Increasing inclusion around open standards for data

I read an interesting article this week by Ana Brandusescu, Michael Canares and Silvana Fumega. Called “Open data standards design behind closed doors?” it explores issues of inclusion and equity around the development of “open data standards” (which I’m reading as “open standards for data”). Ana, Michael and Silvana rightly highlight that standards development is … Continue reading Increasing inclusion around open standards for data

The Common Voice data ecosystem

In 2021 I’m planning to spend some more time exploring different data ecosystems with an emphasis on understanding the flows of data within and between different data initiatives, the tools they use to collect and share data, and the role of collaborative maintenance and open standards. One project I’ve been looking at this week is … Continue reading The Common Voice data ecosystem

A short list of some of the things I’ve worked on which I’ve particularly enjoyed

Part of planning for whatever comes next for me in my career involved reflecting on the things I’ve enjoyed doing. I’m pleased to say that there’s a quite a lot. I thought I’d write some of them down to help me gather my thoughts around what I’d like to do more of in the future. … Continue reading A short list of some of the things I’ve worked on which I’ve particularly enjoyed

Four types of innovation around data

Vaughn Tan’s The Uncertainty Mindset is one of the most fascinating books I’ve read this year. It’s an exploration of how to build R&D teams drawing on lessons learned in high-end kitchens around the world. I love cooking and I’m interested in creative R&D and what makes high-performing teams work well. I’d strongly recommend it … Continue reading Four types of innovation around data

FAIR, fairer, fairest?

“FAIR” (or “FAIR data”) is an term that I’ve been bumping into more and more frequently. For example, its included in the UK’s recently published Geospatial Strategy. FAIR is an acronym that stands for Findable, Accessible, Interoperable and Reusable. It defines a set of principles that highlight some important aspects of publishing machine-readable data well. … Continue reading FAIR, fairer, fairest?

Why is change discovery important for open data?

Change discovery is the process of identifying changes to a resource. For example, that a document has been updated. Or, in the case of a dataset, whether some part of the data has been amended, e.g. to add data, fill in missing values, or correct existing data. If we can identify that changes have been … Continue reading Why is change discovery important for open data?