Data Futures Assurance

Data delays shouldn’t mean data disorganisation

By |2019-07-11T15:02:06+01:00July 11th, 2019|What I've done|

I know it’s been a while since I’ve posted anything. This is not by any means due to a lack of content, it’s more a lack of time. Or - to be more accurate - time management! I was however moved to write a short article on why Universities should persevere with their initiatives to improve the quality of the data asset, in spite of the news this week that Data Futures has been put back at least another year. WONKHE were kind enough to publish it on their website Hopefully this will kick start my approach to dealing with the [...]

Why visualising Data Quality issues can overcome institutional inertia.

By |2019-01-28T17:05:40+00:00January 28th, 2019|What I've done|

A recurring problem with resolving cross domain data quality issues is the asymmetry of benefits. Essentially the data producer (responsible for entering or uploading data at the point of collection) has little visibility of how the quality of that data will affect the data consumer (the person or persons who use it). The utility of data is often scuppered at this collection point, as the producer - understandably - will apply only the business and quality rules relating to their own use cases. This is not simple to fix. I used to believe merely showing people the implications of these actions [...]

Data Futures Mapping Tool v2.1

By |2019-01-23T10:15:37+00:00January 7th, 2019|What I've done|

In my last blog post, I introduced a mapping tool linking the HESA Data Futures schema (2.01) to the UCISA HE capability model. This generated an enormous amount of feedback and interest. This interest made me appreciate - again - how powerful the capability model is if tuned to a real world scenario, and that I'd created a bit of a monster in terms of the tool itself. Having said I wasn't going to enhance it, the number of  requested changes, and a bit of spare time over the break has brought forth version 2.1.  The new functionality includes: A query function [...]

Restricted content

By |2022-12-31T09:40:08+00:00December 12th, 2018|Concepts and Templates, Members Area|

Download it here: HESA-Schema-Data-Mapping-to-HE-Capability-Model-Web-v2.1 This free to use tool allow you to map the HESA Data Futures Schema to the UCISA HE capability map. It is provided without license or warranty! For more information, please read the accompanying blog post and the update for version 2.1 Latest update: V2.1: Capability Lookup Query, Additional analysis and ranking, new graphs and visualisations and new mapping functionality showing where a capability is both ‘captured’ and ‘used’. Bug fixes pointed out by a few people who downloaded it. Hope it proves useful. If you have any comments in questions, get in touch via the [...]

Warm Fusion: Mapping the HESA Data Futures Schema…

By |2018-12-13T18:46:41+00:00December 12th, 2018|What I've done|

Some combinations just work; Bacon and Eggs,  Fred and Ginger,  Tom and Jerry,  Sheringham and Shearer and - of course - Angus and Malcolm Young of AC/DC. Okay the last one might not be for everyone, but segues into the idea of this article. For universities developing solutions for in-year reporting to the Office for Students, there is a raft of material available. Most of which is provided by HESA as part of the 'Data Futures' Programme*. The most important of which is the Data Dictionary (or schema)which defines all the entities and attributes mandated for each reference point.  I've seen [...]

Restricted content

By |2018-10-06T20:18:57+01:00October 5th, 2018|Concepts and Templates|

The Data Capability toolkit originally developed in the HEDIIP programme is now hosted at HESA: https://www.hesa.ac.uk/support/tools/data-capability. The template we've provided here is a version tweaked to get your started with Data Futures. We have added a set of objectives, issues, aspirations and gaps which reflect the challenges and opportunities which come with a successful implementation of in-year reporting. This template has been used in a detailed form for a number of universities to develop their Data Futures scope and plan.

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