Collaborative Workspace

Transcription

1 Introduction Scenario 1 Scenario 2 Scenario 3 Collaborative Workspace Stoney Trent Martin Voshell Justin Grossman

2 Introduction Scenario 1 Scenario 2 Scenario 3 Findings concerning Intelligence Analysis Analysts have variable expertise Support tools should help senior analysts mentor and delegate to junior analysts Open-workspaces facilitate rigorous analysis, aid in collaborative broadening and help to avoid premature narrowing Analysts may be fully understand the best uses for collection assets and intelligence support tools

3 Introduction Scenario 1 Scenario 2 Scenario 3 Information Exchange Findings Artifacts of current collaborative tools provide insufficient context to support future work of uninitiated practitioners (successors) Successors find it more difficult to use predecessors work than to recreate their own Successors are heavily dependent on the organization of their predecessor Competing goals of both parties interfere with effective exchange Successors find it most difficult to acquire an appreciation for complex interactions that predecessors could infer based on their experience (software designers emphasize reusability in design) Exchanges of facts and tools are easy, exchanges of relationships, interactions and process is difficult Exchanges are most effective when done between comparably skilled and resourced practitioners Most successful handoffs involve right seat/left seat rides (in medical domain: Watch one- try one teach one )

4 Introduction Scenario 1 Scenario 2 Scenario 3 Joint Cognitive System Support Requirements Observable Directable Directing Attention Facilitating multiple perspectives

5 Introduction Scenario 1 Scenario 2 Scenario 3 Collaborative Workspace Metaphor of Support Considerations Story Team of successful analysts Using sharable workspace which facilitates work externalization Collaborating to identify changing patterns in behavior among rebel groups in Angola Illustration of Supported Tasks- Scenario 1 Organize, select, annotate information (folders, files and data) Derive patterns in time, space and personal/organizational association Tool supports identification of dimensions which could be used to display relevant trends (time scrubbing, geospatial layering, personality database dimensions)

6 Introduction Scenario 1 Scenario 2 Scenario 3 Collaborative Workspace Metaphor of Support Considerations Illustration of Supported Tasks- Scenarios 2 & 3 Observable Collection Plan to help identify intelligence gaps Compare collection plan with evolving trends in reporting Distant collaboration Review audit trail Attach relevant information

7 Introduction Scenario 1 Scenario 2 Scenario 3 workspace Click the Window above to launch Scenario 1 in Quicktime

8 Introduction Scenario 1 Scenario 2 Scenario 3 scenario 2 observable collection Observable Collection Plan Available collection assets are displayed and can be selected for view in multiple representations. Click the Window above to launch Scenario 2 in Quicktime

9 Introduction Scenario 1 Scenario 2 Scenario 3 scenario 3 distant collaboration Click the Window above to launch Scenario 3 in Quicktime

10 Collaborative Workspace: supporting the Intelligence Analyst Introduction No analyst is an island. As the term Intelligence Community suggests, analysts may work on individual aspects of a problem, but their collective effectiveness is a function of how well they collaborate. Analysts often interact with colleagues who have access to different data that relates to the same problem, and senior analysts need to be able to distribute tasks to and mentor junior analysts. Furthermore, a significant vulnerability exists in the exchange of information at either the individual or organizational levels. Analysts and staff officers indicate several important considerations of information exchanges: Artifacts of current collaborative tools provide insufficient context to support future work of uninitiated practitioners (successors) Most successful handoffs involve right seat/left seat rides (in medical domain: Watch one- try one teach one ) Successors find it more difficult to use predecessors work than to recreate their own Successors are heavily dependent on the organization of their predecessor Competing goals of both parties interferes with effective exchange Clearly defined objectives from predecessor coupled with joint agreement on task completion aids in effective exchanges Successors find it most difficult to acquire an appreciation for complex interactions that predecessors could infer based on their experience (software designers emphasize reusability in design) Exchanges of facts and tools are easy, exchanges of relationships and interactions and process is difficult Exchanges are most effective when done between comparably skilled and resourced practitioners To support collaborative information exchange, workstations, software, and education must be designed to address functional roles and variable expertise. Additionally, the Laws of Joint Cognitive Systems suggest that designs should be observable, directable, be able to direct attention and facilitate multiple perspectives (Woods, Hollnagel, 2005). National Intelligence Support Team (NIST) - Angola In our envisioned world scenario, the NIST analysts analyze and synthesize reports from various intelligence collection sources (SIGINT, IMINT, HUMINT, etc.). These daily assessments are further synthesized by distant and local consumers. Both near and distant collaborators or supervisors need to share raw data, exchange ideas, and be aware of each other s analytical process. Growing evidence for civil-military unrest can be deduced by viewing evolving patterns with respect to time, space and personal relationships. The broad array of targets, ranging from guerrilla leader communication devices to physical locations of people and equipment to personal discussions about plans and intentions, poses variable difficulties for collection. It is, therefore, important for the analyst to be able to observe his/her own collection assets with respect to the trends being observed. Ultimately the team is successful under steady-state conditions and can cope with inevitable surprise because it is supported by tools and education that support critical tasks of collaborative analysis while adhering to the Laws of Joint Cognitive Systems. Go to next page 2

11 Design Seed Our design seed addresses the local and distant (in space and time) collaboration. Local collaboration functions similar to a shared, interactive whiteboard (ie Smartboard) where analysts share their data as well as their processes from collection, to raw data, to hypothesis evaluation. Collaboration at a distance is supported by video communication, asynchronous chat, and data exchange. This design seed attempts to capture the ease of use and dynamic interactions of chalkboards, acetate and butcher paper, and open workspaces with tools that are customizable to support domain-specific intelligence activities. The workspace supports the analytical process by aiding in the externalization of work and data while not being tied to any specific set of data. The workspace supports discrete, but interrelated analyst functions (data organization and selection and pattern analysis) as well as multiple tools for interaction and annotation available via a palette-based interface. The analyst can interact with functional components in a node based data flow workspace area to create workflows. Using extensive drag and drop, analysts take these self-contained functional components and can string together actions in sequences so as to generate or test hypotheses. Reusable Components Graphical editors and actions can be extended by the analyst to meet their own specific needs. For example, analysts need the ability to be able to save discrete workflow components and define unknown variables (ie, a favorable geospatial projection and how it compares to new data coming in) for future processing and comparison- disseminate, reuse, refine. Audit Trail & Annotation As well as assisting in report creation, the workflow API may be available to other applications such that any image/hypothesis/piece of data that can be embedded into final product (at varying levels of accessibility) can be played back and the workflow actions and components leading to creation are available. Additionally, analysts and supervisors can create voice annotation or semantic tags upon playback of particular workflows to report on the personal processes employed. Angola Micro Scenarios: 1. The Collaborative Observable Workspace Organization precedes selectivity. In this scenario, we show co-located analysts selecting, organizing and annotating data from various sources. The analysts are able to generate displays which help to deduce patterns in several dimensions temporal, geospatial and personality associations. Inexpert analysts often have trouble deciding on which representations of their data may yield useful patterns. Therefore, the system aids them in identifying possible perspectives from which to view patterns. For instance, it presents the analyst with available layers to augment their geospatial analsys, or it may identify from the selected array of data certain dimensions that could be displayed in the personality link analysis. In creating their representations of various patterns, the tool records the data and rules used to arrive at the process. In doing so this facilitates information exchange and collaboration with distant teams. 2. Distant Collaboration Distant collaborators often lack an appreciation for the immediate situation and the constraints within which a team must work. Also, as indicated earlier, current collaborative tools do not provide sufficient context to support future work or handoffs to successors. Both highlight the continual cost of coordination which is amplified by separation in time and space. To support this continual cost, this scenario demonstrates the interaction of a distant collaborator who brings added insight, data and different perspectives to the analytical work. The design allows for insight into the data used by a particular analyst as well as references to the rules or processes that were used to arrive at the assessment. Further, it allows for the collaborator to add his/her new information to the analysis to weigh its impact on the ultimate conclusion. 3. Observable Collection A thorough understanding of the actual collection assets is critical to assessing intelligence gaps and placing context on trends that are derived or unobserved. This scenario shows an analyst accessing the collection plan of multiple collection assets and viewing their coverage (both temporal and geospatial) in relation to the data under consideration. Since most analysts are not experts in the capabilities and limitations of all collection assets, this function should also support their understanding of their collection systems attributes. 1