2555341
doi
10.5281/zenodo.2555341
oai:zenodo.org:2555341
user-eu
Anne-Laure Jousselm
NATO Science and Technology Organization, Centre for Maritime Research and Experimentation (CMRE
Cyril Ray
NATO Science and Technology Organization, Centre for Maritime Research and Experimentation (CMRE)
Pseudo-synthetic datasets in support to maritime surveillance algorithms assessment
Clément Iphar
NATO Science and Technology Organization, Centre for Maritime Research and Experimentation (CMRE)
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
<p>In the maritime domain, the ever-growing availability of data from<br>
systems such as the Automatic Identification System (AIS) enables the monitoring of worldwide maritime activities. The processing of huge amounts of spatial and temporal data rises issues linked to Big Data analyses. In particular, this paper focuses on the lack of veracity of data, and specifically on the characterisation of AIS dataset quality. In this paper, we aim at producing datasets either with a known and controlled veracity levels, or with added spatial events. Such quantified variations taking into account the initial quality level of the dataset and the desired level of degradation are performed following the mechanisms enabling data degradation, data improvement or event injection. A library has been developed, enabling the generation of those pseudo-synthetic datasets to be further used as benchmark for the assessment of algorithms solving Maritime Situation Awareness (MSA) issues such as anomaly detection.</p>
Zenodo
2019-02-01
info:eu-repo/semantics/conferencePaper
2555340
user-eu
award_title=Big Data Analytics for Time Critical Mobility Forecasting; award_number=687591; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/687591; funder_id=00k4n6c32; funder_name=European Commission;
1579541884.377635
794858
md5:61516ce847896367bd73c077b59528e7
https://zenodo.org/records/2555341/files/Verita19.pdf
public
10.5281/zenodo.2555340
isVersionOf
doi