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WRM: “Tradecraft, Workflow, and Performance Representations for Mission Analysis”

Apr 26, 2017 @ 1:00 pm - 2:30 pm

Darniet K. Jennings, Ph.D. MBA
Laboratory for Analytic Sciences


This talk will focus on how data science techniques are being investigated for developing insights into analytic tradecraft, analysis workflows, and organizational performance. There are many definitions of data science, however there is one core reality which is true in all its variations. In the absence of sufficient data, there are limited means to create value through data science. Data wrangling is as much the foundation of a data science approach as the analytics themselves. Since the availability of data is key, the presentation will also share ideas on concepts being implemented for a workflow analysis dashboard that combines a “work in progress” data elicitation process with instrumentation to categorize, visualize, and prioritize different types of work within an organization for situational awareness and decision support. The practical idea behind a work-oriented view is to create a visual representation where tradeoffs and decisions can be interactively reviewed in a consistent manner, with or without a complete set of source data.

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We are going to use the NC State WebEx for the web conference. Please note that this
WebEx belongs to NC State and can not be downloaded directly from Cisco.
Also, it should work on iPhones and iPads via the WebEx App.
A good internet connection is recommended.
For better audio, please join via computer and then have the meeting call your number
or call in directly using one of the numbers below. When not speaking, please mute
your phone to avoid background noise.
When it’s time, join the WebEx meeting from here:
Meeting Number: 991 680 272
Audio Connection: 919-513-9329 (WolfMeeting)
Access Code: 991 680 272

Sponsored by the Laboratory for Analytic Sciences


Apr 26, 2017
1:00 pm - 2:30 pm
Event Category:
Event Tags:
meeting, research, wednesday, WRM


Mindy Huffman

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LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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