction... 1 Analytics... 1 Forecast cycle efficiencies... 3 Business intelligence...

More information

Data Mining, Predictive Analytics with Microsoft Analysis Services and Excel PowerPivot

Data Mining, Predictive Analytics with Microsoft Analysis Services and Excel PowerPivot www.etidaho.com (208) 327-0768 Data Mining, Predictive Analytics with Microsoft Analysis Services and Excel PowerPivot 3 Days About this Course This course is designed for the end users and analysts that

More information

Knowledge Management in Intercultural Collaborative Environments

Knowledge Management in Intercultural Collaborative Environments Knowledge Management in Intercultural Collaborative Environments Mihaela MUNTEAN, Professor PhD West University of Timisoara, Romania Faculty of Economics E-mail: mihaela.muntean@fse.uvt.ro Claudiu BRANDAS,

More information

JOURNAL OF OBJECT TECHNOLOGY

JOURNAL OF OBJECT TECHNOLOGY JOURNAL OF OBJECT TECHNOLOGY Online at www.jot.fm. Published by ETH Zurich, Chair of Software Engineering JOT, 2008 Vol. 7, No. 8, November-December 2008 What s Your Information Agenda? Mahesh H. Dodani,

More information