Thinking in networks
One of the things I most often find myself telling people is that I don’t think in lists. I think in networks.
I think like this because:
- they show linkages between concepts and ideas
- they can help give an idea of priorities — those nodes with the most connections may be the best things to work on first (or the most complicated, of course!)
- they intuitively make more sense to me :)
Here’s a recent example.
- promote open data
- lift data management capability
- connect data communities, and
- build data literacy.
I was also asked what gaps and opportunities I saw — some are covered in my ideas for the above :)
The temptation would be to list some items under each bullet point. But I saw that not only are each of those four points linked to each other, but so are many of the ideas for each.
So I made a (very simple!) network graph.
I thought it told a more compelling story. It also meant I got to play with tool I’d not used before (kumu) and so learn while working — definitely an approach of which I’m in favour.
Note: these are just some of my ideas, presented very briefly and in overview. They’re _definitely_ not to be taken as any sort of commitment or road plan (yes, I got the job!).
If you’re curious, you can also check out the individual slides.
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Plain text version
Here’s (roughly) what I said :)
The best way to sum up the role I think data.govt could play is as the hub for data-related conversations in NZ, especially as they relate to government and communities.
One of the major priorities, I believe, is to work especially hard on improving knowledge and skills — I see from the dashboard that this aspect has gone down since last year — and target the final two columns in the open government data programme progress report to June 2018.
Data is, like tech, now core infrastructure underpinning almost every aspect of our society, so I see “community” as an extremely important consideration.
Some ideas follow.
Guides and tutorials
Examples include how-to guides (glad to see we’ve started) covering a range of user expertise, including how to map things, how to clean data, appropriate and inappropriate uses of data / datasets, why metadata is important, etc
Target content to user expertise
New York City’s data portal is a great example of targeting resources to user type, too, and one from which we could learn.
Stories / case studies — questions asked, and how answered
A huge part of how to get people on board with data literacy, and open data, is helping people to tell their own stories. Sharing stories about what questions other people have asked, and what they did, would be a huge kickstart.
There’s enormous scope to help empower and upskill all sorts of communities all over NZ.
To illustrate how important this is, in my head, the site’s tagline is something like “data.govt — tell your story”.
For example, I know that iwi often aren’t sure, when it comes to data:
- what questions to ask
- what questions the data can (and can’t) answer
- where to begin, etc.
And I know they’re very tired of other people telling their stories for them.
Connect data communities
Stories and guides are some of the ways to connect our data communities.
But we should not only connect, but broaden the data community, lifting literacy amongst existing data users and suppliers, and also bringing more people on board.
Diversity, inclusion and belonging (DIB) are key considerations.
Expand the conversation
We could (should?) also expand the conversation in general. It’s bigger than just open data. We need to be thinking about data more broadly, but openness still needs to be woven in where it should be — open standards and formats are THE key thing for this, as they have a significant impact on interoperability and the ability to share and collaborate around data. Pointing to resources like datastandards.directory would be a great start!
Conversations around issues and challenges
We need to engage openly and honestly around issues with data, and open data (and yes, “AI” / machine learning touch all of these), for example:
Māori data sovereignty
This includes discomfort with some aspects of open data, especially as it pertains to open data about Māori (it was especially interesting hearing about this at last year’s Data Iwi Leaders Group conference)
Security, privacy and anonymisation
A priority in the implementation plan is to make agencies aware of the PC’s Privacy Impact Assessment Toolkit. Could we make that into a webform of some sort, too, to make it easier to use?
Big vs small data
Research has shown that small datasets can provide insights just as well as big data, without the accompanying privacy etc concerns. They’re also easier to manage, easier to analyse, and so forth.
There’s a great article summing up some of the issues at https://diigo.com/0d3unz.
Difficulties around opening data
These include dataset prioritisation and preparation, resourcing (humans), infrastructure, knowledge, skills, and concerns such as privacy.
Control and access to open data (and resources to use it)
For example, the issues mentioned in “Seeing like a geek”, https://diigo.com/0d4bqm.
Map NZ’s openX communities
It would be helpful to have a much more detailed picture of NZ’s open data-and-related communities. We have some links on the site, but we need more.
I see it as a network rather than list — in fact, a couple of years ago I developed and built a proof of concept for a network graph of NZ’s openX communities (and will update it here in the near future).
Private sector / NGOs
We could do more to engage with NZ’s private and NGO sectors, both generally around data and specifically around open data — I gave a talk about the former at APIdays in 2016.
OpenX / civic hackers / civic tech
We could use data.govt as a primary interface with NZ’s openX and civic hacking communities, and do more to showcase projects which use open data, including having content on how communities use data.
Promote open data
In addition to everything else mentioned here, we could go further — for example, we could actively engage in more conversations on Twitter, as well as looking for other channels (including offline!) to engage with.
Concept: weekly challenges, based on issues (we could poli.is!), or user-generated questions, or fun questions to use data to answer (the Grow GIS group on Facebook does this well, for example).
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