http://www2.bui.haw-hamburg.de/tematres/vocab/ DaLiCo Glossary Kristin Ameis, Christine Gläser, Hanna Käfer, Ulrike Spree data literacy : Indicates that this term is a “meta-term” meaning it is only used for hierarchical purposes. Deviating from the Thesaurus norm the metaterms below are used to assign references to facets. BT: Broader Term – Indicates the “parent” of the term, in the hierarchical tree structure. BTG: Broder Term Generic - is used when a generic is_a relation between the "parent" of the term exists. The generic relationship is the link between a class or category and its members or species. NT: Narrower Term – Indicates the “child” of the term, in the hierarchical tree structure. NTG: Narrower Term Generic - is used when a generic is_a "child" of relation exists. RT: Related Term – Indicates any terms that are related in meaning or in scope to the term being viewed. USE: Use reference - Indicates that the current terms is "Non-preferred" and that it should not be used for indexing purposes. UF: Used for - references to non-preferred equivalent term(s) Translations of the terms into dutch, german, hungarian and spanish are referenced as specialized UF Relations. UFDE - references the German translation UFES - references the Spanish translation UFHU - references the Hungarian translation UFNE - refernces the Dutch translation If you wish to receive a download in SKOS-format feel free to get in touch with the contact mail. ]]> Kristin Ameis, Christine Gläser, Hanna Käfer, Ulrike Spree 2021-08-05 en-GB 2021-11-14 21:44:52 2022-08-09 08:59:33 analyse 2021-11-14 21:44:52 2022-08-09 08:59:33 refers to all activities for gaining insight from data. This includes the ability to analyse structured and unstructured data using appropriate tools like text-mining, natural language processing, machine learning and advanced statistics (e.g., inferential view of data, linear regression, decision trees).

Source: DaLiCo Team (2022).

]]> refers to all activities for gaining insight from data. This includes the ability to analyse structured and unstructured data using appropriate tools like text-mining, natural language processing, machine learning and advanced statistics (e.g., inferential view of data, linear regression, decision trees).

Source: DaLiCo Team (2022).

]]> analyze http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1811 analizar http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1811 analyse [HU] http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1811 analyseren http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1811http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1934http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=2853http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1802http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=2144http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=2864http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1840http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1893http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1961http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1964http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=2004http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=2005http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=2006http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=2003