Yesterday we had our monthly all hands meeting at my company. In these meetings we allocate some time to various things to increase our team’s knowledge and skills. This time we looked at information security, and I gave a little intro to start a more long term discussion and effort to raise information security in our company.

When people discuss information security it’s often along the lines of ‘if you want to do it right I’d have to go full paranoid, and that is completely over the top, so I won’t bother with it at all’. This is akin to saying that because it makes no sense to turn your home into an impenetrable fortress against invaders, you’ll just leave the door standing open. In practice you’ll do something in between those two extremes, and have locks on the door.

The Magic Door

Fortress or open door? That’s a false dilemma. (fortress by Phillip Capper, CC-BY, open door by Hartwig HKD, CC-BY-SA and locked door by Robert Montalvo CC-BY)

You know the locks on your door won’t keep out very determined burglars or say a swat team, but it will raise the time and effort needed for less determined invaders to a point they will be discouraged.
At the same time keeping the door closed and locked isn’t just useful to keep out burglars but also serves as a way to keep out the wind, rain and leaves and dust blowing in from the street.
Similarly in information security you won’t keep out determined government three letter agencies, but there too there are basic hygiene measures and a variety of measures to raise the cost of more casual or less determined attacks. Like with preventative measures at home, information security can be viewed in layers on a spectrum.

I tried to tease out those layers, from the most basic to the most intensive:

  1. hygiene
  2. keeping your files available
  3. basic steps against loss or theft, also on the road
  4. protect client information, and compliance
  5. secure communication and exchanges
  6. preventing danger to others
  7. traveling across borders outside of the Schengen area
  8. active defence against being targeted
  9. active defence against being targeted by state actors

For each of those levels there are multiple dimensions to consider. First of all in recent years a new group of actors interested in your data has clearly emerged. The tech companies for whom adtech is their business model started tracking you as much as they can get away with. This adds the need for measures to all but the most intensive levels, but especially means the basic levels intensify.
Then there’s the difference between individual measures, and what can be arranged at the level of our organisation, and how those two interplay.

Practically each level can be divided first along the lines of our two primary devices, laptop and phone. Second, there’s a distinction between technological measures, and behaviour (operational security).

the list of levels, and the distinction in dimensions as I showed them yesterday

I provided examples of how that plays out on the more basic levels, and on the most intensive level. E.g. on the level of hygiene, technological measures you can think of are firewalls, spam and virus filters, a privacy screen, ad blockers and tracker blockers, using safer browsers. Behavioural measures are not clicking links before checking what they lead to, recognising phishing attempts, not plugging in usb sticks from others, using unique user names and passwords, using different browsers for different tasks, and switching off wifi, bluetooth and gps (on mobile) when you’re not specifically using them.

Over the years working on open data I’ve increasingly become aware of and concerned about information security, and since early 2014 actively engaging with it. I’m more or less at level 7 of the list above, and with the company I think we need to be at level 5 at least, whereas some of us haven’t quite reached level 1 at the moment. From the examples I gave, and showing some of the (simple) things I do, we had a conversation about the most pressing questions and issues each of us has. This we’ll use to sequence steps. We’ll create short faq’s and/or how-to sheets, we’ll suggest tools and behavioral measures, suggest what needs a collective choice, and provide help with adoption / implementation. I feel with this we have a ‘gentle’ approach, that avoids overwhelm that leads to not taking measures at all.

The first things people mentioned because they were worried about it are: usernames/passwords, e-mail, trackers, vpn, and handling copies of ID’s.
So we’ll take those as starting points.

If you want to read up on information security and operational security around your devices, dearly missed Arjen Kamphuis’s book on information security for journalists is a very useful resource. My approach as described is more geared to the actual context of the people involved, and what I know about their habits and routines, and to the context of our work and typical projects.

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.

Data Inventories for Local Data Governance by Ton Zijlstra

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.)

This is a quick assessment to get a grip on how I can secure my documents, and against which risks.

Basically the core device is my laptop. I haven’t incorporated my phone yet in this overview.

Laptop
Risk: gets stolen
Mitigation: encrypt HDD, and back-up to Time Machine and/or NAS drive and/or VPS, cash reserve for immediate replacement
Current status: mitigation measures in place

Risk: breaks down / HDD failure
Mitigation: back-up to Time Machine and/or NAS drive and/or VPS
Current status: mitigation measures in place

Risk: gets read / copied while en route
Mitigation: encrypt HDD, being able to travel without documents and without being able to reveal passwords needed to trigger access to remotely restore documents to laptop
Current status: mitigation measures partly in place

Time Machine
Risk: not in sync, HDD failure
Mitigation: fix sync, restore from off-site back-up or laptop
Current status: mitigation measures in place

Risk: gets stolen
Mitigation: encrypt files, and maintain offsite back-up
Current status: mitigation measures in place

NAS drive (with archived files, music library)
Risk: not in sync, HDD failure
Mitigation: syncing process, RAID, restore from off-site back-up
Current status: mitigation measures in place

Risk: gets stolen
Mitigation: encrypt files, and maintain offsite back-up
Current status: mitigation measures partly in place (encryption not supported by current NAS, planned to replace NAS) UPDATE: NAS replaced, encryption added.

VPS
Risk: crashes
Mitigation: restore from back-up service, or restore from on-site back-ups and laptop
Current status: mitigation measures in place

Risk: gets hacked
Mitigation: encrypt files, keep on-site back-ups of files, restore from back-up service
Current status: mitigation measures in place

Risk: deleting files through syncing errors (actually happened already)
Mitigation: syncing through a local copy on laptop (scripted), one-way syncing
Current status: mitigation measures partly in place