From your FODAVA leadership team after visiting NVAC 1 That visualization and data analysis are not...
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Transcript of From your FODAVA leadership team after visiting NVAC 1 That visualization and data analysis are not...
From your FODAVA leadership team after visiting NVAC
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That visualization and data analysis are not by themselves the final result or the purpose of VA, but rather it is an integrated part of iterative analytic process
The most interesting parts were the interplay between the analysts and the tool builders, which made it clear that neither the data analytics part, nor the viz part, could do it alone…
So data and visual analytics is not just a disjoint union of data analytics and visualization. Rather it involves an iterative and interaction process of computer reasoning and visualization based on human reasoning
We think the three words, “Iterative, Interactive, and Integrative are important”.
I would like to add Engaging, Enlightening, and Expressive
Visual analytics is not a static mapVisual analytics is not information retrievalVisual analytics in not data mining
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Visualization and Analytics Centers
Detecting the Expected -- Discovering the UnexpectedTM
RVACUniversity of Washington
RVACPurdue UniversityIndiana Univ.Schoolof Medicine
RVACUniv. of North Carolina Charlotte,Georgia TechBank of America
RVACPenn. State
DHSGVACs
Scholars
Consortium
A Partnership with Academia,Industry, Government LaboratoriesAlaska
NewZealand
Australia
Hawaii
Europe
Canada
PacificRim
Drexel UniversityNY/NJ Port AuthorityEmergency Op Center
NSF
IVAC
RVACStanford
University
IDS-UACUniversity of
Southern California
IDS-UACUniv. of Illinois
IDS-UAC, Rutgers Univ.
IDS-UACUniversity of Pittsburgh
VISUAL COMMUNICATIONNV13: Active Products
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Data IngestPreparation
Data Representions & Transformation
Visual Explorationand Analytics
Dissemination andCollaboration
NATIONAL
REGIONAL
OUTREACH AND EDUCATION
CYBER
ANIMAL AND HUMAN HEALTH
NV6: Law Enforcement
PS16: NeoCities
PD3: Disaster ResponsePD5: Personnel Tracking
PD7: Mobile: Emergency Response
UW3: Medical Supply Analytics
RU4: Law Enforcement, Stat. Graphics
PD11: Zoonotic Disease Spread
PD12: Animal Health
NV11: Assessment Wall
NV10: Electric Power Grids
PS4: FEMARepVIZ
PS8: Health GeoJunction
PD14: Network Flow Security
UG6: JIGSAW, Investigative Analytics
SF5: IRIS Scalable Network Security
UW4: Coast Guard Command VA
UG3: Global Terrorism DB Analytics
UG9: Digital Library
NV1: Consortium
NV2: Conferences
NV4: Education
PD15: Education Initiative
RU11: New Jersey Outreach
RU12: K-12 Education
RU13: Undergraduates
RU14: Summer Reconnect Conf
RU5: Lab for Port Security
IL4: Deep Web Analytics
UC5: E-mail Org and People Analytics
IL7: Monitoring People/Events
IL8: Data Science Summer Inst.
RU1: WEB/Virtual Communities
EVALUATIONNV7: Threat Stream Generator NV8: Evaluation
MATH/SEMANTIC FOUNDATIONSNV3: NSF-FODAVA
NV12: Un/Str Text Analytics
NV18: IN-SPIRE
PS6: TexPlorer
TEXT PS2: Extraction PS3: Fact Extraction
PS5: Context Discovery
IL3: Contextual Text Analytics
PT2: Extraction Opinion
PT3: Information Extraction
UC2: Patterns in Text TEXT
NV9: Semantic Graphs NV16: ProSPECTPS14: SemanticNetSA
PD10: Social NetworksIL5: Streams, link analytics
RU3: Learning Decision Making
RU10: Semantic Graphs
PT1: Opinion/Sentiment Analytics
UC4: Context Based TrustGRAPH AND REASONING
UG2: STAB: Investigative Analytics
UG1: Reasoning Decision Making
GRAPH AND REASONING
RU1: Universal Information Graphs
UC4: Context Based Trust
IMAGE/VIDEO
UG5: Image/Video Theme/Temporal Analytics
PS11: Improvise PS15: ConceptVistaPS13: CiteSpace
PS7: Geo-Info Retrieval
PS12: GeoViz Toolkit
PS1: Geo-Knowledge
GEOSPATIAL
GEOSPATIAL/IMAGE
CYBER SF1: Scalable Transactional Analytics
IL6: Image AnalyticsUC1: Geospatial Multiple Media
PS9: Visual Computation
MULTIMEDIAHETEROGENOUS/IR
UG4: Multimedia Analytics
UG8: ResultMapsSF2: Heterogenous Info Spaces
IL1: Search Paradigms, IR
NV14: Synthesis NV17: Audio
MOBILEPD4: Mobile CCI
PD6: In-Field MobileNV5: SRS-Mobile
SENSOR
RU6: Inspection Algorithms
RU7: Nuclear Sensor Detection
RU9: Entropy Bio-surveillance
TEMPORAL PD13:Temporal Disease Surv.SF3: Scalable Temporal Databases
SF4: Perceptual Efficiency
SIMULATION
UW1: RimSim, SimulationUW2: JITC3, AR responders
DATA BASE
UC3: Information Store
NV15: First LookNV19: UPA
PD1: Data Integration
DATA INGEST
PRIVACYPD2: Privacy and Anonymized Data
RU8: Privacy Preserving Models
Analytic CycleProject Map
Visual AnalyticsCenters and Programs
March 2008 Compendium
NV: NVAC/PNNLPS: Penn StatePD: PurdueSF: StanfordUG: UNCC/GTUW: U. of WashingtonIL: U. of IllinousPT: U. of PittsburgRU: RutgersUS: USC
Key
Projects are listed once, while they often could be in multiple places
Vertical order has no implications e.g. Geospatial supports National Missions
Developed by Jim Thomas 5/12/08
SURVEILLANCE PD8: Surveillance:video
PD9: Smart Video Surv.PS10: Geo NewsWire
FINANCEUG7: Financial Analytics
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Spring/Fall Consortium and IEEE VAST 2008• Spring VAC Consortium: May 21-22, 2008 at APL,
JHU ---- Fall Nov 12, 13 in Richland Washington• IEEE Symposium on Visual Analytics Science and
Technology (VAST) 2008• http://conferences.computer.org/vast/vast2008/
• Columbus Ohio• Oct 19-24, 2008
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NSF Partnership
MOU signed between DHS and NSF July 23, 2007
5 year agreement to forward basic science in visual analytics
Larry Rosenblum, Leader of NSF Management Team (Sankar Basu, Ephraim Glinnert, Leland Jamison, Tie Luo, Larry Rosenblum, Maria Zemakova)
Workshop Wednesday Sept. 17, 2008
0800 – 0900 Breakfast
0900 – 0945 FODAVA-Lead: Missions and Plans, Haesun Park (Georgia Tech)
0945 – 1130 Grand Tour Visual Analytics (Thomas) with Demo IEEE VAST student competition winner and discussion topic: refining Visual Analytics Methods
1130 – 1245 Lunch (Klaus Building 1116)
1245 – 14:15 The Depth and Breadth of Visual Analytics (Ebert) with discussion topic: Where can we have the most impact?
14:15 - 1545 Tools for Analytical Thinking about Complex Problems (Rbarasky):, with discussion topic Developing analytic tools and methods for real applications
1545 – 1600 Concluding Remarks
1600 Adjourn
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ConclusionsVisual Analytics is an opportunity worth consideringPractice of Interdisciplinary Science is requiredBroadly applies to many aspects of society For each of you:
The best is yet to come…
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Top Ten Challenges within Visual Analytics
Human Information Discourse for Discovery—new interaction paradigm based around cognitive aspects of critical thinking
New visual paradigms that deal with scale, multi-type, dynamic streaming temporal data flows
Data, Information and Knowledge Representation
Collaborative Predictive/Proactive Visual Analytics
Visual Analytic Method Capture and Reuse