Category: Distributed digital transformation

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Bookmarked Internet of Things and Objects of Sociality (by Ton Zijlstra, 2008)

Fifteen years ago today I blogged this brainstorming exercise about how internet-connectivity for objects might make for different and new objects of sociality. A way to interact with our environment differently. Not a whole lot of that has happened, let alone become common. What has happened is IoT being locked up in device and mobile app pairings. Our Hue lights are tied to the Hue app, and if I’d let it collect e.g. behavioural data it would go to Philips first, not to me. A Ring doorbell (now disabled), our Sonos speakers are the same Those rigid pairings are a far cry from me seamlessly interacting with my environment. One exception is our Meet Je Stad sensor in the garden, as it runs on LoRaWan and the local citizen science community has the same access as I do to the data (and I run a LoRa gateway myself, adding another control point for me).

Incoming EU legislation may help to get more agency on this front. First and foremost, the Data Act when it is finished will make it mandatory that I can access the data I generate with my use of devices like those Hue lights and Sonos speakers and any others you and I may have in use (the data from the invertor on your solar panels for instance). And allow third parties to use that data in real time. A second relevant law I think is the Cyber Resilience Act, which regulates the cybersecurity of any ‘product with digital elements’ on the EU market, and makes it mandatory to provide additional (technical) documentation around that topic.

The internet of things, increases the role of physical objects as social objects enormously, because it adds heaps of context that can serve relationships. Physical objects always have been social objects, but only in their immediate physical context. … Making physical objects internet-aware creates a slew of possible new uses for it as social objects. And if you [yourself] add more sensors or actuators to a product (object hacks so to speak), the list grows accordingly.

Ton Zijlstra, 2008

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ODRL, Open Digital Rights Language popped up twice this week for me and I don’t think I’ve been aware of it before. Some notes for me to start exploring.

Rights Expression Languages

Rights Expression Languages, RELs, provide a machine readable way to convey or transfer usage conditions, rights, restraints, granularly w.r.t. both actions and actors. This can then be added as metadata to something. ODRL is a rights expression language, and seems to be a de facto standard.

ODRL is a W3C recommendation since 2018, and thus part of the open web standards. ODRL has its roots in the ’00s and Digital Rights Management (DRM): the abhorred protections media companies added to music and movies, and now e-books, in ways that restrains what people can do with media they bought to well below the level of what was possible before and commonly thought part of having bought something.

ODRL can be expressed in JSON or RDF and XML. A basic example from Wikipedia looks like this:


{
"@context": "http://www.w3.org/ns/odrl.jsonld",
"uid": "http://example.com/policy:001",
"permission": [{
"target": "http://example.com/mysong.mp3",
"assignee": "John Doe",
"action": "play"
}]
}

In this JSON example a policy describes that example.com grants John permission to play mysong.

ODRL in the EU Data Space

In the shaping of the EU common market for data, aka the European common data space, it is important to be able to trace provenance and usage conditions for not just data sets, but singular pieces of data, as it flows through use cases, through applications and their output back into the data space.
This week I participated in a webinar by the EU Data Space Support Center (DSSC) about their first blueprint of data space building blocks, and for federation of such data spaces.

They propose ODRL as the standard to describe usage conditions throughout data spaces.

The question of enactment

It wasn’t the first time I talked about ODRL this week. I had a conversation with Pieter Colpaert. I reached out to get some input on his current view of the landscape of civic organisations active around the EU data spaces. We also touched upon his current work at the University of Gent. His research interest is on ODRL currently, specifically on enactment. ODRL is a REL, a rights expression language. Describing rights is one thing, enacting them in practice, in technology, processes etc. is a different thing. Next to that, how do you demonstrate that you adhere to the conditions expressed and that you qualify for using the things described?

For the EU data space(s) this part sounds key to me, as none of the data involved is merely part of a single clear interaction like in the song example above. It’s part of a variety of flows in which actors likely don’t directly interact, where many different data elements come together. This includes flows through applications that tap into a data space for inputs and outputs but are otherwise outside of it. Such applications are also digital twins, federated systems of digital twins even, meaning a confluence of many different data and conditions across multiple domains (and thus data spaces). All this removes a piece of data lightyears from the neat situation where two actors share it between them in a clearly described transaction within a single-faceted use case.

Expressing the commons

It’s one thing to express restrictions or usage conditions. The DSSC in their webinar talked a lot about business models around use cases, and ODRL as a means for a data source to stay in control throughout a piece of data’s life cycle. Luckily they stopped using the phrase ‘data ownership’ as they realised it’s not meaningful (and confusing on top of it), and focused on control and maintaining having a say by an actor.
An open question for me is how you would express openness and the commons in ODRL. A shallow search surfaces some examples of trying to express Creative Commons or other licenses this way, but none recent.

Openness, can mean an absence of certain conditions, although there may be some (like adding the same absence of conditions to re-shared material or derivative works), which is not the same as setting explicit permissions. If I e.g. dedicate something to the public domain, an image for instance, then there are no permissions for me to grant, as I’ve removed myself from that role of being able to give permission. Yet, you still want to express it to ensure that it is clear for all that that is what happened, and especially that it remains that way.

Part of that question is about the overlap and distinction between rights expressed in ODRL and authorship rights. You can obviously have many conditions outside of copyright, and can have copyright elements that may be outside of what can be expressed in RELs. I wonder how for instance moral authorship rights (that an author in some (all) European jurisdictions cannot do away with) can be expressed after an author has transferred/sold the copyrights to something? Or maybe, expressing authorship rights / copyrights is not what RELs are primarily for, as it those are generic and RELs may be meant for expressing conditions around a specific asset in a specific transaction. There have been various attempts to map all kinds of licenses to RELs though, so I need to explore more.

This is relevant for the EU common data spaces as my government clients will be actors in them and bringing in both open data and closed and unsharable but re-usable data, and several different shades in between. A range of new obligations and possibilities w.r.t. data use for government are created in the EU data strategy laws and the data space is where those become actualised. Meaning it should be possible to express the corresponding usage conditions in ODRL.

ODRL gaps?

Are there gaps in the ODRL standard w.r.t. what it can cover? Or things that are hard to express in it?
I came across one paper ‘A critical reflection on ODRL’ (PDF Kebede, Sileno, Van Engers 2020), that I have yet to read, that describes some of those potential weaknesses, based on use cases in healthcare and logistics. Looking forward to digging out their specific critique.

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I’ve been involved in open data for about 15 years. Back then we had a vibrant European wide network of activists and civic organisations around open data, partially triggered by the first PSI Directive that was the European legal fundament for our call for more open government data.

Since 2020 a much wider and fundamental legal framework than the PSI Directive ever was is taking shape, with the Data Governance Act, Data Act, AI Regulation, Open Data Directive, High Value Data implementing regulation as building blocks. Together they create the EU single market for data, adding data as fourth element to the list of freedom of movement for people, products and capital within the EU. This will all take shape as the European common dataspace(s), built from a range of sectoral dataspaces.

In the past years I’ve been actively involved in these developments, currently helping large government data holders in the Netherlands interpret the new obligations and above all new opportunities for public service that result from all this.

Now that the dataspaces are slowly taking shape, what I find missing from most discussions and events is the voice of civic organisations and activists. It’s mostly IT companies and research institutions that are involved. While for the Commission social impact (climate, health, energy and agricultural transitions e.g.) is a key element in why they seek to implement these new laws, for most parties involved in the dataspaces that is less of a consideration, and economic and technological factors are more important. Not even government data holders themselves are represented much in how the European data space will turn out. Even though everyone single one of us and every public entity by default is a part of this common market.

I would like to strengthen the voice of civil society and activists in this area, to together influence the shape these dataspaces are taking. So that they are of use and value to us too. To use the new (legal) tools to strengthen the commons, to increase our agency.

Most of the old European open data network however over time has dissolved, as we all got involved in national level practical projects and the European network as a source of sense of belonging and strengthening each others commitment became less important. And we’ve moved on a good number of years, so many new people have come on to the scene, unconnected to that history, with new perspectives and new capabilities.

So the question is: who is active on these topics, from a civil society perspective, as activists? Who should be involved? What are the organisations, the events, that are relevant regionally, nationally, EU wide? Can we connect those existing dots: to share experiencs, examples, join our voices, pool our efforts?

Currently I’m doing a first scan of who is involved in which EU country, what type of events are visible, organisations that are active etc. Starting from my old network of a decade ago. I will share lists of what I find at Our Common Data Space.

Let me know if you count yourself as part of this European network. Let me know the relevant efforts you are aware of. Let me know which events you think bring together people likely to want to be involved.

I look forward to finding out about you!


Open Government Data Camp in Warsaw 2011. An example of the vibrancy of the European open data network, I called it the community’s ‘family christmas party’, at the time. Above the schedule of sessions created collectively by the participants, with many local initiatives and examples shared with the EU wide network. Below one of those sessions, on local policy making and open data.

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It had been expected, Tweetdeck is now no longer available to me to follow Twitter topics and lists. Tweetdeck is only available to paying Twitter accounts. Earlier today it still worked for me as a non-paying account, now no longer. It went web-only a year ago before Twitter’s transition of ownership. Last month it became clear Tweetdeck would be limited to paying accounts. With Tweetdeck gone the last remaining shred of utility of Twitter for me dissolved.

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Bookmarked Disinformation and its effects on social capital networks (Google Doc) by Dave Troy

This document by US journalist Dave Troy positions resistance against disinformation not as a matter of factchecking and technology but as one of reshaping social capital and cultural network topologies. I plan to read this, especially the premises part looks interesting. Some upfront associations are with Valdis Krebs’ work on the US democratic / conservative party divide where he visualised it based on cultural artefacts, i.e. books people bought (2003-2008), to show spheres and overlaps, and with the Finnish work on increasing civic skills which to me seems a mix of critical crap detection skills woven into a social/societal framework. Networks around a belief or a piece of disinformation for me also point back to what I mentioned earlier about generated (and thus fake) texts, how attempts to detect such fakes usually center on the artefact not on the richer tapestry of information connections (last 2 bullet points and final paragraph) around it (I called it provenance and entanglement as indicators of authenticity recently, entanglement being the multiple ways it is part of a wider network fabric). And there’s the more general notion of Connectivism where learning and knowledge are situated in networks too.

The related problems of disinformation, misinformation, and radicalization have been popularly misunderstood as technology or fact-checking problems, but this ignores the mechanism of action, which is the reconfiguration of social capital. By recasting these problems as one problem rooted in the reconfiguration of social capital and network topology, we can consider solutions that might maximize public health and favor democracy over fascism …

Dave Troy

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Bookmarked WordPress AI: Generative Content & Blocks (by Joe Hoyle, found via Chuck Grimmett)

As many others I am fascinated by what generative algorithms like ChatGPT for texts and Stable Diffusion for images can do. Particularly I find it fascinating to explore what it might do if embedded in my own workflows, or how it might change my workflows. So the link above showing an integration of ChatGPT in WordPress’ Gutenberg block editor drew my attention.

The accompanying video shows a mix of two features. First having ChatGPT generate some text, or actually a table with specific data, and having ChatGPT in ‘co-pilot’ style generate code for Gutenberg blocks. I think the latter might be actually useful, as I’ve seen generative AI put to good use in that area. The former, having ChatGPT write part of your posting is clearly not advisable. And the video shows it too, although the authors don’t point it out or haven’t reflected on the fact that ChatGPT is not a search engine but geared to coming up with plausible stuff without being aware of its actual information (the contrast with generating code is that code is much more highly structured in itself so probabilities collapse easier to the same outcome).

The blogpost in the video is made by generating a list of lunar missions, and then turning them into a table, adding their budgets and sorting them chronologically. This looks very cool in the vid, but some things jump out as not ok. Results jump around the table for instance: Apollo 13 moves from 1970 to 2013 and changes budget. See image below. None of the listed budgets for Apollo missions, nor their total, match up with the detailed costs overview of Apollo missions (GoogleDocs spreadsheet). The budget column being imaginary and the table rows jumping around makes the result entirely unfit for usage of course. It also isn’t a useful prompt: needing to fact check every table field is likely more effort and less motivating than researching the table yourself from actual online resources directly.

It looks incredibly cool ‘see me writing a blogpost by merely typing in my wishes, and the work being done instantly’, and there are definitely times I’d wish that to be possible. To translate a mere idea or thought into some output directly however means I’d skip confronting such an idea with reality, with counter arguments etc. Most of my ideas only look cool inside my head, and need serious change to be sensibly made manifest in the world outside my head. This video is a bit like that, an idea that looks cool in one’s head but is great rubbish in practice. ChatGPT is hallucinating factoids and can’t be trusted to create your output. Using it in the context of discovery (as opposed to the justification context of your output such as in this video) is possible and potentially useful. However this integration within the Gutenberg writing back-end of WordPress puts you in the output context directly so it leads you to believe the generated plausible rubbish is output and not just prompting fodder for your writing. ‘Human made’ is misleading you with this video, and I wouldn’t be surprised if they’re misleading themselves as well. A bit like staging the ‘saw someone in half and put them together again’ magician’s trick in an operating room and inviting surgeons to re-imagine their work.

Taking a native-first approach to integrating generative AI into WordPress, we’ve been experimenting with approaches to a “WordPress Copilot” that can “speak” Gutenberg / block-editor.

Copy-pasting paragraphs between ChatGPT and WordPress only goes so far, while having the tools directly embedded in the editor … open up a world of possibilities and productivity wins…

Joe Hoyle


An android robot is filling out a table listing Apollo missions on a whiteboard, generated image using Midjourney