Data citation, attribution, and employability

dc.contributor.author Dailey, Meagan
dc.contributor.author Henke, Ryan
dc.date.accessioned 2017-01-13T00:19:05Z
dc.date.available 2017-01-13T00:19:05Z
dc.date.issued 2017-01-06
dc.description Poster: Demand from academic departments for linguists possessing data skills has remained low in the last decade despite an influx of new data-driven tools, research, and ability to manage data in ways not possible before the internet. We assessed two barometers of employability: academic job postings and course descriptions. A survey of the academic linguistic job market over 10 years reveals that despite the field becoming more reliant on digital data, employers are not asking that candidates be fluent in data management. We also surveyed course descriptions and syllabi from 25 of the top-ranked linguistics programs in the United States and abroad, finding that most universities do not offer training in basic data management, despite offering courses in data- driven subdisciplines. This poster presents the data supporting these points including data management hiring and training trends.
dc.description.abstract Demand from academic departments for linguists possessing data skills has remained low in the last decade despite an influx of new data-driven tools, research, and ability to manage data in ways not possible before the internet. We assessed two barometers of employability: academic job postings and course descriptions. A survey of the academic linguistic job market over 10 years reveals that despite the field becoming more reliant on digital data, employers are not asking that candidates be fluent in data management. We also surveyed course descriptions and syllabi from 25 of the top-ranked linguistics programs in the United States and abroad, finding that most universities do not offer training in basic data management, despite offering courses in data- driven subdisciplines. This poster presents the data supporting these points including data management hiring and training trends.
dc.description.sponsorship This material is based upon work supported by the National Science Foundation under grant SMA-1447886.
dc.format.extent 1
dc.identifier.uri http://hdl.handle.net/10125/43571
dc.language.iso en-US
dc.rights Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported Attribution-NonCommercial-ShareAlike 3.0 United States
dc.subject data citation
dc.subject attribution
dc.subject Linguistics
dc.title Data citation, attribution, and employability
dc.type Conference Paper
dc.type Presentation
dc.type.dcmi StillImage
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