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Orca

Metadata Updated: April 11, 2025

Orca is a data-driven, unsupervised anomaly detection algorithm that uses a distance-based approach. It uses a novel pruning rule that allows it to run in nearly linear time. Orca was co-developed by Stephen Bay of ISLE and Mark Schwabacher of NASA ARC. More information about Orca, including downloadable software, can be found here:

http://stephenbay.net/orca/

A conference paper about Orca can be found here:

https://dashlink.arc.nasa.gov/paper/mining-distance-based-outliers-in-near-linear-time/

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date November 12, 2020
Metadata Updated Date April 11, 2025
Data Update Frequency irregular

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date April 11, 2025
Publisher Dashlink
Maintainer
Identifier DASHLINK_121
Data First Published 2010-09-10
Data Last Modified 2025-03-31
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id f9baa0ce-e4e4-484e-b1ff-ce5ae57e5caa
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL https://c3.nasa.gov/dashlink/resources/121/
Program Code 026:029
Source Datajson Identifier True
Source Hash 179f3be891a3a302efc0bae191c8f2e9fc70b43f47b9c0fe7a0f91990ea5824d
Source Schema Version 1.1

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