5-Stars of Open Data Engagement?

[Summary: Notes from a workshop at UKGovCamp that led to sketching a framework to encourage engagement and impact of open data initiatives might contain]

Update: The 5 Stars of Open Data Engagement now have their own website at http://www.opendataimpacts.net/engagement/.

In short

* Be demand driven

* * Provide context

* * * Support conversation

* * * * Build capacity & skills

* * * * * Collaborate with the community

The Context

I’ve spent the last two days at UKGovCamp, an annual open-space gathering of people from inside and around local and national government passionate about using digital technologies for better engagement, policy making and practice. This years event was split over two days: Friday for conversations and short open-space slots; Saturday for more hands-on discussions and action. Suffice to say, there were plenty of sessions on open data on both days – and this afternoon we tried to take forward some of the ideas from Day 1 about open data engagement in a practical form.

There is a general recognition of the gap between putting a dataset online, and seeing data driving real social change. In a session on Day 1 led by @exmosis, we started to dig into different ways to support everyday engagement with data, leading to Antonio from Data.gov.uk suggesting that open data initiatives really needed to have some sort of ‘Charter of engagement’ to outline ways they can get beyond simply publishing datasets, and get to supporting people to use data to create social, economic and administrative change. So, we took that as a challenge for day 2, and in session on ‘designing an engaging open data portal’ a small group of us (including Liz StevensonAnthony Zacharzewski, Jon Foster and Jag Goraya) started to sketch what a charter might look like.

You can see the (still developing) charter draft in this Google Doc. However, it was Jag Goraya‘s suggestion that the elements of a charter we were exploring might also be distilled into a ‘5 Stars’ that seemed to really make some sense of the challenge of articulating what it means to go beyond publishing datasets to do open data engagement. Of course, 5-star rating scales have their limitations, but I thought it worth sharing the draft that was emerging.

What is Open Data Engagement?

We were thinking about open data engagement as the sorts of things an open data initiative should be doing beyond just publishing datasets. The engagement stars don’t relate to the technical openness or quality of the datasets (there are other scales for that), and are designed to be flexible to be able to apply to a particular dataset, a thematic set of datasets, or an open data initiative as a whole.

We were also thinking about open government data in our workshop; though hopefully the draft has wider applicability. The ‘overarching principles’ drafted for the Charter might also help put the stars in context:

Key principles of open government data: “Government information and data are common resources, managed in trust by government. They provide a platform for public service provision, democratic engagement and accountability, and economic development and innovation. A commitment to open data involves making information and data resources accessible to all without discrimination; and actively engaging to ensure that information and data can be used in a wide range of ways.”

Draft sketch of five stars of Open Data Engagement

The names and explanatory text of these still need a lot of work; you can suggest edits as comments in the Google Doc where they were drafted.

* Be demand driven

Are your choices about the data you release, how it is structured, and the tools and support provided around it based on community needs and demands? Have you got ways of listening to people’s requests for data, and responding with open data?

** Provide good meta-data; and put data in context

Do your data catalogue provide clear meta-data on datasets, including structured information about frequency of updates, data formats and data quality? Do you include qualitative information alongside datasets such as details of how the data was created, or manuals for working with the data? Do you link from data catalogue pages to analysis your organisation, or third-parties, have already carried out with the data, or to third-party tools for working with the data?

Often organisations already have detailed documentation of datasets (e.g. analysis manuals and How To’s) which could be shared openly with minimal edits. It needs to be easy to find these when you find a dataset. It’s also common that governments have published analysis of the datasets (they collected it for a reason), or used it in some product or service, and so linking to these from the dataset (and vice-versa) can help people to engage with it.

*** Support conversation around the data

Can people comment on datasets, or create a structured conversation around data to network with other data users? Do you join the conversations? Are there easy ways to contact the individual ‘data owner’ in your organisation to ask them questions about the data, or to get them to join the conversation? Are there offline opportunities to have conversations that involve your data?

**** Build capacity, skills and networks

Do you provide or link to tools for people to work with your datasets? Do you provide or link to How To guidance on using open data analysis tools, so people can build their capacity and skills to interpret and use data in the ways they want to? Are these links contextual (e.g. pointing people to GeoData tools for a geo dataset, and to statistical tools for a performance monitoring dataset)? Do you go out into the community to run skill-building sessions on using data in particular ways, or using particular datasets? Do you sponsor or engage with community capacity building?

When you give people tools – you help them do one thing. When you give people skills, you open the possibility of them doing many things in future. Skills and networks are more empowering than tools. 

***** Collaborate on data as a common resource

Do you have feedback loops so people can help you improve your datasets? Do you collaborate with the community to create new data resources (e.g. derived datasets)? Do you broker or provide support to people to build and sustain useful tools and services that work with your data?


It’s important for all the stars that they can be read not just with engaging developers and techies in mind, but also community groups, local councillors, individual non-techie citizens etc. Providing support for collaboration can range from setting up source-code sharing space on GitHub, to hanging out in a community centre with print-outs and post-it notes. Different datasets, and different initiatives will have different audiences and so approaches to the stars – but hopefully there is a rough structure showing how these build to deeper levels of engagement.

Where next?

Hopefully Open Data Sheffield will spend some time looking at this framework at a future meeting – and all comments are welcome on the Google doc. Clearly there’s lot to be done to make these more snappy, focussed and neat – but if we do find there’s a fairly settled sense of a five stars of engagement framework (if not yet good language to express it) then it would be interesting to think about whether we have the platforms and processes in place anywhere to support all of this: finding the good practice to share. Of course, there might already be a good engagement framework out there we missed when sketching this all out – so comments to that effect welcome too…

 

Updates:

Ammended 22nd January to properly credit Antonio of Data.gov.uk as originator of the Charter idea

Exploring Open Charity Data with Nominet Trust

[Summary: notes from a pilot one-day working on open data opportunities in third-sector organisations]

On Friday I spent the day with Nominet Trust for the second of a series of charity ‘Open Data Days’ exploring how charities can engage with the rapidly growing and evolving world of open data. The goal of these hands-on workshops is to spend just one working day looking at what open data might have to offer to a particular organisation and, via some hands-on prototyping and skill-sharing, to develop an idea of the opportunities and challenges that the charity needs to explore to engage more with open data.

The results of ten open data days will be presented at a Nominet Trust, NCVO and Big Lottery Fund conference later in the year, but for now, here’s a quick run-down / brain-dump of some of the things explored with the Nominet Trust team.

What is Open Data anyway?

Open data means many different things to different people – so it made sense to start the day looking at different ways of understanding open data, and identifying the ideas of open data that chimed most with Ed and Kieron from the Nominet Trust Team.

The presentation below runs through five different perspectives on open data, from understanding open data as a set of policies and practices, to looking at how open data can be seen as a political movement or a movement to build foundations of collaboration on the web.


Reflecting on the slides with Ed and Kieron highlighted that the best route into exploring open data for Nominet Trust was looking at the idea that ‘open data is what open data does’ which helped us to set the focus for the day on exploring practical ways to use open data in a few different contexts. However, a lot of the uses of open data we went on to explore also chime in with the idea of a technical and cultural change that allows people to perform their own analysis, rather than just taking presentations of statistics and data at face value.

Mapping opportunities for open data

Even in a small charity there are many different places open data could have an impact. With Nominet Trust we looked at a number of areas where data is in use already:

  • Informing calls for proposals – Nominet Trust invite grant applications for ideas that use technology for disruptive innovation in a number of thematic areas, with two main thematic areas of focus live at any one time. New thematic areas of focus are informed by ‘State of the Art’ review reports. Looking at one of these it quickly becomes clear these are data-packed resources, but that the data, analysis and presentation are all smushed together.
  • Throughout the grant process – Nominet Trust are working not only to fund innovative projects, but also to broker connections between projects and to help knowledge and learning flow between funded projects. Grant applications are made online, and right now, details of successful applicants are published on the Trust’s websites. A database of grant investment is used to keep track of ongoing projects.
  • Evaluation – the Trust are currently looking at new approaches to evaluating projects, and identifying ways to make sure evaluation contributes not only to an organisations own reflections on a project, but also to wider learning about effective responses to key social issues.

With these three areas of data focus, we turned to identify three data wishes to guide the rest of the open data day. These were:

  • Being able to find the data we need when we need it
  • Creating actionable tools that can be embedded in different parts of the grant process – and doing this with open platforms that allow the Nominet Trust team to tweak and adapt these tools.
  • Improving evaluation – with better data in, and better day out

Pilots, prototypes and playing with data

The next part of our Open Data Day was to roll up our sleeves and to try some rapid experiments with a wide range of different open data tools and platforms. Here are some the experiments we tried:

Searching for data

We imagined a grant application looking at ways to provide support to young people not in education, employment or training in the Royal Borough of Kensington and Chelsea, and set the challenge of finding data that could support the application, or that could support evaluation of it. Using the Open Data Cook Book guide to sourcing data, Ed and Keiron set off to track down relevant datasets, eventually arriving at a series of spreadsheets on education stats in London on the London Skills and Employment Observatory website via the London Datastore portal.  Digging into the spreadsheets allowed the team to put claims that could be made about levels of education and employment exclusion in RBKC in context, looking at the difference interpretations that might be drawn from claims made about trends and percentages, and claims about absolute numbers of young people affected.

Learning: The data is out there; and having access to the raw data makes it possible to fact-check claims that might be made in grant applications. But, the data still needs a lot of interpretation, and much of the ‘open data’ is hidden away in spreadsheets.

Publishing open data

Most websites are essentially databases of content with a template to present them to human readers. However, it’s often possible to make the ‘raw data’ underlying the website available as more structured, standardised open data. The Nominet Trust website runs on Drupal and includes a content type for projects awarded funding which includes details of the project, it’s website address, and the funding awarded.

Using a demonstration Drupal website we explored how the Drupal Views and the Views Bonus Pack open source modules it was easy to create a ‘CSV’ open data download of information in the website.

The sorts of ‘projects funded’ open data this would make available from Nominet Trust might be of interest to sites like OpenlyLocal.com which are aggregating details of funding to many different organisations.

Learning: You can become an open data publisher very easily, and by hooking into existing places where ‘datasets’ are kept, keeping your open data up-to-date is simple.

Mashing-up datasets

Because open datasets are often provided in standardised forms, and the licenses under which data is published allow flexible re-use of the data, it becomes easy to mash-up different datasets, generating new insights by combining different sources.

We explored a number of mash-up tools. Firstly, we looked at using Google Spreadsheets and Yahoo Pipes to filter a dataset ready to combine it with other data. The Open Data Cook Book has a recipe that involves scraping data with Google Spreadsheets, and a Yahoo Pipes recipe on combing datasets.

Then we turned to the open data powertool that is Google Refine. Whilst Refine runs in a web browser, it is software you install on your own computer, and it keeps the data on your machine until you publish it – making a good tool for a charity to use to experiment with their own data, before deciding whether it will be published as open data or not.

We started by using Google Refine to explore data from OpenCharities.org – taking a list of all the charities with the word ‘Internet’ in their description that had been exported from the site, and using the ‘Facets’ feature (and a Word Facet) in Google Refine to look at the other terms they used in their descriptions. Then we turned to a simple dataset of organisations funded by Nominet Trust, and explored how by using API access to OpenlyLocal.com’s spending dataset we could get Google Refine to fetch details of which Nominet Trust funded organisations had also recieved money from particular local authorities or big funders like Big Lottery Fund and the Arts Council. This got a bit technical, so a step-by-step How To will have to wait – but the result was an interesting indication of some of the organisations that might turn out to be common co-funders of projects with Nominet Trust – a discovery enabled by those funders making their funding information available as open data.

Learning: Mash-ups can generate new insights – although many mash-ups still involve a bit of technical heavy-lifting and it can take some time to really explore all the possibilities.

Open data for evaluation

Open data can be both an input and an output of evaluation. We looked at a simple approach using Google Spreadsheets to help a funder create evaluation online evaluation tools for funded projects.

With a Google Docs account, we looked at creating a new ‘Form’. Google Forms are easy to create, and let you design a set of simple survey elements that a project can fill in online, with the results going directly into an online Google Spreadsheet. In the resulting spreadsheet, we added an extra tab for ‘Baseline Data’, and exploring how the =ImportData() formula in Google Spreadsheet can be used to pull in CSV files of open data from a third party, keeping a sheet of baseline data up-to-date. Finally, we looked at the ‘Publish as a Web Page’ feature of Google Spreadsheets which makes it possible to provide a simple CSV file output from a particular sheet.

In this way, we saw that a funder could create an evaluation form template for projects in a Google Form/Spreadsheet, and with shared access to this spreadsheet, could help funded projects to structure their evaluations in ways that helped cross-project comparison. By using formulae to move a particular sub-set of the data to a new sheet in the Spreadsheet, and then using the ‘Publish as a Web Page’ feature, non-private information could be directly published as open data from here.

Learning: Open data can be both an input to, and an output from, evaluation.

Embeddable tools and widgets

Working with open data allows you to present one interpretation or analysis of some data, but also allow users of your website or resources to dig more deeply into the data and find their own angles, interpretations, or specific facts.

When you add a ‘Gadget’ chart to a Google Spreadsheet of data you can often turn it into a widget to embed in a third party website. Using some of the interactive gadgets allows you to make data available in more engaging ways.

Platforms like IBM’s Many Eyes also let you create interactive graphs that users can explore.

Sometimes, interactive widgets might already be available, as in the case of Interactive Population pyramids from ONS. The Nominet Trust state of the art review on Aging and use of the Internet includes a static image of a population pyramid, but many readers could find the interactive version more useful.

Learning: If you have data in a report, or on a web page, you can make it interactive by publishing it as open data, and then using embeddable widgets.

Looking ahead

The Open Data Day ended with a look at some of the different ways to take forward learning from our pilots and prototypes. The possibilities included:

Sooner

  • Quick wins: Making funded project data available as structured open data. As this information is already published online, there are not privacy issues with making it available in a more structured format.
  • Developing small prototypes taking the very rough proof-of-concept ideas from the Open Data Day on a stage, and using this to inform plans for future developments. Some of the prototypes might be interactive widgets.
  • A ‘fact check’ experiment: taking a couple of past grant applications, and using open data resources to fact-check the claims made in those applications. Reflecting on whether this process offers useful insights and how it might form part of future processes.
  • Commissioning open data along with research: when Nominet Trust commissions future State of the Art reviews it could include a request for the researcher to prepare a list of relevant open datasets as well, or to publish data for the report as open data.

Later

  • Explore open data standards such as the International Aid Transparency Initiative Standard for publishing project data in a more detailed form.
  • Building our own widgets and tools: for example, tools to help applicants find relevant open data to support their application, or tools to give trustees detailed information on applicant organisations to help their decision making.
  • Building generalisable tools and contributing to the growth of a common resource of software and tools for working with open data, as well as just building things for direct organisational use.

Where next?

This was just the second of a series of Open Data Days supported by Nominet Trust. I’m facilitating one more next month, and there are a team of other consultants working with varied other charities over the coming weeks. So far I’ve been getting a sense of the wide range of possible areas open data can fit into charity work (it feels quite like exploring the ways social media could work for charities did back in 2007/8…), but there’s also much work to be done identifying some of the challenges that charities might face, and sustainable ways to overcome them. Lots more to learn….