Using MODESTR to download, import and clean species distribution records

ABSTRACT: 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.

• Autores: Pelayo Villamil, Patricia; García Roselló, Emilio; Guisande, Cástor; Heine, Juergen; Manjarrés Hernández, Ana; González Vilas, Luis; Vaamonde, Antonio; González Dacosta, Jacinto; Granado Lorencio, Carlos
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2014
• Institución: Universidad de Antioquia
• Repositorio: Repositorio UdeA
• Idioma: eng
• OAI Identifier: oai:bibliotecadigital.udea.edu.co:10495/37297
• Acceso en línea: https://hdl.handle.net/10495/37297
• Palabra clave: Almacenamiento de información; Information storage; Calidad de los datos; Data quality; Data cleaning; Geographic records; http://aims.fao.org/aos/agrovoc/c_2fe8a00c
• Rights: openAccess
• License: https://creativecommons.org/licenses/by-nc-nd/4.0/