To convert data to knowledge, a convergence of knowledge management, information architecture, and data science is necessary. This is called knowledge architecture. Knowledge architecture involves designing and implementing an organization's intellectual infrastructure to capture, organize, analyze, and utilize information. It transforms information into knowledge through applying context. NASA faces challenges with large amounts of growing and siloed data. Opportunities for knowledge architecture at NASA include improving search capabilities, developing metadata standards, using analytics and visualization, and creating a lessons learned knowledge graph. This could help NASA make better decisions by leveraging past knowledge and reducing waste.
5. “The most important contribution
management needs to make in the
21st Century is to increase the
productivity of knowledge work and the
knowledge worker.”
PETER F. DRUCKER, 1999
6. NASA Challenges
• Hundreds of millions of documents, reports, project data, lessons learned,
scientific research, medical analysis, geo spatial data, IT logs, etc., are
stored nation wide
• The data is growing in terms of variety, velocity, volume, value and veracity
• Accessibility to Engineering data sources
• Visibility is limited
7. To convert data to knowledge a convergence of Knowledge
Management, Information Architecture and Data Science is
necessary.
7
Knowledge Management
Data Science
Information Architecture
8. Knowledge Architecture
• The people, processes, and technology of designing, implementing, and
applying the intellectual infrastructure of organizations.
• What is an intellectual infrastructure?
• The set of activities to create, capture, organize, analyze, visualize,
present, and utilize the information part of the information age..
• Information + Contexts = Knowledge
• Information Architecture + Knowledge Management + Data Science =
Knowledge Architecture
• KM without applications is empty (Strategy Only)
• Applications without KA are blind (IT based KM)
• Data Science transforms your data to knowledge
8
9. “We have an opportunity for everyone in the world to have access to all the world’s
information. This has never before been possible. Why is ubiquitous information so
profound? It is a tremendous equalizer. Information is power.”
ERIC SCHMIDT (FORMER CEO OF GOOGLE)
12. 30%of total R&D spend is
wasted duplicating
research and work
previously done.
Source: National Board of Patents
and Registration (PRH), WIPO, IFA
54%of decisions are made
with incomplete,
inconsistent and
inadequate information
Source: InfoCentric Research
Opportunity 1: Search in the Enterprise
46%Workers can’t find the
information they need
almost half the time.
Source: IDC
14. Page Rank By The Numbers
Google 5 Billion queries per day
Enterprise 1000 queries per day
What We
Are Looking
For
15. NASA SEARCH EVALUATION
15
• There is No One Solution
• Master Data Management Plan is essential
• Identify Critical Data
• Develop Standards for Government and Contractor created data
• Analytics is essential
• Meta Data
16. TOP USER REQUIREMENTS
16
• Semantic search
• Cognitive Computing – Clustering, topic modeling
• Faceting
• Repository specific searches
• Ability to save searches
• Alerts
26. LESSON LEARNED DATABASE
26
2031 lessons submitted across NASA. Filter by date and Center only.
Useful information stored in database.
27. TOPIC MODELING
27
Topic models are based upon the idea that documents are mixtures of topics, where a
topic is a probability distribution over words.
LDA Model from Blei (2011)
David Blei homepage - http://www.cs.columbia.edu/~blei/topicmodeling.htmlBlei, David M. 2011. “Introduction to Probabilistic Topic Models.” Communications of the ACM.
37. 37
WHAT COULD YOU ACCOMPLISH IF YOU COULD:
• Empower faster and more informed decision-making
• Leverage lessons of the past to minimize waste,
rework, re-invention and redundancy
• Reduce the learning curve for new employees
• Enhance and extend existing content and document
management systems
38. Contact Information
David Meza – david.meza-1@nasa.gov
Twitter - @davidmeza1
Linkedin - https://www.linkedin.com/pub/david-meza/16/543/50b
Github – davidmeza1
Blog
davidmeza1.github.io
38