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 2021-11-29 08:42:43 Ridsdale Matrix 2021-11-29 08:42:43 Compilation of a set of skills and abilities that together comprise various levels of data literacy which are presented in a data literacy competencies matrix, organized by the five core aspects of a suggested data literacy definition (data, collection, management, evaluation, application). In the following years matrix developed into a kind of foundation for the ongoing conversations about
standards for assessing and evaluating levels of data literacy. The matrix very much informed the the creation of learning outcomes in data literacy education.

Source: Chantel Ridsdale, Rothwell, J., Smit, M., Ali-Hassan, H., Bliemel, M., Irvine, D., Kelley, D., Matwin, S., & Wuetherick, B. (2015). Strategies and Best Practices for Data Literacy Education: Knowledge Synthesis Report [Report]. https://doi.org/10.13140/RG.2.1.1922.5044

 
]]> Compilation of a set of skills and abilities that together comprise various levels of data literacy which are presented in a data literacy competencies matrix, organized by the five core aspects of a suggested data literacy definition (data, collection, management, evaluation, application). In the following years matrix developed into a kind of foundation for the ongoing conversations about
standards for assessing and evaluating levels of data literacy. The matrix very much informed the the creation of learning outcomes in data literacy education.

Source: Chantel Ridsdale, Rothwell, J., Smit, M., Ali-Hassan, H., Bliemel, M., Irvine, D., Kelley, D., Matwin, S., & Wuetherick, B. (2015). Strategies and Best Practices for Data Literacy Education: Knowledge Synthesis Report [Report]. https://doi.org/10.13140/RG.2.1.1922.5044

 
]]> data literacy competencies matrix http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1939http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1880http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1983http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1984http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1985http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1986http://www2.bui.haw-hamburg.de/tematres/vocab/xml.php?skosTema=1987