In my last post I explored how we might better support the use of datasets. To do that I applied the BASEDEF framework to outline the ways in which communities might collaborate to help unlock more value from individual datasets. But what if we changed our focus from supporting discovery and use of datasets and … Continue reading Cooking up a new approach to supporting purposeful use of data
Getting the most value from data, whilst minimising its harmful impacts, is a community activity. Datasets need to be governed and published well. Most of that responsibility falls on the data publisher. Because the choices they make shapes data ecosystems. But other people have a role to play too. Being a good data user means … Continue reading How can you help support the use of a dataset?
Last month I wrote a post looking at how publishing new data might increase the value of existing data. I ended up listing seven different ways including things like improving validation, increasing coverage, supporting the ability to link together datasets, etc. But that post only looked at half of the issue. What about the opposite? … Continue reading How can publishing more data decrease the value of existing data?
There's lots to love about the "Value of Data" report. Like the fantastic infographic on page 9. I'll wait while you go and check it out. Great, isn't it? My favourite part about the paper is that it's taught me a few terms that economists use, but which I hadn't heard before. Like "Incomplete contracts" … Continue reading How can publishing more data increase the value of existing data?
Whenever you're accessing, using or sharing data you will be bound by a variety of laws and agreements. I've written previously about how data governance is a nested set of rules, processes, legislation and norms. In this post I wanted to clarify the differences between three types of agreements that will govern your use of … Continue reading Three types of agreement that shape your use of data
We're at the end of week 5 of 2020, of the new decade and I'm on a diet. I'm back to using MyFitnessPal again. I've used it on and off for the last 10 years whenever I've decided that now is the time to be more healthy. The sporadic, but detailed history of data collection … Continue reading When can expect more from data portability?
It's hard to read an article about data science or really anything that involves creating something useful from data these days without tripping over this factoid, or some variant of it: Data scientists spend 80% of their time cleaning data rather than creating insights. Or Data scientists only spend 20% of their time creating insights, … Continue reading Do data scientists spend 80% of their time cleaning data? Turns out, no?
This blog post is a quick review and notes relating to a research paper called: The Coerciveness of the Primary Key: Infrastructure Problems in Human Services Work (PDF available here) It's part of my new research notebook to help me collect and share notes on research papers and reports. Brief summary This paper explores the … Continue reading [Paper Review] The Coerciveness of the Primary Key: Infrastructure Problems in Human Services Work
This is the latest in a series of posts in which I explore some basic questions about data. In our work at the ODI we have often been asked for advice about how best to publish data. When giving trying to give helpful advice, one thing I'm always mindful of is how the decisions about … Continue reading How do data publishing choices shape data ecosystems?
This is a summary of a short talk I gave internally at the ODI to help illustrate some of the important aspects of data standards for non-technical folk. I thought I'd write it up here too, in case its useful for anyone else. Let me know what you think. We benefit from standards in every … Continue reading Lets talk about plugs