EXPLORATION OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNIQUES TO LINK SCIENTIFIC PUBLICATIONS WITH OBSERVATIONAL DATA
19, April 2019

ESA Open Invitation to Tender AO9772
Open Date: 12/04/2019
Closing Date: 24/05/2019 13:00:00

Status: ISSUED
Reference Nr.: 19.167.02
Prog. Ref.: LTDP+
Budget Ref.: E/0429-05 – LTDP+
Special Prov.: GR
Tender Type: C
Price Range: 100-200 KEURO
Products: Ground Segment / Mission Operations / Other
Techology Domains: Others
Establishment: ESAC
Directorate: Directorate of Science
Department: Operations Department
Contract Officer: Delgado, Javier
Industrial Policy Measure: N/A – Not apply
Last Update Date: 12/04/2019
Update Reason: Tender issue

the exploration of artificial intelligence (AI) and machine learning (ML) techniques for establishing precise links between the publications and the specific science instruments and experiments carried by the space science missions, at a high level of detail, so as to highlight which instruments and modes of operation lead to more successful results. The goal is to find and classify semantic relations and non-obvious patterns among the entities in ESA science missions publications, in order to link them to the existing Science Archive databases for further processing. While similar activities are already carried out manually as part of the science operations by some of the ESA science missions, the ultimate goal of SAPS is to implement this semi-automated activity for all sciencemissions to facilitate the work of the SAPS librarian, in order to also allow effective cross-comparisons. Moreover, another objective is to bring the SAPS database up to date with the latest publications (from June 2017 onwards, until the end of this contract) from all ESA Space Science missions. In the course of this activity, any not yet documented bugs shall be addressed in dedicated reports. Furthermore, bugs will be tracked using industry-standard applications such as ESA-TRAC, Alfresco, and JIRA.

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