Aimee Whitcroft – Open Data Establishment Lead, New Zealand Transport Agency (NZTA)
While many people know about the value of releasing and using open data, many organisations are unsure how to go about it: where to start, what to bear in mind, and how to keep going.
This means that organisations open data in scattershot or ad-hoc ways, or poorly (for example, not looking after privacy properly), or don’t open (appropriate) data at all. None of this allows us to leverage the enormous (positive) potential value of the data that organisations collect.
To help address this situation, we at NZTA have been working on developing a simple open data framework and processes. As part of working in the open, and our ‘iterate and optimise’ philosophy, we’re releasing them openly for comment and feedback.
After all, they’re resources devoted to opening things :D
Also, after reading about the first version of our open data framework and processes, check out the follow up blog post we wrote about implementation.
A Framework and process for opening data, part 2
The framework and processes were developed after reviewing other publicly available open data frameworks from around the world* – including New Zealand – and are still very much a first rough version. We’re working to flesh out the governance layers more, and these (especially) will differ between different organisations.
The idea is that the framework and processes form a living resource, and that people continue to iterate, adapt, and optimise them for their own uses.
You can use them as a resource for a dataset in any part of the lifecycle, including datasets which you’re considering opening, or datasets you’ve already opened.
And we’re developing the more detailed processes underlying them (you’ll see references to toolkit worksheets etc). The prioritisation process(es) especially are a fascinating challenge :)
We’d love to know what you think!
You can get in touch with me at aimee.whitcroft (at) nzta.govt.nz
Alternatively, come along to an open data doers’ catchup :)
The work above – and people’s interest in it – led to a thought, now validated with some fab peeps.
If you're working on building such frameworks / processes, for example, or are an open data practitioner, you're invited to a monthly lunchtime session we’re starting, as of early August. It’s an opportunity to share thoughts, challenges, ideas, and knowledge, and fill gaps rather than reinvent wheels :) All welcome!
Let me know if you’d like to come along – email me at aimee.whitcroft (at) nzta.govt.nz
NZTA’s open data framework – overview. Image explained in text below. Credit: NZTA. Licence: CC-BY 4.0 International.
NZTA’s open data framework – details. Image explained in text below. Credit: NZTA. Licence: CC-BY 4.0 International.
Identify the dataset(s) you’re considering opening using a range of internal and external sources.
Components:
Assess the dataset(s) for appropriateness to publish (eg risk assessments, privacy assessments, etc), and gain approval to continue the opening process.
Components:
Prioritise the dataset(s) against other open dataset candidates, using a range of prioritisation metrics.
Components:
Prepare the dataset(s) for publishing, including preparing the relevant metadata and documentation.
Components:
Gain final approval to publish the dataset(s) and accompanying metadata.
Publish the dataset(s) and accompanying metadata on the open data portal, list them on other relevant sites like data.govt.nz, and engage with user groups.
Components:
Measure and report against the use of and feedback about the datasets, feeding that info into data quality and change processes, as well as steps 1, 3, 6 and 7 (informing what to measure / report against).
Components:
The data governance layer is made up, essentially, of:
We’re working through the details of the functions associated with these.
Note: the data custodian role may be filled, at least in part, by an organisational open data champion.
Inputs:
Outputs:
Inputs:
Outputs:
Inputs:
Outputs:
Inputs:
Outputs:
Inputs:
Outputs:
Inputs:
Outputs:
Inputs:
Outputs:
We’ve built some very basic automation for these, to mark where outputs automatically mean the inputs for another step are completed – the idea is to help prevent accidental duplication, and save time.
Interested in the more detailed processes, or the information management side of all this (ie the documents we’ll be setting up and running)? Get in touch :)
Check out part 2 on the open data framework journey
A Framework and process for opening data, part 2
let us know if you’d like a list of reading materials / references :)