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dc.contributor.authorPelayo Villamil, Patricia-
dc.contributor.authorGarcía Roselló, Emilio-
dc.contributor.authorGuisande, Cástor-
dc.contributor.authorHeine, Juergen-
dc.contributor.authorManjarrés Hernández, Ana-
dc.contributor.authorGonzález Vilas, Luis-
dc.contributor.authorVaamonde, Antonio-
dc.contributor.authorGonzález Dacosta, Jacinto-
dc.contributor.authorGranado Lorencio, Carlos-
dc.date.accessioned2023-11-13T21:31:46Z-
dc.date.available2023-11-13T21:31:46Z-
dc.date.issued2014-
dc.identifier.citationGuerrero, M. J., Bedoya, C. L., López, J. D., Daza, J. M., & Isaza, C. (2023). Acoustic animal identification using unsupervised learning. Methods in Ecology and Evolution, 14(6), 1500–1514. https://doi.org/10.1111/2041-210X.14103spa
dc.identifier.urihttps://hdl.handle.net/10495/37297-
dc.description.abstractABSTRACT: 1. Data quality is one of the highest priorities for species distribution data warehouses, as well as one of the main concerns of data users. There is the need, however, for computational procedures with the facility to automatically or semi-automatically identify and correct errors and to seamlessly integrate expert knowledge and automated processes. 2. New version MODESTR 2.0 (http://www.ipez.es/ModestR) makes it easy to download occurrence records from the Global Biodiversity Information Facility (GBIF), to import shape files with species range maps such as those available at the website of the International Union for Conservation of Nature (IUCN), to import KML files, to import CSV files with records of the users, to import ESRI ASCII grid probability files generated by distribution modelling software and show the resulting records on a map. 3. MODESTR supports five different methods for cleaning the data: (i) data filtering when downloading records from GBIF, (ii) habitat data filtering, (iii) taxonomic disambiguation filtering, (iv) automatic spatial dispersion and environmental layer filters and (v) custom data filtering.spa
dc.format.extent6spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherWileyspa
dc.publisherBritish Ecological Societyspa
dc.type.hasversioninfo:eu-repo/semantics/publishedVersionspa
dc.rightsinfo:eu-repo/semantics/openAccessspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.titleUsing MODESTR to download, import and clean species distribution recordsspa
dc.typeinfo:eu-repo/semantics/articlespa
dc.publisher.groupGrupo de Ictiologíaspa
dc.identifier.doi10.1111/2041-210X.12209-
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2spa
dc.identifier.eissn2041-210X-
oaire.citationtitleMethods in Ecology and Evolutionspa
oaire.citationstartpage708spa
oaire.citationendpage713spa
oaire.citationvolume5spa
oaire.citationissue7spa
dc.rights.creativecommonshttps://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.publisher.placeHoboken, Estados Unidosspa
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.type.redcolhttps://purl.org/redcol/resource_type/ARTspa
dc.type.localArtículo de investigaciónspa
dc.subject.lembAlmacenamiento de información-
dc.subject.lembInformation storage-
dc.subject.agrovocCalidad de los datos-
dc.subject.agrovocData quality-
dc.subject.proposalData cleaningspa
dc.subject.proposalGeographic recordsspa
dc.subject.agrovocurihttp://aims.fao.org/aos/agrovoc/c_2fe8a00c-
dc.description.researchgroupidCOL0078704spa
dc.relation.ispartofjournalabbrevMethods. Ecol. Evol.spa
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