Tag Archives: Open Data

Is it getting hot in here?

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Lisa Allen said MenopauseX came out of Women in Data, which was set up to address barriers to women taking up employment.

A high proportion of women drop out in their 50s, as they go through perimenopause or menopause. So, MenopauseX is looking for data that can explain this. “We are looking for a smoking gun,” Lisa said.

“We publish stats for population, and aging, but there are other data sets that might be useful, like how many women go part-time, or drop out? “How can we get data out of companies to help them tackle these issues? What I want to get out of this session is help – how do we do this?”

One participant suggested one challenge is that it can be hard to disentangle issues connected with the menopause from issues associated with mid-life in general – weariness, caring for elderly relatives, careers stalling.

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Generative AI, large language models and open data

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Alex Ivanov, a data scientist from Faculty, wanted to talk about some of the technology that has been making waves in the press recently.

Usefully, he started by defining a few terms. “LLMs are a subset of AI models,” he said. “They are trained on vast amounts of text data and they can learn the intricacies of human language to do things like answer questions or search databases. At heart, they are trained to predict the next piece of text.

“Generative AI is a wider thing that can create things that are new, including text, and images, and even drugs: they are very broad. So, in any AI, we are talking about a machine learning from data. And the main difference between normal AI and generative AI is the output.

“In traditional AI, we focus on data and classification, to predict things like whether someone will develop diabetes, or even house prices. Wheras with generative AI we create data that was not there already.

“Where open data comes in is that these models are often trained on big datasets, so it can provide the raw material. However, there are certain challenges. One is data quality. If you just pick up lots of data without thinking about its quality that can cause problems.

“Then, there is privacy. Most open data doesn’t identify individuals, but there are some cases where that can happen. You need standardisation to bring all these sources together. Scaleability can be an issue. There are legal issues.

“And we need to think about transparency: some of these AIs are like black boxes, their outputs are almost like magic, so we need to understand what kind of output they are likely to have, and what impact that is likely to make.

“So, I’d like to think about how open data works in this context, and how we address some of these issues around transparency and bias.”

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The NHS, open data, and AI

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This session was led by John Kellas, an expert in community development in healthcare, and the “complicated” subject of healthcare, AI and licensing. He asked people to share anything they felt was important, with a view to making recommendations to policy makers.

“In 2017, I helped run a series of webinars on AI in healthcare,” he said, “and on the back of that I was asked to be part of the Academic Health Science Network core AI advisory group and support the development of a national survey on AI in healthcare.

“I was already interested in open data and open source, so I asked for a small question on licensing to be included in this survey. What we found was that about 38% was proprietary, and much less was open source, although there was a lot of ‘don’t want to say’ or ‘don’t know.’

“Since then, we’ve had a £250 million pot for AI in the NHS, and some vague talk about a value return. But I think there is room for something stronger. Because it’s clear that the data for AI is very valuable, and it’s reasonable to think that patients should get some return for it.

“And at the moment, there seems to me to be an issue around whether the NHS is going to procure AI, or develop it, and how we are going to secure that value is not really clear.”

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Helloooo Wolverhampton!

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Welcome to the Live Blog for Open Data Camp 8.

We’re at the University of Wolverhampton’s Springfield Campus, which is a modern building, updating a brewery, and who couldn’t like that? Ahead of us lie two days of ‘unconferencing’ about all things open data.

Stand by for updates on the pitching, the discussions about the hot topics in data collection and use, and some great examples of why open data really matters. It’s going to lively, it’s going to be FUN…

ODCamp 7: Thank you and goodbye

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And so, as night draws in, the latest Open Data Camp draws to a close. Thank you to all the sponsors, the camp organisers, and the campers. Open Data Camp moves around: it has now been in Aberdeen, Belfast, Bristol, Cardiff, London, Manchester and Winchester. Where will it be next? That depends on… someone volunteering to take it on…

If you are interested in hosting the event, then get in touch. But, for now, catch up on all the blog posts, Tweet (using the hashtag #ODCamp), blog, and generally pass on all the good stuff from two great days. And we’ll see you at the next one.

ODCamp 7: Horror stories…

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Just a few days after Halloween, and with pumpkins adorning the refreshment tables at Open Data Camp 7, campers gathered at the end of day two to swap open data horror stories. Or, as leader Dan Barrett put it, to learn from their experiences and mistakes. Because that can be cathartic — and helpful for others.

Story one

A reflection on working at [a large public institution] and spending six years trying to improve its open data division. “I recognised that there was a division between its work and public understanding of what it did. And I thought open data could help to bridge that.” Things were going fairly well. “And then they went spectacularly badly, and the work stopped.”

What did the teller learn? “That it is important to own the story of your own work, and to think about how you tell it to other people,” particularly in an environment in which others are seeking to benefit from telling a counter-narrative, “discounting the work you do, playing down the benefits of what you do”, and diverting resources to other priorities. “So that is the lesson I am taking into a new role: Tell stories that resonate with everybody about data.”

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ODCamp 7: Getting started on a guide to getting started

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Post lunch on the second day of Open Data Camp 7, and Simon Worthington from Register Dynamics set up a practical session to making a start on a guide to getting started with open data. With sticky notes, of course. So, he asked participants, what would they have needed to know when they were getting started? And what resources would they have pointed people towards the answer those questions?

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Registers: why they matter and how to save them

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A Open Data Camp 7 session on registers, led by Andy Bennet of registers.app.

At the end of 2015, there was a project in the Government Digital Service about the structure of data. There was open.gov.uk, where the data was quite unstructured. The consumer had to wrangle it into the form they needed. In the legalisation, there were hundreds of thousands of mentions of registers – datasets that different departments and minsters needed to keep. The idea was to publish these registers of things government knows.

One core principle: these are owned and maintained registers. This makes them about governance – about making sure that there are people in positions of power with responsibility for them. You can’t spread the decision-making around – it has to be a named individual. There’s been some work done by the Open Data Institute in the last year about collaborative ownership models.

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ODCamp 7: Ten years of open data. What have we learned?

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Tim Davies has written a book: The State of Open Data (@stateofopendata) with the support of international development and open data organisations and the OD4D.net initiative.

So he wanted to run a retrospective of the first ten years of open data at Open Data Camp 7 in London: and to find out from campers what their experience had been: “the good, the bad, the in between.”

First, the book. “We recognised sometime last year that we were coming up on a decade since President Obama made a splash on open data in the US and the UK launched the Open Data Institute. So we put up some Google documents and looked at seven areas to brainstorm thoughts about what had happened in them.”

More than 200 people pitched in ideas, and commented on events and initiatives from different perspectives. Then, the authors – 40% of whom were women, and many of whom come from the global south – were asked to comment and revise what became 6,000 word chapters.

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ODCamp 7: Going green(er) with open procurement data

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Day two of Open Data Camp 7 at Geovation in London started with a session on public sector procurement data, and how it could be used to encourage green initiatives. Ian Makgill introduced the session. His company has a site that captures public tender information and makes it “freely available to everyone” and then analyses the data to say “oh look, this is how much work this company has got” or “here’s a trend in a particular kind of spending.”

However, he said, while this was interesting, it wasn’t having a big impact on organisational behaviour. But: “What we realised is that suppliers are very interested in when contracts are coming to an end. That’s understandable, but it’s also a massive leverage point at which the public could encourage procurement that reduces carbon.”

After all, government spends around £12.9 billion a year on things, and those things are responsible for about 17% of carbon output, because they are things like roads, and airports. So there should be an opportunity for experts and the public to get in and argue that setting a contract in a different way will induce change.

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