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Dreams of a Unified Text

- January 24, 2012 in Ideas, Musings, Open Knowledge, Public Domain

The following is a blog post by Rufus Pollock co-Founder of the Open Knowledge Foundation. I have a dream, one which I’ve had for a while. In this dream I’m able to explore, seamlessly, online, every text ever written. With the click of a button I can go from Pynchon to Proust, from Musil to Machiavelli, from Homer to Hugo. And in this dream not only can I read, but I myself am able to contribute, to write upon these texts — to annotate, to anthologize, to interlink, to translate, to borrow — and to share what I do with others. I can see what others have shared, what notes they have added, what selections they have made. I can see the interweaving of these texts created by borrowing, by inspiration, by reference, all made concrete by the insight and efforts of myself and others and their ability to layer their insights freely upon those original texts — just as those writers built upon the works that had gone before them. And while each text still can stand still stand alone — in all its greatness or mediocrity — we have something new, a single unified corpus woven together out of this multitude of separate text — e pluribus unum. A whole that is a concrete instantiation in an immaterial realm of the cultural achievement of mankind as expressed in the written word.

Dream Meets Reality

Why is this dream not yet a reality? After all don’t we have the tools and technology. One answer is legal, one answer is technological, and one answer is social. The legal issue is copyright, at least in its current exclusive rights form 1. Copyright means this vision is only really possible for works in the public domain, works therefore that are, in most countries, a hundred years or more old. This isn’t necessarily that big a problem, at least for texts: the public domain though old is already incredibly rich and so we therefore already have more than enough material to be getting on with. On the technology front we have the cost of digitization, processing and storage. Digitization costs are significant. This has meant either that digitization activities have either been limited or the material created has not been released openly (for example, the material produced by Google’s efforts with its Books project, which is probably largest effort to date, is not open). That said, efforts like Project Gutenberg and the Internet Archive have already made available tens of thousands of texts, and there are now several digitization projects underway that will result in even larger amounts of material freely and openly available. Then third we have the social issue, or rather it a question of how technology can support the social activities required for this dream of a unified text to become real. Specifically, to realize our dream we need to bring material — texts and the writing upon them — together in a single coherent experience. Yet the centralization (and ownership) that implies may be a significant obstacle to mass participation.2 Similarly, we need it to be possible for anyone with ‘net access to be able to contribute to the weaving of the unified inter-text but, at the same time, to be able to select which contributions we want to see (if we are not to be overwhelmed by an avalanche of material, much of it possibly of dubious quality).


We have then within our grasp, the realization of th dream of a unified text. Combining of text of technology we can create something truly extraordinary. Interested in making this happen, come join us at the Textus Project.

  1. Let me be clear, I’m not saying that copyright is per se is bad or that everything should be ‘free’. Time, energy and capital are required to create books, music and films and that expenditure often needs to be recompensed. However, the current system of copyright is by no means the best way to achieve this. This is not something I wish to explore in detail here. More can be found on my personal website and in papers such as Forever Minus a Day: Theory and Empirics of Optimal Copyright 
  2. This tension between distributed collaboration and centralizing tendencies of coordination and scale is a common theme in many ‘net projects. 

Season’s Greetings from the Open Knowledge Foundation

- December 24, 2011 in Musings

‘Tis the season to be jolly. This year when preparing your Christmas feast why not take some inspiration from Mrs Beeton and her legendary 1861 Book of Household Management   Words of wisdom from Mrs Beeton…
“In December, the principal household duty lies in preparing for the creature comforts of those near and dear to us, so as to meet Old Christ-mas with a happy face, a contented mind, and a full larder. And in stoning plums, washing currants, cutting peel, beating eggs, and mixing a pudding, a housewife is not unworthily greeting the season of good will. “
“The cost of poultry varies considerably, being affected both by theseason of the year and the district in which it is purchased. It is well to remember that poultry almost invariably rises in price at Christmas, and also tends to be expensive when no game is on the market. These considerations borne in mind, the table below will give a reliable average of prices.” “Fattening Turkeys for the Table. Turkeys grow very slowly ; there-fore, the earlier they are hatched the better when it is necessary that they should attain their full growth by Christmas.”
Boar’s Head
“In ancient times the boar’s head formed the most important dish, and on Christmas Day was invariably the first placed upon the table, its entrance into the hall being preceded by a body of servitors, a flourish of trumpets, and other marks of distinction. The dish itself was borne by the individual next in rank to the lord of the feast. The custom of serving a boar’s head on a silver platter on Christmas Day is still observed at some colleges and Inns of Court. So highly was the grizzly boar’s head regarded in the Middle Ages that it passed into the cognizance of some of the noblest families in the realm ; thus it was not only the crest of the Nevilles and Warwicks with their collateral houses, but it was the cognizance of Richard III …”
Christmas Pudding And if none of that takes your fancy – shake it up a little… All images and text are from Mrs Beeton’s Household Management which is in the public domain and the full text of which is available online at the Internet Archive. Finally, a big thank you to everyone who has been involved in and supported the Open Knowledge Foundation this year. It’s been a great year in the open data space, so Merry Christmas and a happy New Year. See you back here in 2012…  

Carla’s Open Data Collage

- November 11, 2011 in Musings, Open Government Data

Check out this great collage from 9 year old Carla, sent over to us by her Dad, Martin Kaltenböck! This makes Carla our youngest Open Data Ambassador yet ;-) Martin says:
I had a chat with my daughter Carla (9 years old) after the Warsaw Camp 2011 about the idea of Open Government Data, as well as about what happened in Warsaw at and around the event – and as she was already collecting open data and OKFN stickers from the last 1.5 years of my open data journey, she created her collage on Open Data inspired by our discussion!

She also knows now – and thinks that this is important – that looking for schools or kindergartens in a city like Vienna on a mobile phone needs the basic data behind; that this data is collected mainly by the public administration of the city; and that we can realise this mobile app only if we can use and re-use this data… Despite her knowledge about OGD, the main reason for the collage was creativity and her artistic disposition ;-) enjoy…

Carla & Martin

Prizewinning bid in ‘Inventare il Futuro’ Competition

- November 5, 2011 in Annotator, Bibliographic, Essays, Featured Project, Free Culture, Musings, News, OKF Projects, Open Shakespeare, Public Domain, Public Domain Works, texts, WG Humanities, WG Open Bibliographic Data

By James Harriman-Smith and Primavera De Filippi On the 11th July, the Open Literature (now Open Humanities) mailing list got an email about a competition being run by the University of Bologna called ‘Inventare il Futuro’ or ‘Inventing the Future’. On the 28th October, Hvaing submitted an application on behalf of the OKF, we got an email saying that our idea had won us €3 500 of funding. Here’s how.

The Idea: Open Reading

The competition was looking for “innovative ideas involving new technologies which could contribute to improving the quality of civil and social life, helping to overcome problems linked to people’s lives.” Our proposal, entered into the ‘Cultural and Artistic Heritage’ category, proposed joining the OKF’s Public Domain Calculators and Annotator together, creating a site that allowed users more interaction with public domain texts, and those texts a greater status online. To quote from our finished application:
Combined, the annotator and the public domain calculators will power a website on which users will be able to find any public domain literary text in their jurisdiction, and either download it in a variety of formats or read it in the environment of the website. If they chose the latter option, readers will have the opportunity of searching, annotating and anthologising each text, creating their own personal response to their cultural literary heritage, which they can then share with others, both through the website and as an exportable text document.

As you can see, with thirty thousand Euros for the overall winner, we decided to think very big. The full text, including a roadmap is available online. Many thanks to Jason Kitkat and Thomas Kandler who gave up their time to proofread and suggest improvements.

The Winnings: Funding Improvements to OKF Services

The first step towards Open Reading was always to improve the two services it proposed marrying: the Annotator and the Public Domain Calculators. With this in mind we intend to use our winnings to help achieve the following goals, although more ideas are always welcome:
  • Offer bounties for flow charts regarding the public domain in as yet unexamined jurisdictions.
  • Contribute, perhaps, to the bounties already available for implementing flowcharts into code.
  • Offer mini-rewards for the identification and assessment of new metadata databases.
  • Modify the annotator store back-end to allow collections.
  • Make the importation and exportation of annotations easier.
Please don’t hesitate to get in touch if any of this is of interest. An Open Humanities Skype meeting will be held on 20th November 2011 at 3pm GMT.

Scaling the Open Data Ecosystem

- October 31, 2011 in Essays, Musings, News, Open Data, Open Knowledge

This is a post by Rufus Pollock, co-Founder of the Open Knowledge Foundation. As reported elsewhere I’ve been fortunate enough to have my Shuttleworth Fellowship renewed for the coming year so that I can continue and extend my work at the Open Knowledge Foundation on developing the open data ecosystem. The following text and video formed the main part of my renewal application.

Scaling the Open Data Ecosystem

Describe the world as it is.

The last several decades the world has seen an explosion of digital technologies which have the potential to transform the way knowledge is disseminated. This world is rapidly evolving and one of its more striking possibilities is the creation of an open data ecosystem in which information is freely used, extended and built on. The resulting open data ‘commons’ is valuable in and of itself, but also, and perhaps even more importantly, because the social and commercial benefits it generates — whether in helping us to understand climate change; speeding the development of life-saving drugs; or improving govenance and public services. In developing this open data ecosystem there are three key things are needed: material, tools and people. This is a key point: open information without tools and communities to utilise it is not enough, after all, openness isn’t an end itself – open material has no value if it isn’t used.We need therefore to have widely available the capabilities for utilising open material, for processing, analysing and sharing it, especially on a large scale. Relevant tools need to be freely and openly available and the related infrastructure — after all tools need somewhere to run, and data needs somewhere to be stored — should be capable of effective deployment by distributed communities. Over the last few years we’ve started to see increasing amounts of open material made available, with release of open data really starting to take off in the last couple of years. But the (open) tools and the communities to use them are still very limited — we’re just starting to see the first self-identified “data wranglers / data hackers / data scientists” (note how the terms have not settled yet!). Key architectural elements of the ecosystem, such as how we create and share data in an open componentized way, are only just beginning to be worked through. We are therefore at a key moment where we transition from just ‘getting the data’ (and building the app) to a real data ecosystem in which data is transformed, shared and reintegrated and we replace a ‘data pipeline’ with ‘data cycles’.

What change do you want to make?

I want to see a world in which open data – data that can be freely shared and used without restriction – is ubiquitous and in which that data is used to improve the world around us, whether by finding you a better route to work, helping us to prevent climate change, or improving reportage. I want open data to allow us to build the tools and systems to help us navigate and managing the increasingly complex information-based world in which we now live. Specifically, I want to help grow the emerging open data ecosystem. While part of this involves supporting and expanding the ongoing release of material — building on the major progress of the last few years — the biggest change I want to make is develop the tools and communities so that we can make effective use of the increasing amounts of open data is now becoming available. Particular changes I want to make are:
  • Development of real ‘data cycles’ (especially for government data). By data cycles I mean a process whereby material is released, it’s used and improved by the community and then that work finds its way back to the data source.
  • Greater connection of open data to journalists and other types of reporters/analysts who can use this data and bring it to a wider audience.
  • Development of an active and globally-connected community of open data wranglers.
  • Development of better open tools and infrastructure for working with data, especially in a distributed community using a componentization approach that allow us to scale rapidly and efficiently.

What do you want to explore?

I’m interested in learning more about the actual and potential user communities for open data. I want to explore what they want — in relation to both tools and data — and, also their awareness of what is already out there. I’m especially interested in areas like journalism, government, and the general civic hacker community. I want to explore the processes around ‘data refining’ — obtaining, cleaning and transforming source data into something more useful and data ‘analysis’ (usually closely related tasks). I’m especially interested in existing business activity in this area — often labelled with headings like business intelligence and data warehousing. I want to see what we could learn from business regarding tools and process that could be used in the wider open data community as well as how the business community can take advantage of open data. I want to explore how we can connect together the distributed community of data wranglers and hacktivists, focusing on a specific area like civic information or finances. How do we allow for loose networks across different location and different organisations while sharing information and collaborating on the development of tools. Lastly, I want to explore the tools and processes needed to support decentralised, collaborative, and componentised development of data. How can we build robust and scalable infrastructures? How can we build the technology to allow people to combine multiple sources of official data in a wiki-like manner – so that changes can be tracked, and provenance can be traced? How can we break down data into smaller manageable components, and then successfully recombine them again? How can we ‘package’ data and create knowledge APIs to enable automated distribution and reuse of datasets? How can we achieve real read/write status for official information – not just access alone?

What are you going to do to get there?

I want to focus my efforts in this next year on 3 key areas, breaking new ground but also building on existing work I’ve been doing with the Open Knowledge Foundation. First, I want to build out CKAN software and community from a registry to a data hub – a platform for working with data not just listing it. The last year has seen very significant uptake of the CKAN with dozens of CKAN instances around the world including several official government and institutional deployments. Improving and expanding CKAN we will allow us to capitalize on this success to make CKAN into an essential tool and platform for open data “development”. The most important aspect of the software side of this will be the development of a datastore component supporting the processing and visualization of data within CKAN. With features like these CKAN can become a valuable tool not just for tech-savvy data ‘geeks’ but for the more general users of data such as journalists and civil servants. Engaging this wider, “non-techy” audience is a key part of scaling up the ecosystem. It is important to emphasize that this won’t just be about developing software but is about understanding and engaging with the a variety of data-user communities, exploring how they work, what they want and how they can be helped. Second I want to build out the OpenSpending platform and community. OpenSpending is Where Does My Money Go Goes globalized — a worldwide project to ‘map the money’. Following the successful launch of Where Does My Money Go last autumn in the UK, in the last 6 months we have dramatically expanded of coverage with data now from more than 15 countries (in May our work on Italy received coverage in La Stampa, the Guardian and other major newspapers). Working with OpenSpending complements work on CKAN because it is a chance to act as a data user and refiner — we already have some basic integration with CKAN but it’s still very basic. Furthermore, OpenSpending presents the chance to develop a specific data wrangler / data user community and one which can and should have close links with users and analysts of data including journalist and civic ‘hacker’ groups. In this way OpenSpending can act as a microcosm and prototype for developments in the wider open data community. Third, I want to develop the OKF Open Data Labs. Much like the “Google Labs” for Google’s web services, Mozilla Labs for the Web, and the “Sunlight Labs” for US transparency websites, I would like the “Open Data Labs” to be a place for coders and data wranglers to collaborate, experiment, share ideas and prototypes, and ultimately build a new generation of open source tools and services for working with open data. The labs would form a natural complement to the my other activities with CKAN and OpenSpending – the Labs could build on material and tools from those projects while simultaneously acting as an incubator for new extensions and ideas useful both there and elsewhere.

Building the (Open) Data Ecosystem

- March 31, 2011 in Essays, Ideas, Musings, Open Data, Open Knowledge

The following is a post by Rufus Pollock, co-Founder of the Open Knowledge Foundation.

The Present: A One-Way Street

At the current time, the basic model for data processing is a “one way street”. Sources of data, such as government, publish data out into the world, where, (if we are lucky) it is processed by intermediaries such as app creators or analysts, before finally being consumed by end users1. It is a one way street because there is no feedback loop, no sharing of data back to publishers and no sharing between intermediaries. So what should be different? Data Ecosystem - Current

The Future: An Ecosystem

What we should have is an ecosystem. In an ecosystem there are data cycles: infomediaries — intermediate consumers of data such as builders of apps and data wranglers — should also be publishers who share back their cleaned / integrated / packaged data into the ecosystem in a reusable way — these cleaned and integrated datasets being, of course, often more valuable than the original source. Data Ecosystem - Future In addition, corrected data, or relevant “patches” should find their way back to data producers so data quality improves at the source. Finally, end users of data need not be passive consumers but should be also be able to contribute back — flagging errors, or submitting corrections themselves. With the introduction of data cycles we have a real ecosystem not a one way street and this ecosystem thrives on collaboration, componentization and open data. What is required to develop this ecosystem model rather than a one way street? Key changes include (suggestions welcome!):
  • Infomediaries to publish what they produce (and tools to make this really easy)
  • Data packaging and patching format (better ways to publish and share data)
  • Publisher notification of patches (pull requests) with automated integration (merge) tools
We’re starting to see the first versions of tools that will help here2: for example Google Refine with its javascript “patch” format, Scraperwiki and our own CKAN Data Management System. And for some items, such as increased sharing and publication, evangelism and a change in attitude (to a world in which the default is to publish) may be more important than tools — though even here make better tools can make easier to publish as well as provide incentives to do so (because publishing gives you access to those tools). But it is just a beginning and there’s still a good way to go before we’ve really made the transition from the one-way street to a proper (open) data ecosystem.

Annexe: Some Illustrations of Our Current One Way Street

Currently it’s common to hear people describe web-apps or visualizations that have been built using some particular dataset. However, it’s unusual to hear them then say “and I published the cleaned data, and the data cleaning code back to the community in a way that was reusable” and even rarer to hear them say “and the upstream provider has corrected the errors we found in the data based on our reports”. (It’s also rare to hear people talk about the datasets they’ve created as opposed to the apps or visualizations they’ve built). We know about this first hand. When the UK government first published its 25k spending data last Autumn we worked hard as part of our Where Does My Money Go? project to process and load the data so it was searchable and visualizable. Along the way we found data ‘bugs’ of the kind that are typical in this area — dates presented as 47653 (time since epoch), dates presented in inconsistent styles (US format versus UK format), occasional typos in names of departments or other entities etc. We did our best to correct these as part of the load. However, it’s doubtful any of the issues we found got fixed (and certainly not as a result of our work) and we also didn’t do much to share with other datawranglers who were working on the data. Why was this? First, there is no mechanism to feed back to the publishers (we did notify of some of the issues we found but it is very hard for them to act on this — the precise ‘publisher’ within a department may be hard to identify and may even be a machine (if the data is automatically produced in some way). Second, there is no easy format in which to share fixes. Our cleaning code was public on the web but a bunch of python if statements is not the best ‘patch’ format for data. In a perfect world we’d have a patch format for data (or even just for csv’s) — and one that was algorithmic not line-based (so one could specific in one statement column X is wrongly formatted in this way rather than have 10k line changes); that was easily reviewable (we’re patching government spending data here!); and automatically apply-able (in short a patch format with tool support).

  1. I’m inevitably simplifying here. For example, there is of course some direct consumption by end users. There is some sharing between systems etc. 
  2. I discussed some of the work around data revisioning in this previous post We Need Distributed Revision/Version Control for Data
Related posts:
  1. Open Bibliographic Data: How Should the Ecosystem Work?
  2. Momentum building for open government data in Norway
  3. Articles in CTWatch Quarterly

As coder is for code, X is for data

- February 11, 2011 in Musings

For code we have the term coder, as in, “he’s a great coder”, but what do we use when talking about data? datanaut, datar, data wrangler, data hacker, data geek …? Suggestions (and votes) please in a comment or tweet! (@okfn or @rufuspollock) Would also be nice to have equivalents for the many variations that code has: hacker, geek, codesmith, programmer … Update: 14h in … So far have the following list. Many of these are 2 word versions of form data + ‘something’. I personally have a preference for just one word (as in coder versus software developer …). Single words (generally newly coined!): Two words
  • data wrangler (x3)
  • data geek (x2)
  • data nerds (Hjalmar)
  • data cruncher (Conrad)
  • data juggler (Conrad – job description!)
  • data artist (@psychemedia)
  • data mechanic (@exmosis)
  • data engineer (@Laura_B_James)
  • data scientist
  • data prospector (Francis Irving)
  • data researcher (may be a bit different)
  • data ninja (Ted Smith)
  • data investigator
  • data shepherd (Eric Hellman)
  • data analyst
  • spreadsheet monkey
Other (existing general word but possibly applicable here): Related posts:
  1. Clear Climate Code, and Data
  2. Clearer Climate Code
  3. Improvements to the Concordance

Playing around with Open Linked Data:

- February 7, 2011 in Guest post, Musings, Open Data

The following guest post is by Christopher Gutteridge, a Web & Systems Programmer and Open Data Architect at the University of Southampton. When he was young he wrote the “coffee stain” filter for GIMP, and is the developer of Graphite RDF PHP library & tools. He is a member of the OKF Working Group on Open Bibliographic Information. I know that it’s best to practice a new technique before employing it on anything major. I also like over-engineering for its own sake. (Beware the Modeller!) That’s how I ended up building There are essentially 3 kinds of dataset on the site.

Esoteric RDF

First of all, the occult stuff. There’s something really satisfying about how over-engineered some of the occult materials are: the agonising effort made to map one system into another, like tarot cards onto the Kaballah. Alisdeir Crowley produced a book that was practically just a huge occult spreadsheet. I really enjoy the process of messing around with data, and it seemed too good a data source to miss, and one nobody else would worry about. In an over-enthusiastic moment, I asked Professor Nigel Shadbolt (the UK Government advisor on Open Data) if occult correspondence was transitive. He gave me one of those expressions that makes you feel like you’ve just put back your career. Not much… maybe a couple of weeks. Still, he’s now got me doing some interesting stuff with Open Data so hopefully he’s forgotten. Don’t get me wrong, I’m not asserting any of that data is true. But the complex interrelating patterns of information remind me of some spiritual precursor to RDF.

Ontological Perversity

The second category of dataset is the perverse ones. I kinda hate OWL and over-modelling. (While I love over-engineering, I think it’s unhelpful. I’ve never actually benefited from writing a machine-readable schema, except to get the AI people to get off my back) The perverse datasets kinda reflect this. The zzStructures is a homage to the fact that they were only a teeny-tiny bit different to RDF, and literally decades earlier (Ted Nelson for the nearly-win!) but those differences hobbled the system. RDF is hobbled too, of course, but less so. Right now most open data is put out from well-meaning liberal sources, and there’s a dangerous assumption that you can find truth in it. There is not absolute truth, and the Daily Mail Cancer Causes dataset is intended as a cautionary dataset to those used to getting open data from the Guardian. It’s screen-scraped from the oncology-ontology site.

How about a nice game of Chess?

The last set of data is accidentally quite interesting. It defines URIs for states of deterministic games like Noughts & Crosses and Chess. The chess one was done because everybody who saw the O&X one suggested it. I’d not recommend actually loading it into a triplestore as it’s generated on-the-fly and, while finite, the data would probably take billions of years to download. Describing a game of chess (or tic-tac-toe) using URIs for the states and moves (my dataset in fact defines a URI for every move from every possible state of a chess game), means you could resolve the URIs to find alternate moves and the state of the board etc. A final bit of headache on this was trying to use the unicode chess symbols as part of the URIs to represent chess-pieces. This wasn’t too bad, but I’d never done it before.

Just because it’s stupid doesn’t mean it’s not Open Linked Data

I have to say I’m rather proud that made it onto the last Linked Open Data Map (down and left a bit from DBPedia). Richard Cyganiak, who produces the map (as well as the invaluable site), was slightly snarky about it, as he does it as a service to the community and it gets bigger every time. But I wrote him a handy little analytical tool by way of apology and he says he’s now forgiven me, so long as I buy him a pint if we ever meet in person. Hopefully his job’s going to get even harder. Our EPrints software puts out Open Data out of the box, with v3.2.1 released last year. The second someone builds a dataset which links 100′s of EPrints (and similar tools) into the diagram, it becomes unmaintainable… And that’s a good sign of healthy take-up of the ideas. I remember my student homepage, back in 1995, appeared in the list of “new pages on the web, today” – as one of over a 1000 pages that day. Soon after that counting became a pointless exercise, thanks to exponential growth. Anyway, now I’ve hopefully got all that over-engineered, low-utility RDF out of my system I can return to my day job, producing sensible, useful open data.

Silliness with SPARQL

Just before I go, here are a couple of silly uses for sensible data. These use SPARQL and dbpedia for very silly ends and were produced as a result of the Oxford Open Data Hack Day. Source: Related posts:
  1. Opening up university infrastructure data
  2. Next version of the Linked Open Data cloud based on CKAN!
  3. Getting started with Governmental Linked Open Data

Turin: Italian Open Data kicks off!

- December 7, 2010 in ckan, Events, Government, Musings, Open Data, Open Government Data, Policy

This post was cowritten by Friedrich Lindenberg, CKAN developer, and Stefano Costa, lead of OKF Italia.
Driven by the powerful combination of late-night espresso and a room full of italian open data enthusiasts, the Italian instance of CKAN received a major push of new pacchetti dati last thursday in Turin. Most of the data sources originated from the Piedmont regional portal for open data reuse In the afternoon before, the group had spent an intense three hours discussing various aspects of open data at the Turin CloudCamp in the city’s high-tech zone, Envipark, with topics ranging from data catalogues to open data policies, and from the economic to the social impact of open government data.
The midnight data hunt also represented last-minute preparations for the first Open Data Conference held by TOP-IX, one of Italy’s major internet exchanges. CKAN and the OKFN community made repeated appearances at the event, first with two invited talks by Rufus Pollock, who spoke about openness as a means for interoperability, and Prodromos Tsiavos, who presented an overview of the current European PSI agenda. During a panel with other Italian open data supporters, Stefano Costa argued for the value of closer connection with the open data movement throughout Europe, also in relation to the development of business opportunities. The message of these two days was clear: open data is gaining a lot of traction south of the alps, and one can be confident that sites like LinkedOpenCamera will soon see a lot of company.