'In the eye of the beholder': knowledge and skills requirements for data professionals

Research output: Research - peer-reviewArticle

Abstract

Introduction. The professionals required to in data science, data librarianship and data management are a new breed for whom the knowledge and skills are just emerging. Academic institutions are putting together courses to address this shortage without fully understanding what the knowledge and skills requirements are for data professionals in different types of organisation types. This paper aims to increase that understanding.
Method. Interviews were conducted with thirty-six currently practicing data professionals and their employers about current knowledge and skills requirements. Participants were purposefully selected to achieve a cross section of data roles and employing institutions and interviews ceased once saturation was achieved.
Analysis. Two types of coding were employed: initial coding to establish categories, followed by more focused coding, for analytical depth. Every effort is made to accurately present the viewpoint of participants.
Results. All participants reported the importance of high level communication and personal learning skills and characteristics around curiosity, flexibility, and comfort with change. In universities and scientific research organisations the required knowledge and skills are in areas which might be classified as data management and curation; and in business and government organisations, as data science and management.
Conclusion. While there are still uncertainties about knowledge and skills requirements and role ambiguities in different data roles in different organisational types, knowledge and skills related to particular roles begin to emerge and are discussed.
LanguageEnglish
JournalInformation Research: an international electronic journal
Volume22
Issue number4
StatePublished - 2017

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coding
management
interview
science
type of organization
research organization
librarianship
shortage
employer
flexibility
uncertainty
university
communication
learning

Cite this

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title = "'In the eye of the beholder': knowledge and skills requirements for data professionals",
abstract = "Introduction. The professionals required to in data science, data librarianship and data management are a new breed for whom the knowledge and skills are just emerging. Academic institutions are putting together courses to address this shortage without fully understanding what the knowledge and skills requirements are for data professionals in different types of organisation types. This paper aims to increase that understanding.Method. Interviews were conducted with thirty-six currently practicing data professionals and their employers about current knowledge and skills requirements. Participants were purposefully selected to achieve a cross section of data roles and employing institutions and interviews ceased once saturation was achieved.Analysis. Two types of coding were employed: initial coding to establish categories, followed by more focused coding, for analytical depth. Every effort is made to accurately present the viewpoint of participants.Results. All participants reported the importance of high level communication and personal learning skills and characteristics around curiosity, flexibility, and comfort with change. In universities and scientific research organisations the required knowledge and skills are in areas which might be classified as data management and curation; and in business and government organisations, as data science and management.Conclusion. While there are still uncertainties about knowledge and skills requirements and role ambiguities in different data roles in different organisational types, knowledge and skills related to particular roles begin to emerge and are discussed.",
author = "Kennan, {Mary Anne}",
year = "2017",
volume = "22",
journal = "Information Research",
issn = "1368-1613",
publisher = "Thomas Daniel Wilson",
number = "4",

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AU - Kennan,Mary Anne

PY - 2017

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N2 - Introduction. The professionals required to in data science, data librarianship and data management are a new breed for whom the knowledge and skills are just emerging. Academic institutions are putting together courses to address this shortage without fully understanding what the knowledge and skills requirements are for data professionals in different types of organisation types. This paper aims to increase that understanding.Method. Interviews were conducted with thirty-six currently practicing data professionals and their employers about current knowledge and skills requirements. Participants were purposefully selected to achieve a cross section of data roles and employing institutions and interviews ceased once saturation was achieved.Analysis. Two types of coding were employed: initial coding to establish categories, followed by more focused coding, for analytical depth. Every effort is made to accurately present the viewpoint of participants.Results. All participants reported the importance of high level communication and personal learning skills and characteristics around curiosity, flexibility, and comfort with change. In universities and scientific research organisations the required knowledge and skills are in areas which might be classified as data management and curation; and in business and government organisations, as data science and management.Conclusion. While there are still uncertainties about knowledge and skills requirements and role ambiguities in different data roles in different organisational types, knowledge and skills related to particular roles begin to emerge and are discussed.

AB - Introduction. The professionals required to in data science, data librarianship and data management are a new breed for whom the knowledge and skills are just emerging. Academic institutions are putting together courses to address this shortage without fully understanding what the knowledge and skills requirements are for data professionals in different types of organisation types. This paper aims to increase that understanding.Method. Interviews were conducted with thirty-six currently practicing data professionals and their employers about current knowledge and skills requirements. Participants were purposefully selected to achieve a cross section of data roles and employing institutions and interviews ceased once saturation was achieved.Analysis. Two types of coding were employed: initial coding to establish categories, followed by more focused coding, for analytical depth. Every effort is made to accurately present the viewpoint of participants.Results. All participants reported the importance of high level communication and personal learning skills and characteristics around curiosity, flexibility, and comfort with change. In universities and scientific research organisations the required knowledge and skills are in areas which might be classified as data management and curation; and in business and government organisations, as data science and management.Conclusion. While there are still uncertainties about knowledge and skills requirements and role ambiguities in different data roles in different organisational types, knowledge and skills related to particular roles begin to emerge and are discussed.

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