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This group aims to provide a forum to share understanding and practice around ‘Data Science’, and to share and co-develop that understanding with as wide a range of institutions as possible via appropriate HESPA networks. The group is open to any HESPA member, and we operate an MS teams site to support this work, so please contact email@example.com to sign up.
The group is new, and aims play a key part in framing the way the sector approaches data science, but it is envisaged that we will cover the following areas:
Defining data science - there is a lot of ‘mythology’ around what data science is, and what it can achieve. A clear, concise, agreed definition of data science, kept under review as the area evolves, will resolve a lot of potential confusion.
Ethics - as a new and developing area ethical concerns and responsible approaches need to be carefully considered, and the group will undertake some of this work.
Collection of case studies - where has data science been used successfully, what did it cost, and what did it achieve? This is a critical component in grounding the definition above in reality, and giving clear insight into the full range of effort required to make data science work.
Guidance on what a good data science project looks like - although the principals of good data science are already known, they are abstract. This guidance should use the case studies to inform a sense of what good, impactful, cost effective data science project looks like in differing HE contexts, and in institutions of different sizes/missions.
Maturity framework (a simple self-assessment tool) - establishing different maturity levels in a HE specific context for data science that would give a clear sense of where each institution was, and what the logical/appropriate next steps were in the form of a developmental road map.
BI and Data Science strategies – what should an institutional strategy around this activity look like/cover? Can we define some clear principals that can be tailored to local need?
This group will be of particular interest to senior planners interested in turning data into targeted insight, technical specialists with an understanding of the techniques involved, or those with an interest in developing a use case in their own institutions.
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