[@OKau] Intelligent Data Management

Cobi Alison Smith cobi.smith at unimelb.edu.au
Mon May 11 08:51:44 UTC 2015

I strongly agree with Ben's comments about the need for documentation to accompany data, and in my mind this dovetails well with what Rosie has been saying about putting community needs first. A few years back I created this article on Wikipedia, which has since been built on by others:

The kind of documentation work Ben's talking about it part of a participatory evaluation process (which should begin at the start of the project), as it helps to clarify within a community what makes data meaningful, what intended uses of data could be, and how use can be supported. This ownership aspect is important - as Steven added, let the custodians publish so they can learn how - and if they don't know, invest in building capacity.

Organisations that have silos of funding for communication and evaluation separate to operational and development funding can typically benefit from linking these silos together. All too often I'm asked to come into some project 6 months before its funding runs out to do a marketing/communications/"positive evaluation" work as part of justifying further funding... whereas if a project began with community needs in mind, those things would have emerged throughout the project cycle without an artificial push at the end. Part of the ethics of evaluation work is managing expectations about positive evaluations and enforcing reporting about "unexpected outcomes", both good and bad.

It's refreshing to see big international donors recognising that independent external project evaluations aren't as productive as participatory action projects with communities - that translates in my mind to smaller scale startup projects in not waiting until user interface design to consult with users, but rather investigating the whole user experience from project conception forwards, which may be more costly upfront but results in more meaningful and valuable products.

In terms of changing organisational culture... valuing people elements of open data projects as much as technical elements seems to be a theme on this list of late :)

From: okfn-au [okfn-au-bounces at lists.okfn.org] on behalf of Steven De Costa [steven.decosta at linkdigital.com.au]
Sent: Monday, 11 May 2015 9:27 AM
To: Open Knowledge discussion list for Australia.
Subject: Re: [@OKau] Intelligent Data Management

Yep. Publish via CKAN :) internally as an information asset register or externally as open data.

And, let the custodians publish so the learn how. If they don't know how then teach them :)

On Monday, May 11, 2015, Ben Searle <ben at odiqueensland.org.au<mailto:ben at odiqueensland.org.au>> wrote:

I earlier emails last week I wrote about what i was calling the missing link, and suggested that many agencies get no or little value from participating in the open data movement.

I also referred to a concept I called intelligent Data Management.  This raised a few comments….

I would like to elaborate on the Intelligent Data Management concept.

In simple terms Intelligent Data Management is where an organisation is at a data management maturity level where it appreciates the value of the data it collects and creates and applies appropriate organisational support to the data creation process.  By this I mean that data is well document by those that create it.  A simple concept, but one vary rarely undertaken, at least in my experience.

Documenting data is not a natural thing for an organisation, those that are best placed to do this have no real business need to do it (they already know all about the data), they also are not given any incentive to document the data, in fact often the opposite.  They are pressured to produce more data, not ‘waste’ time on documenting the data.

What happened in most organisations with data not effectively documented?  It cannot  be easily located for re-use.  Also, if it is found, then because e potential new user cannot understand its provenance, then they are unsure if it is suitable for re-use and often re-create the data.

This costs the organisation a considerable amount in resources, lost opportunities and poor decisions.

A simple fix is to have an organisational culture (supported strongly by senior management) that data is an asset and should be treated as such.  This means that any data collected or created must be effectively documented.  This takes a small amount of additional resources but this ‘additional cost’ is returned as a significant reduction in the cost of ‘not finding data’ for this organisation.

Data creators need incentives to document the data they create and their managers also =need to be rewarded for this effort.

This is not rocket science, just organisational culture.

As an analogy, when successful document management systems (DMS) are implemented, as much is spent on staff training and cultural change (to ensure each document is effectively described) as is spent on the actual technology so that the DMS actually works and returns on the investment.  Examples of this are common and the same principle applies to data management.  Organisation focus on the technology, not the organisational culture….

What has this to do with open data?  If an organisation has its data sets well described locatable and usable, it becomes a much simpler exercise to make the data publicly available.  Additionally, when the data is well documented, its value to the open data community is significantly higher…

So, any thoughts, on how to change this organisational cultural barrier?


ODI Queensland

0400 453 601
ben at odiqueensland.org.au<UrlBlockedError.aspx>

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Queensland  4000  Australia


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