I facilitated two unconferences this week. On Monday with our company The Green Land we hosted a 90 minute unconference on (the future of) open government. It was a sweltering day, without much wind. Held on the rooftop of our office building, we had precisely the amount of shade needed to keep all participants out of the sun. With some 20 people from around our network we compared notes on open government, civic tech, and potential collective action. Having built the program with the group I participated in conversations on public versus market roles, what ‘sticks‘ we have in our toolbox when working towards more open government, and the Dutch Common Ground program.

A group in discussion
Groups in conversation

The program
The program

We ended with a fun ‘open government pubquiz’ led by my colleagues Frank and Niene.

(At CaL earlier this month in Canada, someone asked me if I did unconference facilitation as work. I said no, but then realised I had two events lined up this week putting the lie to that ‘no’. This week E suggested we might start offering training on how to host and facilitate an unconference.)

A new weblog has been started by Anna Powell-Smith, called Missing Numbers:

Missing Numbers is a blog about the data that the government should collect and measure in the UK, but doesn’t.

I expect that whatever she finds in missing data within the UK public sector, similar or matching examples can be found in other countries, such as here in the Netherlands.

One such Dutch example are the election results per candidate per polling station. The election council (Kiesraad) that certifies election results only needs the aggregated results per municipality, and that is what it keeps track of. Local governments of course have this data immediately after counting the votes, but after providing that data to the Kiesraad their role is finished.

The Open State Foundation (disclosure: I’m its current chairman of the board) in recent years has worked towards ensuring results per polling station are available as open data. In the recent provincial and water authority elections the Minister for the Interior called upon municipalities to publish these results as machine readable data. About 25% complied, the other data files were requested by the Open State Foundation in collaboration with national media to get to a complete data set. This way for the first time, this data now exists as a national data set, and is available to the public.

Viz of all polling station results of the recent elections by the Volkskrant national paper

Added Missing Numbers to my feedreader.

Today I gave short presentation at the Citizen Science Koppelting conference in Amersfoort. Below is the transcript and the slidedeck.

I’ve worked on opening data, mainly with governments worldwide for the past decade. Since 2 years I’ve been living in Amersfoort, and since then I’ve been a participant in the Measure Your City network, with a sensor kit. I also run a LoRaWan gateway to provide additional infrastructure to people wanting to collect sensor data. Today I’d like to talk to you about using open data. What it is, what exists, where to find it, and how to get it. Because I think it can be a useful resource in citizen science.

What is open data? It is data that is published by whoever collected it in such a way, so that anyone is permitted to use it. Without any legal, technical or financial barriers.

This means an open license, such as Creative Commons 0, open standards, and machine readable formats.
Anyone can publish open data, simply by making it available on the internet. And plenty people, academics, and companies do. But mostly open data means we’re looking at government for data.

That’s because we all have a claim on our government, we are all stakeholders. We already paid for the data as well, so it’s all sunk costs, while making it available to all as infrastructure does not increase the costs a lot. And above all: governments have many different tasks, and therefore lots of different data. Usually over many years and at relatively good quality.

The legal framework for open data consists of two parts. The national access to information rules, in NL the WOB, which says everything government has is public, unless it is not.
And the EU initiated regulation on re-using, not just accessing, government material. That says everything that is public can be re-used, unless it can’t. Both these elements are passive, you need to request material.

A new law, the WOO, makes publication mandatory for more things. (For some parts publication is already mandated in laws, like in the WOB, the Cadastre law, and the Company Register)

Next to that there are other elements that play a role. Environmental data must be public (Arhus convention), and INSPIRE makes it mandatory for all EU members to publish certain geographic data. A new EU directive is in the works, making it mandatory for more organisations to publish data, and for some key data sets to be free of charge (like the company register and meteo data)

Next to the legal framework there are active Dutch policies towards more open data: the Data Agenda and the Open Government action plan.

The reason open data is important is because it allows people to do new things, and more importantly it allows new people, who did not have that access before, to do new things. It democratises data sources, that were previously only available to a select few, often those big enough to be able to pay for access. This has now been a growing movement for 10-15 years.

That new agency has visible effects. Economically and socially.In fact you probably already use open data on a daily basis without noticing. When you came here today by bike, you probably checked Buienradar. Which is based on the open data of the KNMI. Whenever in Wikipedia you find additional facts in the right hand column, that informations doesn’t come from Wikipedia but is often directly taken from government databases. The same is true for a lot of the images in Wikipedia, of monuments, historic events etc. They usually come from the open collections of national archives, etc.

When Google presents you with traffic density, like here the queues in front of the traffic lights on my way here, it’s not Google’s data. It’s government data, that is provided in near real-time from all the sensors in the roads. Google just taps into it, and anyone could do the same.You could do the same.

There are many big and small data sets that can be used for a new specific purpose. Like when you go to get gas for the car. You may have noticed at manned stations it takes a few seconds for the gas pump to start? That’s because they check your license plate against the make of the car, in the RDW’s open database. Or for small practical issues. Like when looking for a new house, how much sunshine does the garden get. Or can I wear shorts today (No!).

But more importantly for today’s discussion, It can be a powerful tool for citizen scientists as well. Such as in the public discussion about the Groningen earth quakes. Open seismological data allowed citizens to show their intuition that the strength and frequency of quakes was increasing was real. Using open data by the KNMI.Or you can use it to explore the impact of certain things or policies like analysing the usage statistics of the Utrecht bicycle parking locations.A key role open data can play is to provide context for your own questions. Core registers serve as infrastructure, key datasets on policy domains can be the source for your analysis. Or just a context or reference.

Here is a range of examples. The AHN gives you heights of everything, buildings, landscape etc.
But it also allows you to track growth of trees etc. Or estimate if your roof is suitable for solar panels.This in combination with the BAG and the TOP10NL makes the 3d image I started with possible. To construct it from multiple data sources: it is not a photograph but a constructed image.

The Sentinel satellites provide you with free high resolution data. Useful for icebreakers at sea, precision agriculture, forest management globally, flooding prevention, health of plants, and even to see if grasslands have been damaged by feeding geese or mice. Gas mains maintainer Stedin uses this to plan preventative maintenance on the grid, by looking for soil subsidence. Same is true for dams, dikes and railroads. And that goes for many other subjects. The data is all there. Use it to your advantage. To map your measurements, to provide additional proof or context, to formulate better questions or hypotheses.

It can be used to build tools that create more insigt. Here decision making docs are tied to locations. 38 Amersfoort council issues are tied to De Koppel, the area we are in now. The same is true for many other subjects. The data is all there. Use it to your advantage. To map your measurements, to provide additional proof or context, to formulate better questions or hypotheses.

Maybe the data you need isn’t public yet. But it might be. So request it. It’s your right. Think about what data you need or might be useful to you.
Be public about your data requests. Maybe we can for a Koppelting Data Team. Working with data can be hard and disappointing, doing it together goes some way to mitigate that.

[This post was created using a small hack to export the speaking notes from my slidedeck. Strangely enough, Keynote itself does not have such an option. Copying by hand takes time, by script it is just a single click. It took less than 10 minutes to clean up my notes a little bit, and then post the entire thing.]

TL;DR

The European Commission proposed a new PSI Directive, that describes when and how publicly held data can be re-used by anyone (aka open government data). The proposal contains several highly interesting elements: it extends the scope to public undertakings (utilities and transport mostly) and research data, it limits the ways in which government can charge for data, introduces a high value data list which must be freely and openly available, mandates API’s, and makes de-facto exclusive arrangements transparant. It also calls for delegated powers for the EC to change practical details of the Directive in future, which opens interesting possibilities. In the coming months (years) it remains to be seen what the Member States and the European Parliament will do to weaken or strengthen this proposal.

Changes in the PSI Directive announced

On 25 April, the European Commission announced new measures to stimulate the European data economy, said to be building on the GDPR, as well as detailing the European framework for the free flow of non-personal data. The EC announced new guidelines for the sharing of scientific data, and for how businesses exchange data. It announced an action plan that increases safeguards on personal data related to health care and seeks to stimulate European cooperation on using this data. The EC also proposes to change the PSI Directive which governs the re-use of public sector information, commonly known as Open Government Data. In previous months the PSI Directive was evaluated (see an evaluation report here, in which my colleague Marc and I were involved)

This post takes a closer look at what the EC proposes for the PSI Directive. (I did the same thing when the last version was published in 2013)
This is of course a first proposal from the EC, and it may significantly change as a result of discussions with Member States and the European Parliament, before it becomes finalised and enters into law. Taking a look at the proposed new directive is of interest to see what’s new, what from an open data perspective is missing, and to see where debate with MS is most likely. Square bullets indicate the more interesting changes.

The Open Data yardstick

The original PSI Directive was adopted in 2003 and a revised version implemented in 2015. Where the original PSI Directive stems from well before the emergence of the Open Data movement, and was written with mostly ‘traditional’ and existing re-users of government information in mind, the 2015 revision already adopted some elements bringing it closer to the Open Definition. With this new proposal, again the yardstick is how it increases openness and sets minimum requirements that align with the open definition, and how much of it will be mandatory for Member States. So, scope and access rights, redress, charging and licensing, standards and formats are important. There are also some general context elements that stand out from the proposal.

A floor for the data-based society

In the recital for the proposal what jumps out is a small change in wording concerning the necessity of the PSI Directive. Where it used to say “information and knowledge” it now says “the evolution towards a data-based society influences the life of every citizen”. Towards the end of the proposal it describes the Directive as a means to improve the proper functioning of the European data economy, where it used to read ‘content industry’. The proposed directive lists minimum requirements for governments to provide data in ways that enable citizens and economic activity, but suggests Member States can and should do more, and not just stick with the floor this proposal puts in place.

Novel elements: delegated acts, public undertakings, dynamic data, high value data

There are a few novel elements spread out through the proposal that are of interest, because they seem intended to make the PSI Directive more flexible with an eye to the future.

  • The EC proposal ads the ability to create delegated acts. This would allow practical changes without the need to revise the PSI Directive and have it transposed into national law by each Member States. While this delegated power cannot be used to change the principles in the directive, it can be used to tweak it. Concerning charging, scope, licenses and formats this would provide the EC with more elbow room than the existing ability to merely provide guidance. The article is added to be able to maintain a list of ‘high value data sets’, see below.
  • Public undertakings are defined and mentioned in parallel to public sector bodies in each provision . Public undertakings are all those that are (in)directly owned by government bodies, significantly financed by them or controlled by them through regulation or decision making powers. It used to say only public sector, basically allowing governments to withdraw data from the scope of the Directive by putting them at a distance in a private entity under government control. While the scope is enlarged to include public undertakings in specific sectors only, the rest of the proposal refers to public undertakings in general. This is significant I think, given the delegated powers the EC also seeks.
  • Dynamic and real-time data is brought firmly in scope of the Directive. There have been court cases where data provision was refused on the grounds that the data did not exist when the request was made. That will no longer be possible with this proposal.
  • The EC wants to make a list of ‘high value datasets’ for which more things are mandatory (machine readable, API, free of charge, open standard license). It will create the list through the mentioned delegated powers. In my experience deciding on high value data sets is problematic (What value, how high? To whom?) and reinforces a supply-side perspective more over a demand driven approach. The Commission defines high value as “being associated with important socio-economic benefits” due to their suitability for creating services, and “the number of potential beneficiaries” of those services based on these data sets.

Access rights and scope

  • Public undertakings in specific sectors are declared within scope. These sectors are water, gas/heat, electricity, ports and airports, postal services, water transport and air transport. These public undertakings are only within scope in the sense that requests for re-use can be submitted to them. They are under no obligation to release data.
  • Research data from publicly funded research that are already made available e.g. through institution repositories are within scope. Member States shall adopt national policies to make more research data available.
  • A previous scope extension (museums, archives, libraries and university libraries) is maintained. For educational institutions a clarification is added that it only concerns tertiary education.
  • The proposed directive builds as before on existing access regimes, and only deals with the re-use of accessible data. This maintains existing differences between Member States concerning right to information.
  • Public sector bodies, although they retain any database rights they may have, cannot use those database rights to prevent or limit re-use.

Asking for documents to re-use, and redress mechanisms if denied

  • The way in which citizens can ask for data or the way government bodies can respond, has not changed
  • The redress mechanisms haven’t changed, and public undertakings, educational institutes research organisations and research funding organisations do not need to provide one.

Charging practices

  • The proposal now explicitly mentions free of charge data provision as the first option. Fees are otherwise limited to at most ‘marginal costs’
  • The marginal costs are redefined to include the costs of anonymizing data and protecting commercially confidential material. The full definition now reads “ marginal costs incurred for their reproduction, provision and dissemination and where applicable anonymisation of personal data and measures to protect commercially confidential information.” While this likely helps in making more data available, in contrast to a blanket refusal, it also looks like externalising costs on the re-user of what is essentially badly implemented data governance internally. Data holders already should be able to do this quickly and effectively for internal reporting and democratic control. Marginal costing is an important principle, as in the case of digital material it would normally mean no charges apply, but this addition seems to open up the definition to much wider interpretation.
  • The ‘marginal costs at most’ principle only applies to the public sector. Public undertakings and museum, archives etc. are excepted.
  • As before public sector bodies that are required (by law) to generate revenue to cover the costs of their public task performance are excepted from the marginal costs principle. However a previous exception for other public sector bodies having requirements to charge for the re-use of specific documents is deleted.
  • The total revenue from allowed charges may not exceed the total actual cost of producing and disseminating the data plus a reasonable return on investment. This is unchanged, but the ‘reasonable return on investment’ is now defined as at most 5 percentage points above the ECB fixed interest rate.
  • Re-use of research data and the high value data-sets must be free of charge. In practice various data sets that are currently charged for are also likely high value datasets (cadastral records, business registers for instance). Here the views of Member States are most likely to clash with those of the EC

Licensing

  • The proposal contains no explicit move towards open licenses, and retains the existing rules that standard license should be available, and those should not unnecessarily restrict re-use, nor restrict competition. The only addition is that Member States shall not only encourage public sector bodies but all data holders to use such standard licenses
  • High value data sets must have a license compatible with open standard licenses.

Non-discrimination and Exclusive agreements

  • Non-discrimination rules in how conditions for re-use are applied, including for commercial activities by the public sector itself, are continued
  • Exclusive arrangements are not allowed for public undertakings, as before for the public sector, with the same existing exceptions.
  • Where new exclusive rights are granted the arrangements now need to made public at least two months before coming into force, and the final terms of the arrangement need to be transparant and public as well.
  • Important is that any agreement or practical arrangement with third parties that in practice results in restricted availability for re-use of data other than for those third parties, also must be published two months in advance, and the final terms also made transparant and public. This concerns data sharing agreements and other collaborations where a few third parties have de facto exclusive access to data. With all the developments around smart cities where companies e.g. have access to sensor data others don’t, this is a very welcome step.

Formats and standards

  • Public undertakings will need to adhere to the same rules as the public sector already does: open standards and machine readable formats should be used for both documents and their metadata, where easily possible, but otherwise any pre-existing format and language is acceptable.
  • Both public sector bodies and public undertakings should provide API’s to dynamic data, either in real time, or if that is too costly within a timeframe that does not unduly impair the re-use potential.
  • High value data sets must be machine readable and available through an API

Let’s see how the EC takes this proposal forward, and what the reactions of the Member States and the European Parliament will be.

This is the presentation I gave at the Open Belgium 2018 Conference in Louvain-la-Neuve this week, titled ‘The role and value of data inventories, a key step towards mature data governance’. The slides are embedded further below, and as PDF download at grnl.eu/in. It’s a long read (some 3000 words), so I’ll start with a summary.

Summary, TL;DR

The quality of information households in local governments is often lacking.
Things like security, openness and privacy are safeguarded by putting separate fences for each around the organisation, but those safeguards lack having detailed insight into data structures and effective corresponding processes. As archiving, security, openness and privacy in a digitised environment are basically inseparable, doing ‘everything by design’ is the only option. The only effective way is doing everything at the level of the data itself. Fences are inefficient, ineffective, and the GDPR due to its obligations will show how the privacy fence fails, forcing organisations to act. Only doing data governance for privacy is senseless, doing it also for openness, security and archiving at the same time is logical. Having good detailed inventories of your data holdings is a useful instrument to start asking the hard questions, and have meaningful conversations. It additionally allows local government to deploy open or shared data as policy instrument, and releasing the inventory itself will help articulate civic demand for data. We’ve done a range of these inventories with local government.

1: High time for mature data governance in local and regional government

Hight time! (clock in Louvain-la-Neuve)Digitisation changes how we look at things like openness, privacy, security and archiving, as it creates new affordances now that the content and its medium have become decoupled. It creates new forms of usage, and new needs to manage those. As a result of that e.g. archivists find they now need to be involved at the very start of digital information processes, whereas earlier their work would basically start when the boxes of papers were delivered to them.

The reality is that local and regional governments have barely begun to fully embrace and leverage the affordances that digitisation provides them with. It shows in how most of them deal with information security, openness and privacy: by building three fences.

Security is mostly interpreted as keeping other people out, so a fence is put between the organisation and the outside world. Inside it nothing much is changed. Similarly a second fence is put in place for determining openness. What is open can reach the outside world, and the fence is there to do the filtering. Finally privacy is also dealt with by a fence, either around the entire organisation or a specific system, keeping unwanted eyes out. All fences are a barrier between outside and in, and within the organisation usually no further measures are taken. All three fences exist separately from each other, as stand alone fixes for their singular purpose.

The first fence: security
In the Netherlands for local governments a ‘baseline information security’ standard applies, and it determines what information should be regarded as business critical. Something is business critical if its downtime will stop public service delivery, or of its lack of quality has immediate negative consequences for decision making (e.g. decisions on benefits impacting citizens). Uptime and downtime are mostly about IT infrastructure, dependencies and service level agreements, and those fit the fence tactic quite well. Quality in the context of security is about ensuring data is tamper free, doing audits, input checks, and knowing sources. That requires a data-centric approach, and it doesn’t fit the fence-around-the-organisation tactic.


The second fence: openness
Openness of local government information is mostly at request, or at best as a process separate from regular operational routines. Yet the stated end game is that everything should be actively open by design, meaning everything that can be made public will be published the moment it is publishable. We also see that open data is becoming infrastructure in some domains. The implementation of the digitisation of the law on public spaces, requires all involved stakeholders to have the same (access to) information. Many public sector bodies, both local ones and central ones like the cadastral office, have concluded that doing that through open data is the most viable way. For both the desired end game and using open data as infrastructure the fence tactic is however very inefficient.
At the same time the data sovereignty of local governments is under threat. They increasingly collaborate in networks or outsource part of their processes. In most contracts there is no attention paid to data, other than in generic terms in the general procurement conditions. We’ve come across a variety of examples where this results 1) in governments not being able to provide data to citizens, even though by law they should be able to 2) governments not being able to access their own data, only resulting graphs and reports, or 3) the slowest partner in a network determining the speed of disclosure. In short, the fence tactic is also ineffective. A more data-centric approach is needed.

The third fence: personal data protection
Mostly privacy is being dealt with by identifying privacy sensitive material (but not what, where and when), and locking it down by putting up the third fence. The new EU privacy regulations GDPR, which will be enforced from May this year, is seen as a source of uncertainty by local governments. It is also responded to in the accustomed way: reinforcing the fence, by making a ‘better’ list of what personal data is used within the organisation but still not paying much attention to processes, nor the shape and form of the personal data.
However in the case of the GDPR, if it indeed will be really enforced, this will not be enough.

GDPR an opportunity for ‘everything by design’
The GDPR confers rights to the people described by data, like the right to review, to portability, and to be forgotten. It also demands compliance is done ‘by design’, and ‘state of the art’. This can only be done by design if you are able to turn the rights of the GDPR into queries on your data, and have (automated) processes in place to deal with requests. It cannot be done with a ‘better’ fence. In the case of the GDPR, the first data related law that takes the affordances of digitisation as a given, the fence tactic is set to fail spectacularly. This makes the GDPR a great opportunity to move to a data focus not just for privacy by design, but to do openness, archiving and information security (in terms of quality) by design at the same time, as they are converging aspects of the same thing and can no longer be meaningfully separated. Detailed knowledge about your data structures then is needed.

Local governments inadvertently admit fence-tactic is failing
Governments already clearly yet indirectly admit that the fences don’t really work as tactic.
Local governments have been loudly complaining for years about the feared costs of compliance, concerning both openness and privacy. Drilling down into those complaints reveals that the feared costs concern the time and effort involved in e.g. dealing with requests. Because there’s only a fence, and usually no processes or detailed knowledge of the data they hold, every request becomes an expedition for answers. If local governments had detailed insight in the data structures, data content, and systems in use, the cost of compliance would be zero or at least indistinguishable from the rest of operations. Dealing with a request would be nothing more than running a query against their systems.

Complaints about compliance costs are essentially an admission that governments do not have their house in order when it comes to data.
The interviews I did with various stakeholders as part of the evaluation of the PSI Directive confirm this: the biggest obstacle stakeholders perceive to being more open and to realising impact with open data is the low quality of information systems and processes. It blocks fully leveraging the affordances digitisation brings.

Towards mature data governance, by making inventory
Changing tactics, doing away with the three fences, and focusing on having detailed knowledge of their data is needed. Combining what now are separate and disconnected activities (information security, openness, archiving and personal data protection), into ‘everything by design’. Basically it means turning all you know about your data into metadata that becomes part of your data. So that it will be easy to see which parts of a specific data set contain what type of person related data, which data fields are public, which subset is business critical, the records that have third party rights attached, or which records need to be deleted after a specific amount of time. Don’t man the fences where every check is always extra work, but let the data be able to tell exactly what is or is(n’t) possible, allowed, meant or needed. Getting there starts with making an inventory of what data a local or regional government currently holds, and describing the data in detailed operational, legal and technological terms.

Mature digital data governance: all aspects about the data are part of the data, allowing all processes and decisions access to all relevant material in determining what’s possible.

2: Ways local government data inventories are useful

Inventories are a key first step in doing away with the ineffective fences and towards mature data governance. Inventories are also useful as an instrument for several other purposes.

Local is where you are, but not the data pro’s
There’s a clear reason why local governments don’t have their house in order when it comes to data.
Most of our lives are local. The streets we live on, the shopping center we frequent, the schools we attend, the spaces we park in, the quality of life in our neighbourhood, the parks we walk our dogs in, the public transport we use for our commutes. All those acts are local.
Local governments have a wide variety of tasks, reflecting the variety of our acts. They hold a corresponding variety of data, connected to all those different tasks. Yet local governments are not data professionals. Unlike singular-task, data heavy national government bodies, like the Cadastre, the Meteo institute or the department for motor vehicles, local governments usually don’t have the capacity or capability. As a result local governments mostly don’t know their own data, and don’t have established effective processes that build on that data knowledge. Inventories are a first step. Inventories point to where contracts, procurement and collaboration leads to loss of needed data sovereignty. Inventories also allow determining what, from a technology perspective, is a smooth transition path to the actively open by design end-game local governments envision.

Open data as a policy instrument
Where local governments want to use the data they have as a way to enable others to act differently or in support of policy goals, they need to know in detail which data they hold and what can be done with it. Using open data as policy instrument means creating new connections between stakeholders around a policy issue, by putting the data into play. To be able to see which data could be published to engage certain stakeholders it takes knowing what you have, what it contains, and in which shape you have it first.

Better articulated citizen demands for data
Making public a list of what you have is also important here, as it invites new demand for your data. It allows people to be aware of what data exists, and contemplate if they have a use case for it. If a data set hasn’t been published yet, its existence is discoverable, so they can request it. It also enables local government to extend the data they publish based on actual demand, not assumed demand or blindly. This increases the likelihood data will be used, and increases the socio-economic impact.

Emerging data
More and more new data is emerging, from sensor networks in public and private spaces. This way new stakeholders and citizens are becoming agents in the public space, where they meet up with local governments. New relationships, and new choices result. For instance the sensor in my garden measuring temperature and humidity is part of the citizen-initiated Measure your city network, but also an element in the local governments climate change adaptation policies. For local governments as regulators, as guardian of public space, as data collector, and as source of transparency, this is a rebalancing of their position. It again takes knowing what data you own and how it relates to and complements what others collect and own. Only then is a local government able to weave a network with those stakeholders that connects data into valuable agency for all involved. (We’ve built a guidance tool, in Dutch, for the role of local government with regard to sensors in public spaces)

Having detailed data inventories are a way to start having the right conversations for local governments on all these points.

3: Getting to inventories

To create useful and detailed inventories, as I and my colleagues did for half a dozen local governments, some elements are key in my view. We looked at structured data collections only, so disregarded the thousands of individual once-off spreadsheets. They are not irrelevant, but obscure the wood for the trees. Then we scored all those data sets on up to 80(!) different facets, concerning policy domain, internal usage, current availability, technical details, legal aspects, and concerns etc. A key element in doing that is not making any assumptions:

  • don’t assume your list of applications will tell you what data you have. Not all your listed apps will be used, others won’t be on the list, and none of it tells you in detail what data actually is processed in them, just a generic pointer
  • don’t assume information management knows it all, as shadow information processes will exist outside of their view
  • don’t assume people know when you ask them how they do their work, as their description and rationalisation of their acts will not match up with reality,
    let them also show you
  • don’t assume people know the details of the data they work with, sit down with them and look at it together
  • don’t assume what it says on the tin is correct, as you’ll find things that don’t belong there (we’ve e.g. found domestic abuse data in a data set on litter in public spaces)

Doing an inventory well means

  • diving deeply into which applications are actually used,
  • talking to every unit in the organisation about their actual work and seeing it being done,
  • looking closely at data structures and real data content,
  • looking closely at current metadata and its quality
  • separately looking at large projects and programs as they tend to have their own information systems,
  • going through external communications as it may refer to internally held data not listed elsewhere,
  • looking at (procurement and collaboration) contracts to determine what claims other might have on data,
  • and then cross-referencing it all, and bringing it together in one giant list, scored on up to 80 facets.

Another essential part, especially to ensure the resulting inventory will be used as an instrument, is from the start ensuring the involvement and buy-in of the various parts of local government that usually are islands (IT, IM, legal, policy departments, archivists, domain experts, data experts). So that the inventory is something used to ask a variety of detailed questions of.

bring the islands together
Bring the islands together. (photo Dmitry Teslya CC-BY

We’ve followed various paths to do inventories, sometimes on our own as external team, sometimes in close cooperation with a client team, sometimes a guide for a client team while their operational colleagues do the actual work. All three yield very useful results but there’s a balance to strike between consistency and accuracy, the amount of feasible buy-in, and the way the hand-over is planned, so that the inventory becomes an instrument in future data-discussions.

What comes out as raw numbers is itself often counter-intuitive to local government. Some 98% of data typically held by Dutch Provinces can be public, although usually some 20% is made public (15% open data, usually geo-data). At local level the numbers are a bit different, as local governments hold much more person related data (concerning social benefits for instance, chronic care, and the persons register). About 67% of local data could be public, but only some 5% usually is. This means there’s still a huge gap between what can be open, and what is actually open. That gap is basically invisible if a local government deploys the three fences, and as a consequence they run on assumptions and overestimate the amount that needs the heaviest protection. The gap becomes visible from looking in-depth at data on all pertinent aspects by doing an inventory.

(Interested in doing an inventory of the data your organisations holds? Do get in touch.)