dc.contributor.author | Jussila, Jari | |
dc.contributor.author | Lehtonen, Timo | |
dc.contributor.author | Laitinen, Jari | |
dc.contributor.author | Makkonen, Markus | |
dc.contributor.author | Frank, Lauri | |
dc.date.accessioned | 2018-10-30T10:19:02Z | |
dc.date.available | 2018-10-30T10:19:02Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Jussila, J., Lehtonen, T., Laitinen, J., Makkonen, M., & Frank, L. (2018). Visualising maritime vessel open data for better situational awareness in ice conditions. In <i>Academic MindTrek'18 : Proceedings of the 22nd International Academic MindTrek Conference</i> (pp. 92-99). Association for Computing Machinery. <a href="https://doi.org/10.1145/3275116.3275124" target="_blank">https://doi.org/10.1145/3275116.3275124</a> | |
dc.identifier.other | CONVID_28680272 | |
dc.identifier.other | TUTKAID_79264 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/60021 | |
dc.description.abstract | Situational awareness of maritime vessels in ice conditions is important for the operation of supply chains. In the artic sea areas, the ice conditions pose a major challenge for maritime vessels getting stuck in the ice and being significantly delayed in arrival to harbor. Data science and open data provide new opportunities to overcome these challenges. This paper introduces available open data sources and data visualizations that can be used to develop applications, for example, for detecting maritime vessel collision, predicting estimated time of arrival to harbor, as well as maritime vessel route optimization in ice conditions. The paper begins by introducing available open data sources and existing computational studies on maritime vessels in ice conditions, then presents the developed data science solution and visualizations of the open data along with the open source software code, and finally concludes with a discussion on the potential application areas and opportunities for further research. | fi |
dc.format.extent | 282 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | Association for Computing Machinery | |
dc.relation.ispartof | Academic MindTrek'18 : Proceedings of the 22nd International Academic MindTrek Conference | |
dc.rights | In Copyright | |
dc.subject.other | jäätilanne | |
dc.subject.other | avoin data | |
dc.subject.other | maritime vessel | |
dc.subject.other | ice conditions | |
dc.title | Visualising maritime vessel open data for better situational awareness in ice conditions | |
dc.type | conferenceObject | |
dc.identifier.urn | URN:NBN:fi:jyu-201810244517 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.oppiaine | Tietojärjestelmätiede | fi |
dc.contributor.oppiaine | Information Systems Science | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.date.updated | 2018-10-24T09:15:14Z | |
dc.relation.isbn | 978-1-4503-6589-5 | |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 92-99 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © 2018 the Authors | |
dc.rights.accesslevel | openAccess | fi |
dc.relation.conference | MindTrek conference | |
dc.subject.yso | meriliikenne | |
dc.subject.yso | merialueet | |
dc.subject.yso | paikkatiedot | |
dc.subject.yso | paikkatietojärjestelmät | |
dc.subject.yso | avoin lähdekoodi | |
dc.subject.yso | tilannekuva | |
dc.subject.yso | avoin tieto | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2046 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p8446 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2152 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p16923 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p17089 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p25187 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p26655 | |
dc.rights.url | http://rightsstatements.org/page/InC/1.0/?language=en | |
dc.relation.doi | 10.1145/3275116.3275124 | |
dc.type.okm | A4 | |