This document proposes a new approach to enable users to directly search vast datasets for potential items of interest. Current search methods for databases, data mining, and information retrieval have limitations when applied individually to today's large datasets. The proposed solution adapts elements from these different methods by using relevance estimation concepts from information retrieval, a multidimensional utility function from utility theory, and query refinement through explicit and implicit user feedback from data mining. This novel approach aims to decrease the difficulty of finding important data by combining human and machine intelligence to better support ad hoc searching of multidimensional data.

1. Abstract Systems Operations Data
Partner: System-Wide Safety
NASA and its partners produce staggering amounts of data: and Assurance Technologies
petabytes per day for both earth and space science, with some Customer: Operations and Maintenance
missions producing over a petabyte/day individually. Examining all
the data by hand is clearly impossible; progress has been made
in automated discovery, but little has been done to enable
the user to search for potential items of interest
directly. The goal of our research is to Problem Solution
address this gap.
No existing technology Our approach is to adapt elements from
Strategic Alignment: adequately several methods to address the problem.
OCT Roadmap TA11 (Intelligent • Search begins with
supports a user who wants to search for
Data Understanding, Data • Relevance estimation prototype of anomaly
data in today’s vast data sets:
Lifecycle elements) concepts from information • System ranks
National Aero R&D Plan • The strict query interpretation in retrieval instead of strict candidates by
(organization and mining databases often over- SEARCH constraint application. variation from
of safety data elements) restricts or under- prototype
Initial TRL: 3
restricts the results. METHODS FOR • Multidimensional utility
function from utility theory.
• System
automatically
• Data mining does not
support ad hoc search
as it is not user directed.
D
MULTIDIMENSIONAL DATA
D
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• Query refinement by data expands on user’s
mining explicit and implicit initial specification.
Shawn Wolfe user feedback.
• Information retrieval is Nikunj Oza, PhD
• Multiattribute query
applied to text, not data. Yi Zhang (UCSC), PhD
Martian Images specifications from Safety Reports
As a result, the user database Partner: Aviation Safety
Partner: Planetary Data
misses important systems. Reporting System
System
Customer: Scientists items in the Novelty/Contribution Customer: Safety Analysts
data.
• Decrease difficulty of finding important data
• Utilize strengths from multiple technologies
• Combine human and machine intelligence
Contact:
Shawn Wolfe
• Search for images by metadata • Search over different field types (numbers, categories, text)
Intelligent Systems (TI)
• Scientists enter desired values • Fine-tune performance by data mining past queries and
(650) 604-4760
• Tradeoffs over matching values are used to rank images results
<Shawn.Wolfe@nasa.gov>
• Users can also provide explicit feedback to refine results