Software/Information Systems Center - dodccrp

Software/Information Systems Center - dodccrp

Information Management Reference Model R. Evans, J. Fandozzi , T. Frangioso, R. Haller, M. Hebert, P. Lehner, A. Miller, R. Miller S. Renner, R. Rudman, L. Seligman, A. Weiss 13 May 99 (Version 1) 1999 The MITRE Corporation All Rights Reserved MITRE 2 01/27/20 13:09 Why Are We Here? IM is our job, but we are struggling to understand - How to communicate and represent what IM really is - How the pieces of IM interrelate - How to mature the way DoD creates, manages and employs data information ... and knowledge The Department implements IM capabilities in a plethora of systems, and we are struggling to - Make sense of the C4ISR and IT acronym soup - Determine how to construct an enabling enterprise as a foundation for operational capabilities - Make the needed IM capabilities affordable, secure, and responsive - Re-invent how we acquire, integrate and evolve IM solutions Mission MissionofofDoD DoDInformation Information Management Management Provide Providethe theright rightinformation, information,atatthe theright rightplace placeand andtime timefrom fromthe theright rightsources, sources,ininaa form formthat thatusers userscan canunderstand understandand andreliably reliablyuse usetotoaccomplish accomplishtheir theirmissions missionsand and tasks, effectively and efficiently ITM Strategic Plan - Mar 1997 tasks, effectively and efficiently ITM Strategic Plan - Mar 1997 1999 The MITRE Corporation

2 3 01/27/20 13:09 We Are Here To ... Define Definethe theIM IMproblem. problem. Create Createaaframework/model framework/modelto todiscuss discussIM IMintelligently. intelligently. Examine DoD IM and identify whats broken? Understand Understandthe therelationship relationshipof ofsystems systemsto tothe the IM IMcapabilities capabilitiesneeded neededto tosupport supportmilitary militaryand andbusiness businessoperations. operations. Understand Understandthe theenterprise enterpriseforest forestwithout without being beingblinded blindedby bythe thetechnology technologyand andsystem systemtrees. trees. Identify Identifyvoids, voids,opportunities opportunitiesand andpathological pathologicalinterfaces. interfaces. Understand Understandwhere wherethe thesystem-of-systems system-of-systemsis is duplicative duplicativeor orimbalanced. imbalanced. Identify Identifyan

anaffordable affordablestrategy strategyto tomature matureour ourIM IMcapability capability consistent consistentwith withenterprise enterpriseand andoperational operationalneeds. needs. = Policy, Investment, Evolution, Roles 1999 The MITRE Corporation 3 4 01/27/20 13:09 Organizational View What is the Scope of IM? Values Mission Vision Strategic Goals and Measures Functional Area Strategic Plans End-to-end Processes and Mission Threads Mission Applications Decision Support IM Knowledge Little IM Information Data Infrastructure 1999 The MITRE Corporation 4 5 01/27/20 13:09 Critical Operational Challenges for IM Friendly force status, capabilities, objectives, and plans Enemy and neutrals status, capabilities, objectives, and plans Focused logistics and force readiness / deployment Info assurance monitoring and assessment Course of action development and analysis, decision support Electronic Commerce/Electronic Business Distance learning Telemedicine Electronic access Collaboration 1999 The MITRE Corporation

5 6 01/27/20 13:09 Whats The Problem? Broad domain: encompasses C4ISR and business affairs Scarcity: managing info gathering and comms resources Quality/pedigree/integrity of data & info: source, maintain, propagate Evolving technology: key elements still maturing Semantic translation 1000 Prediction Managing info uncertainty Intent or Cause Value Info security Info sharing/access 100 Implication Dynamic info needs/content Facts Avoiding Info overload Data JV 2010 Goal Understanding Information Data 1 1999 The MITRE Corporation 1 10 Effort 100 6 7 01/27/20 13:09 What is a model and why is it useful? A model is a representation of something serving as the plan from which the thing can be constructed Websters IM encompasses data, information, knowledge, and decisions, in the context of the enterprise and the underlying technology. Today the IM "language" used is inconsistent between the many functional user, technical, and management communities. We need models to facilitate a common understanding and provide a common language.

The IM Model help us link decisions, knowledge, information and data to the enterprise's mission, goals, and performance outcomes. 1999 The MITRE Corporation Mission needs Model(s) Model(s) Model(s) Model(s) Enterprise wide systems/processes 7 8 01/27/20 13:09 Why do we need an IM model? Help us understand the constituent elements in relation to each other and within the context of the whole - Capabilities assessment =Do we have the right systems and processes? =Do we have overlaps? =Do we have gaps? - Common needs Enable linkage between the mission capabilities needed and the systems and processes (including policies) used to satisfy the needs Provide checklists for system, procedure, and policy development 1999 The MITRE Corporation 8 An IM Model should make sense of the jargon Architectures Collaborative computing Communications and networks Decision support systems Human computer interaction Military applications Business applications Government applications Records management Middleware Smart push technology Smart pull technology World Wide Web Enterprise management Network management Information Technology Data Warehouses IT Governance Portfolio analysis Strategic IT investment Balanced scorecard Display technology Imaging systems Nanotechnology Security Optoelectronics Real time Natural language queries Physical security

Automatic speech Information warfare recognition Security measures Graphics Sensors and environment Human mechanics Software management Multimedia Operating systems Information management Software engineering Data management Software components Data mining Training Database management Computer based instruction Data integrity Distance learning Knowledge management Data Mediation Object-oriented Public key encryption Object extraction Authentication Flat files Non-repudiation Intelligent agents Homogeneous environments Search engines Heterogeneous environments Simulation, modeling and training Machine translation Information assurance Information Data fusion ATM,TCP/IP, HTTP, XML, JAVA, Metadata Fuselets Jini Multicast, broadcast 10 01/27/20 13:09 A General Model for Information Management - The Information Management Reference Model A model to frame an organizations broad information environment 1999 The MITRE Corporation 10 11 01/27/20 13:09 A General Information Management Reference Model Information Management Reference Model can be addressed as a single end-to-end thing - Spanning multiple disciplines - Separable from physical implementation

Model is general: specific application eliminates some components Higher layers generally benefit from lower layers Model shown is not a protocol stack Information does not necessarily flow through the layers 1999 The MITRE Corporation Decision Support Knowledge Management Information Management Data Management Physical Implementation Communications, Networking Computing 11 12 01/27/20 13:09 Support to the Decision Process orient observe decide Deciders Deciders Information Information consumers consumersand andproducers producers motivations, motivations,goals, goals,experience, experience,broader broadercontext context act The TheEnvironment Environment 1999 The MITRE Corporation 12 13 01/27/20 13:09 Data Management orient decide observe act Data:

Data Management: Symbols that express statements about the world Control of the process and infrastructure to make data available as needed Words, Numbers, Pictures, etc. Data Management Definitions adapted from Thomas H. Davenport and Laurence Prusak 1999 The MITRE Corporation The TheEnvironment Environment 13 14 01/27/20 13:09 Information Management orient decide observe act Information: Information Management: Data that has meaning within some context for its receiver Information Management Control of the selecting, integrating, and refining of data to produce the information needed by a decider and the dissemination of it Data Management Definitions adapted from Thomas H. Davenport and Laurence Prusak 1999 The MITRE Corporation The TheEnvironment Environment 14

15 01/27/20 13:09 Knowledge Management orient decide observe act Knowledge: Information organized and abstracted to have useful, predictive, and explanatory power for deciders Experience, values, expert insight Knowledge Management: Knowledge Management Control of a systematic approach to creating, diffusing, updating, and applying knowledge Information Management Data Management Definitions adapted from Ilkka Tuomi 1999 The MITRE Corporation The TheEnvironment Environment 15 16 01/27/20 13:09 Decision Support orient decide observe act Decision: Define, select and monitor success of strategies, plans and individual actions Decision Support: Decision Support Knowledge Management Assistance in generating and evaluating

hypotheses and options Information Management Data Management Definitions adapted from "Automated Decision Making", P. Lehner 1999 The MITRE Corporation The TheEnvironment Environment 16 17 01/27/20 13:09 Additional Views and Dimensions of Information Management Reference Model Within a particular discipline or across the spectrum, functionality and technology can be discussed Ent y log hno Tec nal ctio Fun erp rise Op Info era t i on As s s ura nce Go ver nan ce - Decision Support Knowledge Management Information Management As with the disciplines it is difficult to draw hard distinctions between the two Governance, Information Assurance and Enterprise

Operations transcend/cut across the disciplines and the physical implementation - Each is a domain in its own right But each can/should be related to the whole Data Management Physical Implementation Communications, Networking Computing Dimensions 1999 The MITRE Corporation Views 17 01/27/20 13:09 Ent y log hno Tec nal ctio Fun erp rise Op Info era t i on As s s ura nce Go ver nan ce Information Management Reference Model Functional View 18 Decision Support Knowledge Management Information Management Data Management Physical Implementation Communications, Networking Computing 1999 The MITRE Corporation 18 19 01/27/20 13:09

Mapping Representative Functions to IMRM Disciplines Decision Support Create -Collect -Update Knowledge Management Identify Information Management Create Data Management Create info Diffuse Analyze Integrate -Store -Index -Filter -Manipulate -Catalog -Validate -Maintain integrity -Disposition -Refine info -Integrate info -Monitor utility Store/Organize Distribute -Retrieve/query -Search -Synchronize -Share Knowledge Modify Visualize Formulate Hypotheses Generate Options Select options Disseminate -Broker info -Search/ retrieve info Prioritize tasking

Increasing levels of abstraction 1999 The MITRE Corporation 19 20 01/27/20 13:09 Data Management: Functional View Store/Organize Sources Create -Collect -Update 1999 The MITRE Corporation -Store -Index -Filter -Manipulate -Catalog -Validate -Maintain integrity -Disposition Distribute -Retrieve/query -Search -Synchronize -Share 20 21 01/27/20 13:09 Key Data Management Terms and Concepts Create Collect Update Store/Organize Store Index Filter Manipulate Catalog/ Manage Metadata Validate Maintain Integrity Disposition Distribute Retrieve/Query Search Synchronize Share Data Gather data from the environment for later storage and/or processing Gather initial data from the environment Gather most current data to replace data that has already been collected Warehouse data and arrange into an orderly, structured, functional method Manage persistence for data Create and maintain ancillary data structures that enable more efficient search and retrieval

Given a stream of data, produce a subset of that stream, by eliminating data that fails to satisfy specified conditions (i.e., in a query) Change data from its raw state to a more useable representation (includes compression, translation) Create and manage a collection of metadata (i.e., data about data) to facilitate search and retrieval Verify data and mark data with indication of official sanction Check that specified constraints on the data are enforced (includes quality) Transfer data to anothers control or discard/destroy data (includes retention) Make data available to geographically distributed users and applications Get stored data that meets conditions specified in a query Identify potentially relevant data sources when the source is not known a priori Propagate changes across geographically distributed copies of data and potentially enforcing a specified degree of consistency Make data available to multiple user communities and/or applications 1999 The MITRE Corporation 21 22 01/27/20 13:09 Information Management: Functional View Task -Prioritize -Allocate Analyze -Refine Info Data Management Create Info -Discovery -Annotate -Modify -Data mine Sensors and other Collectors 1999 The MITRE Corporation -Summarize -Interpret -Integrate Info -Associate -Correlate -Fuse -Aggregate -Monitor Utility Disseminate -Broker Info Info Need and Use -Publish -Subscribe -Profile -Mediate -Search/Retrieve Info 22 23

01/27/20 13:09 Key Information Management Terms and Concepts Create info Process Refine info Integrate info Monitor utility Disseminate Broker info Search/ retrieve info Prioritize/ Allocate tasking Develop information products from data (Includes annotate, modify, discovery, data mining) Develop information products from existing information Develop information product from single set of information (Includes summarize and interpret) Develop a composite product from multiple information sources. (Includes associate, correlate, fuse, aggregate) Check info to determine its value in support of the needs Make information available to multiple user communities and /or applications Match information producers with information consumers (Includes publish, subscribe, profile, mediate) Identify potentially relevant information sources when the source is not known a priori and gets information Determine which requests for additional information are needed and the order that they should be undertaken 1999 The MITRE Corporation 23 24 01/27/20 13:09 Knowledge Management: Functional View Culture s e v ti n e Inc Identification Diffusion Tacit, Explicit Creation Integration Modification Action Source: Reinhardt and Pawlowsky 1999 The MITRE Corporation 24 25

01/27/20 13:09 Key KM Terms & Concepts Identification Find knowledge that exists inside and outside the organization (knowledge-seeking behavior) Examples: Searching for information and expertise; Seeking activities and associations that will foster discovery Creation Develop new knowledge and generate knowledge that exists inside and outside the organization (gain in new understanding) Examples: The Aha moment In this model: creating a record of the understanding Diffusion Transfer knowledge from person to person, group to group, organization to organization (may be an external representation of understanding) Examples: Dialogue & other forms of personal communication; externalization and internalization discovery & accessing a record of content Integration Fit new understanding into a context of other understanding Examples: Including other thoughts, documents or plans in your understanding Modification Adapt the knowledge context itself Examples: Revising ones thoughts, documents or plans 1999 The MITRE Corporation 25 26 01/27/20 13:09 Decision Support: Functional View Hypothesis Options Response Formulate View data, information, hypotheses and knowledge Generate options Select options Stimulus Source: SHOR framework is a classic framework developed by Joseph Wohl. 1999 The MITRE Corporation 26 27

01/27/20 13:09 Key Decision Support Terms and Concepts Visualize Data/ Graphic representation of the data that Information/ supports rapid "at a glance" understanding of the data content and meaning. Knowledge Formulate Hypotheses Construct alternative explanations of the current situation, and assess their likelihoods; predict Generate Develop options that are appropriate for the hypothesized situations. Options Select Options Choose and execute one of the options, while considering the value of the option in each situation and the likelihood of each situation. 1999 The MITRE Corporation 27 Combined Data Management, Info Management, Knowledge Management, and Decision Support 01/27/20 13:09 Stimulus Hypothesis Options 28 Response Action Identification Integration Creation Modification Diffusion Tacit, Explicit Task -Prioritize Create Info Create Analyze Store/Organize Disseminate Distribute Sources

1999 The MITRE Corporation 28 29 01/27/20 13:09 Common Non-Operational Functions Development Functional Views Developers and System Engineers Development -Analyze & Design -Model -Build -Test -Integrate -Migrate 1999 The MITRE Corporation 29 30 01/27/20 13:09 Application of the Model - Some Examples Iterative nested processes Multiple IM processes make Dec is io n Suppo rt (Decision) Knowledge Management (Understanding) up any given end-to-end IM process Dec is ion Suppo rt (Decision) Knowledge Management (Understanding) Information Exploitation * (Information) Data Manag eme nt (Data) De cision S upport (Dec ision) Knowledge Man agement (Understanding) Information Exploitation * (Information) Data Man age m ent (Data) Dec ision Support (Dec ision)

De c ision S uppo rt (De cision) Knowledge Management (Understanding) Knowledge Management (Unde rstanding) Information Exploitation * (Information) Data Manage me nt (Data) In form ation Exploitation * (Information) Data Manage m ent (Data) Dec ision Support (Dec ision) De c is ion S upport (De cision) Knowledge Management (Understanding) Information Exploitation * (Information) Data Manage me nt (Data) De c is ion Support (Decision) Knowledge Management (Unde rstanding) In form ation Exploitation * (Information) Data Manage m ent (Data) Kn owledg e Managem ent (Understanding) Inform ation Exploitatio n * (Information) Data Managem e nt (Data) Dec ision Support (Dec ision) De c is ion

S upport (De cision) De c is ion Support (Decision) Knowledge Management (Understanding) Knowledge Managem ent (Unde rstanding) Kn owledg e Management (Understanding) Information Exploitation * (Information) Data Manage m ent (Data) Inform ation Exploitation * (Information) Data Manage m ent (Data) Dec isio n Support (Decision) Knowledge Management (Understanding) Inform ation Exploitatio n * (Information) Data Manage me nt (Data) Information Exploitation * (Information) Data Manage me nt (Data) Dec ision S upport (Dec ision) De c is ion S upport (De cision) De c is ion Support (Decision) Dec ision Support (Decision) Dec ision Support (Decision)

Knowledge Man agement (Understanding) Knowledge Managem ent (Unde rstanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Information Exploitation * (Information) Data Man age m ent (Data) Inform atio n Exploitation * (Information) Data Manage m ent (Data) Inform ation E xploitation * (Information) Data Manage me nt (Data) Information Exploitation * (Information) Data Manage me nt (Data) Information Exploitation * (Information) Data Manage me nt (Data) De cision S upport (Dec ision) De c is ion S upport (De cision) Dec is ion Support (Decision) Dec ision Support (Decision) De cision S up po rt (Dec ision)

De cision S up po rt (Dec ision) Knowledge Man agement (Understanding) Information Exploitation * (Information) Data Man age m ent (Data) Kno wledge Managem en t (Unde rstanding) Inform atio n Exploitation * (Information) Data Manage m en t (Data) Knowledge Management (Understanding) Inform ation E xp loitation * (Information) Data Manage me nt (Data) Knowledge Management (Understanding) Information Exploitation * (Information) Data Manage me nt (Data) Knowledge Man agement (Understanding) Inform ation Exploitation * (Information) Data Man age m ent (Data) Knowledge Man agement (Understanding) Inform ation Exploitation * (Information) Data Man age m ent (Data) De c is ion Support (Decision) De c is ion Support (Decision) Knowledge

Management (Understanding) Information Explo itation * (Information) Data Manage ment (Data) Knowledge Management (Understanding) Information Explo itation * (Information) Data Manage me nt (Data) De c is ion Support (Decision) Dec is ion Suppo rt (Decision) Dec is ion S uppo rt (Decision) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Information Explo itation * (Information) Data Manage ment (Data) Info rmation Exploitation * (Information) Data Manag eme nt (Data) Information Exploitation * (Information) Data Manag eme nt (Data) De c is ion Support (Decision) Dec is ion Suppo rt (Decision) De cis ion S uppo rt

(Decision) De cis ion S upport (Decision) Knowledge Management (Understanding) Information Explo itation * (Information) Data Manage ment (Data) Knowledge Management (Understanding) Info rmation Exploitation * (Information) Data Manag eme nt (Data) Knowledge Management (Understanding) Information Exploitation * (Information) Data Manag eme nt (Data) Knowledge Management (Understanding) Informatio n Exploitation * (Information) Data Manag eme nt (Data) De c is ion Support (Decision) Dec is ion Suppo rt (Decision) De cis ion S upport (Decision) De c is ion Support (Decision) De c is ion Support (Decision) Knowledge Management (Understanding) Knowledge Management (Understanding)

Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Information Explo itation * (Information) Data Manage ment (Data) Information Exploitation * (Information) Data Manag eme nt (Data) Information Exploitation * (Information) Data Manag eme nt (Data) Information Exploitation * (Information) Data Management (Data) Information Explo itation * (Information) Data Manage ment (Data) Dec is ion Suppo rt (Decision) Dec is ion Suppo rt (Decision) De cis ion S upport (Decision) De c is ion Support (Decision) De c is ion Support (Decision) De c is ion Support (Decision) Knowledge Management (Understanding)

Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Info rmation Exploitation * (Information) Data Manag eme nt (Data) Information Exploitation * (Information) Data Manag eme nt (Data) Informatio n Exploitation * (Information) Data Manag eme nt (Data) Information Exploitation * (Information) Data Management (Data) Information Explo itation * (Information) Data Manage ment (Data) Information Explo itation * (Information) Data Manage me nt (Data) 1999 The MITRE Corporation Info rmation Exploitatio n * (Information) Data Manag ement (Data) Dec is io n Suppo rt

(Decision) Decis io n S uppo rt (Decision) Knowledge Management (Understanding) Knowledge Management (Understanding) Info rmation Exploitatio n * (Information) Data Manag ement (Data) Info rmatio n Explo itatio n * (Information) Data Manag ement (Data) Decision Support De cis io n S uppo rt (Decision) De cis io n S uppo rt (Decision) De cis io n S uppo rt (Decision) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Informatio n Explo itatio n * (Information) Data Manag e me nt (Data) Informatio n Explo itatio n * (Information) Data Manag e me nt (Data) Informatio n Explo itatio n * (Information) Data Manag e me nt

(Data) Knowledge Management Decis io n Suppo rt (Decision) Dec is io n Suppo rt (Decision) Dec is io n Suppo rt (Decision) Dec is io n Suppo rt (Decision) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Info rmation Exploitatio n * (Information) Data Manag ement (Data) Info rmatio n Explo itation * (Information) Data Manag ement (Data) Info rmatio n Explo itation * (Information) Data Manag ement (Data) Info rmation Exploitatio n * (Information) Data Manag ement (Data) Information Management De cis io n Suppo rt (Decision) Decis io n S uppo rt

(Decision) Decis io n S uppo rt (Decision) Dec is io n Suppo rt (Decision) Decis io n S uppo rt (Decision) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Informatio n Explo itatio n * (Information) Data Manag e me nt (Data) Info rmatio n Explo itatio n * (Information) Data Manag ement (Data) Info rmatio n Explo itatio n * (Information) Data Manag ement (Data) Info rmation Exploitatio n * (Information) Data Manag ement (Data) Info rmatio n Explo itatio n * (Information) Data Manag ement (Data) Data Management Dec is io n Suppo rt

(Decision) Dec is io n Suppo rt (Decision) Dec is io n Suppo rt (Decision) De cis io n S uppo rt (Decision) De cis io n S uppo rt (Decision) De cis io n S uppo rt (Decision) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Info rmatio n Explo itation * (Information) Data Manag ement (Data) Info rmatio n Explo itation * (Information) Data Manag ement (Data) Info rmatio n Explo itation * (Information) Data Manag ement (Data) Informatio n Explo itatio n * (Information) Data Manag e me nt (Data)

Informatio n Explo itatio n * (Information) Data Manag e me nt (Data) Informatio n Explo itatio n * (Information) Data Manag e me nt (Data) 30 31 01/27/20 13:09 Functional Model Applied to a Domain Problem-Time Critical Targeting Detection De c isi on S u ppo rt (Decision) Knowledge Management (Understanding) In fo rmatio n Exploitatio n * (Information) Data Manag e me nt (Data) De c isi on S u ppo rt (Decision) De c is ion S u pp ort (Decisi on) Knowledge Management (Understanding) Knowledge Management (Understanding) In fo rm atio n Exp loitatio n * (Information) Data Manag e me nt (Data) In fo rmatio n Explo itatio n * (Information) Data Man ag e me n t (Data) Track Target Deci s io n Su pport ( D eci s ion) Kn owl edg e M anag em ent

(U nder st andin g) I nf orm ati on E xpl oit at io n* ( In for m ati on) D at a Mana gem ent (D at a) De c isio n S u ppo rt (Decision) De c is ion S u pp ort (Decisi on) De c isi on S u ppo rt (Decision) Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) In form atio n Exp loitatio n * (Information) Data Manag e me nt (Data) In fo rmatio n Exploitatio n * (Information) Data Man ag e me n t (Data) In fo rmatio n Exp loitatio n * (Information) Data Manag e me nt (Data) D ecis i on S uppo rt ( Decis i on) K now le dge Man agem ent ( Under s tandi ng) Inf orm at ion Exp loi ta ti on * ( I nf or mat ion) Dat a Man agem ent ( Dat a) De ci s i on S uppo rt ( Decis io n) K now led ge Man agem ent (U nder st andi ng) Inf orm at ion Expl oi tat i on *

( I nfo rm at ion) D at a Man agem ent ( Dat a) Deci s io n S upport (D ecis ion) K now ledg e Man a g em ent (U nder st andin g) I nf orm ati on Expl oi tat io n* ( I nfor m ati on) D at a Man agem ent ( Dat a) Deci s ion Su pport ( D eci s ion) Kn owl edg e M anag eme nt (U nder st anding ) I nf orma ti on E xpl oit at io n* ( In for ma tio n) D ata Mana geme nt (D ata) Deci s io n Su pport ( D eci s ion) Kn owl edg e M anag em ent (U nder st andin g) I nf orm ati on E xpl oit at io n* ( In for m ati on) D at a Mana gem ent (D at a) Deci s io n Su pport (D eci s ion) K nowl edg e Manag em ent (U nder st andin g) I nf orm ati on Expl oit at io n* ( I nfor m ati on) D at a Mana gem ent (D at a) Deci s ion Sup port ( D ec i s ion) Kn owl edg e M anag eme nt (U nders t anding ) I nfo rm a ti on E xpl oit at io n* ( Inf or ma tio n) D ata Manag eme nt (D ata) D ecis ion Supp ort ( Deci s ion)

Kn owl edge M anage men t ( Und er s ta nding) I nfo rm at i on E xp lo it ati on * (I nf or mat ion ) D ata Manage men t (D ata) D ecis ion Supp ort ( Deci s ion) Kn owl edge M anage ment ( Und er s ta nding) I nfo rm at io n E xp lo it ati on * (I nf or mat ion) D ata Manage ment (D ata) Decis ion Supp ort ( D ec i s ion) Kn owl edge M anage men t ( Un ders ta nding) I nfo rm at i on E xpl oit ati on * (I nf or mat ion ) D ata Manage men t (D ata) D ecis i on Suppo rt ( Deci si on) Kno wl edge Ma nagem ent ( Under s tan ding) In fo rm at io n Exp loi t ati on * (I nf or mat ion) Dat a Managem ent ( Da ta) Deci s io n Su pport (D eci s ion) Deci s ion Sup port ( D ec i s ion) D ecis i on Suppo rt ( Deci si on) D ecis i on Suppo rt ( Deci si on) D ecis i on S uppo rt ( Decis i on) D ecis i on S uppo rt ( Decis i on) K nowl edg e

Manag em ent (U nder st andin g) I nf orm ati on Expl oit at io n* ( I nfor m ati on) D at a Mana gem ent (D at a) Kn owl edge M anag emen t ( Un ders t anding) I nfo rm a ti on E xpl oit at ion * (I nf or ma tion ) D ata Manag emen t (D ata) Kno wl edge Ma nagem ent ( Under s tan ding) In fo rm at io n Exp loi t ati on * (I nf or mat ion) Dat a Managem ent ( Da ta) Kn owl edge M anagem ent ( Und er s tan ding) I nfo rm at io n E xp loi t ati on * (I nf or mat ion) Dat a Managem ent (Da ta) K now le dge Man agem ent ( Under s tandi ng) Inf orm at ion Exp loi ta ti on * ( I nf or mat ion) Dat a Man agem ent ( Dat a) K now le dge Man agem ent ( Under s tandi ng) Inf orm at ion Exp loi ta ti on * ( I nf or mat ion) Dat a Man agem ent ( Dat a) TCT Dec is ion S up po rt (Decision) Dec i sio n S up po rt (Decision) De c isio n S u ppo rt (Decision) De c is ion

S u pp ort (Decisi on) Knowledge Management (Understanding) Knowledge Management (Underst anding) Knowledge Management (Understanding) Knowledge Management (Understanding) Inform ation Exp lo itation * (Information) Data Manage m en t (Data) Inform atio n Exp loitation * (Information) Data Manage m e nt (Data) In fo rm atio n Exp loitatio n * (Information) Data Manag e me nt (Data) In fo rmatio n Exploitatio n * (Information) Data Man ag e me n t (Data) Dec is ion S up po rt (Decision) Dec is io n S up po rt (Decision) De c isio n S u ppo rt (Decision) De c is ion S u pp ort (Decision) De c isi on S u ppo rt (Decision) Knowledge Management (Understanding) Knowledge Management (Understanding)

Knowledge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Understanding) Inform ation Exp lo itation * (Information) Data Man age me n t (Data) Inform atio n Exp loitation * (Information) Data Manage m e nt (Data) In form atio n Exp loitatio n * (Information) Data Manag em e nt (Data) In fo rmatio n Exploitatio n * (Information) Data Man ag e me nt (Data) In fo rm atio n Exp loitatio n * (Information) Data Manag e me nt (Data) Dec is ion S up port (Decision) De c is ion S up port (Decision) Dec is ion S up po rt (Decision) Dec i sio n S up po rt (Decision) De c isio n S u ppo rt (Decision) De c is ion S u pp ort (Decisi on) Knowledge Management

(Understanding) Knowl edge Management (Understanding) Knowledge Management (Understanding) Knowledge Management (Underst anding) Knowledge Management (Understanding) Knowledge Management (Understanding) Inform ation Exp lo itation * (Information) Data Man age me n t (Data) Info rm ation Explo itatio n * (Information) Data Man age me n t (Data) Inform ation Exp lo itation * (Information) Data Manage m en t (Data) Inform atio n Exp loitation * (Information) Data Manage m e nt (Data) In form atio n Exp loitatio n * (Information) Data Manag e me nt (Data) In fo rmatio n Exploitatio n * (Information) Data Man ag e me n t (Data) JAOC Ops Deci s i on S upport (D ecis ion ) K now ledg e Man a g em ent (U nder st andi ng) I nf orm ati on

Expl oi tat io n * ( I nfor m ati on) D at a Man agem ent ( Dat a) Deci s io n Su pport ( D eci s ion) Kn owl edg e M anag em ent (U nder st andin g) I nf orm ati on E xpl oit at io n* ( In for m ati on) D at a Mana gem ent (D at a) Deci s ion Sup port ( D ec i s ion) Kn owl edg e M anag eme nt ( Un ders t anding ) I nfo rm a ti on E xpl oit at io n* (I nf or ma tio n) D ata Manag eme nt (D ata) Decision Support Decision Support Knowledge Management Knowledge Management Information Management Information Management Data Management Data Management Task Asset Assess and Report Decision Support Decision Support Knowledge Management Knowledge Management Information Management

Information Management Data Management Data Management 1999 The MITRE Corporation 31 32 01/27/20 13:09 TCT Example - Initial Detection Does this target require further action? TMDO JAOC Analysts JAOC Analysts JSTARS Analysts -Assessment of target -Monitoring options Mapped location COP IPB Available assets Launch notification Location of impact Time Type TLE SIGINT notification MASINT notification Decision Support Knowledge Management Potential Actions -Start watch box -Request imagery -Task other sensors -No action Functional Technical Breakdown Functions Decision Support CVW CCT TBMCS GCCS V isualize Data/Inf ormation/ Know ledge Formulate Hypotheses Generate Options Select Options CVW

CCT Knowledge Management Identif y Know ledge Create Know ledge Dif f use Know ledge Integrate Know ledge Information Management GCCS TBMCS Modif y Know ledge Information Management Create Inf ormation A nalyze Disseminate Data Management Typical Elements/ Players 1999 The MITRE Corporation ADSI GCCS TBMCS Tasking Data Management Create Store/organize Distribute GCCS TBMCS ADSI CVW CCT Current Systems Key Full Capability Current Systems Limited capability No capability 32 33 01/27/20 13:09 TCT Example - Track Target Potential Actions Is this a valid time critical target? TMDO Decision Support

-Nominate target -No action CVW CCT TBMCS GCCS JSWS Functional Technical Breakdown Functions Decision Support V isualize Data/Inf ormation/ Know ledge Formulate Hypotheses Generate Options JAOC analysts ID target -Characterization of target Knowledge Management CVW CCT TCTA Select Options Knowledge Management Identif y Know ledge Create Know ledge Dif f use Know ledge Mapped location COP IPB IPL Information Management Target location Data Time Type Management TLE Direction Speed EOB All source data List of designated TCTs IPL TCTA SAA JSWS GCCS ADSI JSWS TBMCS GCCS Integrate Know ledge Modif y Know ledge

Information Management Create Inf ormation A nalyze Disseminate Tasking Data Management Create Store/organize Distribute GCCS TBMCS ADSI CVW CCT Current Systems TCTA SAA JSWS Key Full Capability Current Systems Limited capability No capability Typical Elements/ Players 1999 The MITRE Corporation Current Systems 33 34 01/27/20 13:09 TCT Example - Task Asset Potential Actions What asset should be tasked? CCO ACCO -Task Asset -Continue to monitor -Discontinue surveillance Functional Technical Breakdown Functions Decision Support CVW CCT TBMCS GCCS

Decision Support V isualize Data/Inf ormation/ Know ledge Formulate Hypotheses Generate Options Assessment by TMDO, ACCO, SODL, Intel, JAG, BCD, SOF, Airspace Sorted ATO Legal issues COP IPB Weapon Capability Weapon Availability Delivery System -Capability -Vulnerability -Availability -Current tasking Weather TLE Legal situation Knowledge Management Information Management Data Management Typical Elements/ Players 1999 The MITRE Corporation Select Options CVW Knowledge Management Identif y Know ledge CCT Know ledge TCS (Voting Function) Create Dif f use Know ledge TCS (TBMCS) CVW JTW GCCS LAWS Integrate Know ledge Modif y Know ledge Information Management Create Inf ormation A nalyze Disseminate TCS (TBMCS) Tasking Data Management GCCS Create ADSI Store/organize Distribute LAWS GCCS TBMCS ADSI

CVW CCT Current Systems LAWS Key Full Capability Current Systems Limited capability No capability 34 35 01/27/20 13:09 Wing Commander Example How do I allocate resources? What are the support needs? Wing Commander Cmdrs Action Checklist COP SMEs Decision Support Potential Actions: - number of sorties - planned missions Functional Technical Breakdown Functions TBMCS (SAA) GCCS GCSS JMPS Decision Support V isualize Data/Inf ormation/ Know ledge Formulate Hypotheses Generate Options SMEs, TTPs, Doctrine Situation Briefing Assessments (e.g., Threat) Sorted ATO SORTS CTP COP IPB Weapon Capability Weapon Availability Delivery System Locations Weather A/C Data Logistics data People data Knowledge Management Information

Management Data Management Typical Elements/ Players 1999 The MITRE Corporation TBMCS GCCS GCSS JMPS TBMCS GCCS GCSS JMPS Select Options Knowledge Management Identif y Know ledge Create Know ledge Dif f use Know ledge IDM IBS Integrate Know ledge Modif y Know ledge Information Management Create Inf ormation A nalyze Disseminate Tasking TBMCS IDM Management GCCS IBS Data Create GCSS DMS Store/organize MIDS Distribute JMPS GCCS TBMCS GCSS MIDS JMPS Current Systems SAA IDM IBS DMS Key Full Capability Current Systems Limited capability

No capability 35 36 01/27/20 13:09 Notional Program Positioning GCCS GCSS TBMCS JMPS Decision Support Knowledge Management IBS IDM DMS GIG Transport MIDS JTRS GBS Information Management Data Management Physical Implementation Communications, Networking Computing Modelprovides providesaaframework frameworkfor fordiscussion discussion Model Helpsidentify identifyprogram, program,PAD, PAD,research, research,standards, standards,...... Helps positioning,focus, focus,commonality, commonality,...... positioning, 1999 The MITRE Corporation 36 37 01/27/20 13:09 Ent y log hno Tec nal ctio Fun

erp rise Op Info era t i on As s s ura nce Go ver nan ce Governance Functional View Decision Support The direction, guidance mechanisms, controls, structure, and work force to ensure a secure, efficient, effective, interoperable, responsive Information Management environment Knowledge Management Information Management Data Management Physical Implementation Communications, Networking Computing 1999 The MITRE Corporation 37 38 01/27/20 13:09 Governance Functional View Thrusts Direction Guidance Mechanisms Controls Structure Work Force 1999 The MITRE Corporation 38 39 01/27/20 13:09 Governance Functional View Thrust Areas Information Management Direction - Develop IM objective and architecture to guide IM Establish priorities and principles Scope and bound IM horizon Ensure IM support of DoD objectives Information Management Guidance Mechanisms -

Develop IM policy and procedures Develop IM strategic plans Develop strategies Select IM investment programs Information Management Controls - Motivate/incentivize compliance Measure achievement of direction and guidance mechanisms Monitor and assure compliance (i.e. enforcement) of guidance mechanisms Provide course correction 1999 The MITRE Corporation 39 40 01/27/20 13:09 Governance View Functional View Thrust Areas (concluded) Information Management Structure - Identify stakeholders - Identify organizational structures and relationships - Identify and establish leadership roles and responsibilities (distribution of power) - Establish supervision Information Management Work Force - Define skills Provide education and training Motivate work force Establish and promote communications 1999 The MITRE Corporation 40 41 01/27/20 13:09 Ent y log hno Tec nal ctio Fun erp rise Op Info era tion As s s ura n ce Go ver nan ce Info Assurance Functional View

The systems and processes required to ensure a secure, protected Information Management environment. Decision Support Knowledge Management Information Management Data Management Physical Implementation Communications, Networking Computing 1999 The MITRE Corporation 41 42 01/27/20 13:09 Information Assurance Functional View Thrust Areas Protect - Secure routers and switches Identification and Authentication Public Key Infrastructure Perimeter protection Secure operating systems Virus protection Virtual Private Networks Encryption Trust management Access control Process - Risk management Connection approval Certification Accreditation Vulnerability analysis Red Teams Site Assistance Visits Standards and guidelines Product evaluation System Assessment Penetration analysis Detect and React - Intrusion detection Monitoring Incident handling, response Situation awareness Forensics Recovery and backup 1999 The MITRE Corporation 42 01/27/20 13:09

1999 The MITRE Corporation 43 43 44 01/27/20 13:09 Ent y log hno Tec nal ctio Fun erp rise Op Info era tion As s s ura n ce Go ver nan ce Enterprise Operations Functional View Decision Support The solutions, services, operations and control required to ensure efficient, effective, interoperable, and responsive Information Management environment. Knowledge Management Information Management Data Management Physical Implementation Communications, Networking Computing 1999 The MITRE Corporation 44 45 01/27/20 13:09 Enterprise Operations Functional View Thrust Areas Operations and Control - Installation and Maintenance

Customer service support System administration User registration and administration Service Monitoring Service Management Testing - Training Enterprise Services - Collaboration Services Data Services Web Services Mapping Service Search Services Messaging Directories Licensing Services Software Distribution 1999 The MITRE Corporation 45 46 01/27/20 13:09 Ent y log hno Tec nal ctio Fun erp rise Op Info era tion As s s ura n ce Go ver nan ce Technology View Decision Support Systematic technique, method or approach to ensure efficient, effective, interoperable, and responsive Information Management environment. Knowledge Management Information Management Data

Management Physical Implementation Communications, Networking Computing 1999 The MITRE Corporation 46 47 01/27/20 13:09 Technology View Thrust Areas Collaborative Environments Computing and Software Technology Decision Support and Knowledge Environment Human Computer Interaction Data Management Environments Intelligent Information Processing Modeling, Simulation and Training 1999 The MITRE Corporation 47 48 01/27/20 13:09 Maturity Models 1999 The MITRE Corporation 48 49 01/27/20 13:09 Data Management: Maturity Model * F U T U R E P A T H N O W Level 5: Optimizing Process change mgmt, technology change mgmt, defect prevention Level 4: Managed Mgmt of integrated data, data quality, quantitative process Level 3: Defined Inter group coordination, training, organizational process definition and focus, peer reviews, data product eng Level 2: Repeatable Config mgmt, conflict mgmt, quality assurance, project planning and tracking, requirement mgmt Level 1: Initial Disciplined procedures 1999 The MITRE Corporation

*Modification of L. Chambless, B. Parker, Data Management Maturity Model, in B. Thuraisingham, ed., Handbook of Data Management, Boston: Auerbach, 1996 49 50 01/27/20 13:09 Information Management: Maturity Model F U T U R E P A T H Level 4: Integrated Information Management Enterprise-wide reengineered business processes Level 3: Agile Information Management Enterprise culture and policy changes Level 2: Facilitated Information Management Capabilities and tools N O W Level 1: Centralized Information Management Broker role 1999 The MITRE Corporation Source: adapted from the IC vision paper -- Exploiting Information as an Enterprise, MITRE (for the ISS), 97-98. 50 51 01/27/20 13:09 Knowledge Management: Maturity Model F U T U R E Level Level5:5:Optimizing Optimizing Business Businessprocess processalignment alignment Process change management Process change management Level Level4:4:Managed Managed Integrated Integratedknowledge knowledgeprocesses

processes Quantitative process management Quantitative process management P A T H N O W Level 3: Defined Organizational processes Knowledge mapping Intergroup coordination Training program Level 2: Repeatable Program planning Requirements process Content QA process Level 1: Initial Adhoc processes Partial technical infrastructure 1999 The MITRE Corporation 51 52 01/27/20 13:09 Decision Support: Maturity Model F U T U R E P A T H N O W Level 4: Adaptive decision support Adaptive integration of human/machine decision making Iterative option generation/evaluation dialogues Level 3: Integrated decision support Integrated system and decision process engineering Integrated evaluation of complete options Level 2: Partial decision support Decision-focused engineering of applications Selected evaluation of option elements Level 1: Initial Technology-push engineering Untrusted, ad hoc advisory models 1999 The MITRE Corporation 52 53

01/27/20 13:09 Challenges 1999 The MITRE Corporation 53 54 01/27/20 13:09 Data Management Challenges Integrating structured and unstructured data Create Legacy DB migration Store/Organize Security and info assurance 1999 The MITRE Corporation Quality assurance Records mgmt, full lifecycle support Auto-administration Distribute Federation of large numbers of DBs Mass Storage Unifying process and data within active DBs 54 55 01/27/20 13:09 Information Management Challenges Data Mining Optimize local information spaces Tasking automation Visualization Task -Prioritize Data Management Create Info System Integration Analyze Disseminate Collaborative Analysis Distributed Analysis End-to-end Fused Views Info Need and Use

Brokering Tools Self-synchronization Personalization Near real time products Implement agile business practices and standards 1999 The MITRE Corporation 55 56 01/27/20 13:09 Knowledge Management Challenges Development of Enterprise Vision and Strategic Directions Integration with programs across organization Multi-year view of investments Top management buy-in Remove culture barriers often ingrained in processes Action Identification Integration Creation Modification Diffusion Tacit, Explicit Multimedia search tools Knowledge warehouses Collaborative environments Distance learning Mechanized diffusion 1999 The MITRE Corporation 56 57 01/27/20 13:09 Decision Support Challenges Automated Advisory Systems Option generation tools Option evaluation tools Advanced real time M&S Stimulus Hypothesis Option Response Information control Integrated human/machine reasoning 1999 The MITRE Corporation 57 58 01/27/20 13:09

Status Draft white paper undergoing internal/ external peer review Made substantial progress against objectives - Defined the IM problem - Created a framework to discuss IM intelligently Working with other IM initiatives - GNIE NSSA/MIM DARPA ICON Reviewed GIG Reviewed and commented on IM/IDM Policy Reviewed AF IM SAB Provided model to Bob Nesbit, DSB Defense Logistics Community 1999 The MITRE Corporation 58

Recently Viewed Presentations

  • Teaching Reading Strategies to Middle School Students

    Teaching Reading Strategies to Middle School Students

    Summarizing . Making Connections. These seven key reading strategies were explained by Stephanie Harvey and were based on the research of P. David Pearson. They can be applied to a variety of texts from fiction to nonfiction. Throughout this presentation,...
  • Agenda - University of New South Wales

    Agenda - University of New South Wales

    > UNSW Send Costs to GL > UNSW Review GL Expense. Searchby Employee ID and pick the second last search result. This will show results for the last finalised pay. The final row results will appear empty as General Ledger...
  • States of Matter - St. Francis Preparatory School

    States of Matter - St. Francis Preparatory School

    States of Matter 3 States of Matter Solids _____ Liquids _____ Gases _____ Most Dense Least Dense The 4th State of Matter What happens if you raise the temperature to super-high levels…between 1000°C and 1,000,000,000°C? ... kilopascal (kPa) mmHg atm...
  • Companies Act, 2013 - Bhubaneswar ICAI

    Companies Act, 2013 - Bhubaneswar ICAI

    Companies Act, 2013Practical Aspects Accounts and Auditor & New Provisions Related to Financial Statements - Bhubaneshwar26th February,2015 by CA Yagnesh DesaiB.Com. FCA. Financial Statements. ... Schedule III V/s Schedule VI. New Section added Viz ...
  • Native American Review Jeopardy!  Southwest Eastern Region Woodlands

    Native American Review Jeopardy! Southwest Eastern Region Woodlands

    Two landforms that are found here are_____ and _____. What are mesas, canyons, plateaus, mountains, etc.? This is what the Pueblo Indians farmed. What are corn, beans and squash? This was one of this region's type of homes. What is...
  • Consortia to Consortia

    Consortia to Consortia

    3. Agree to functional implementation: meetings, interactions, outreach to other key team members, goal is to begin with Wednesday 9a CT FS Interface meeting time slot. 2020 activities in preparation for DOE CD-2. Planning for ProtoDUNE II. Involvement of FD...
  • Space - Jam Education

    Space - Jam Education

    Earth. Earth is the third planet from the Sun and is the largest of the terrestrial planets. The Earth is the only planet in our solar system not to be named after a Greek or Roman deity.
  • Orange County Treasurer-tax Collector Tax Refunds Process ...

    Orange County Treasurer-tax Collector Tax Refunds Process ...

    ORANGE COUNTY TREASURER-TAX COLLECTOR Tax Collection Recap Fiscal Year End 2005-06 EFFECTIVE & EFFICIENT Methods of Tax Collections Jul. '06 - Dec. 06 EFFECTIVE & EFFICIENT INVESTING TRACS Financial Research Public Interest 2006 Top Investment Returns EFFECTIVE & EFFICIENT Constituent...