A free software model for open knowledge

Notes describing the talk on the work of the Open Knowledge Foundation given last week at Jornadas SIG Libre.

OKF activity graph

I was happily surprised to be asked to give this open knowledge talk at an open source software conference. But it makes sense – the free software movement has created the conditions in which an open data movement is possible. There is lots to learn from open source process, in both a technical and organisational sense.

In English we have one word “free” where Spanish like most languages has two, gratis and libre, signifying separately “free of cost” and “freedom to”. The Open Source Institute coined Open Source as a branding or marketing exercise to avoid the primary meaning “free of cost”. So whenever I say “open” I want you to hear the word “libre” [Later i was told that libre can have meaning in at least 15 different ways]

The best way to talk about the work of the Open Knowledge Foundation is to look at its projects, which form an open knowledge stack similar to the OSGeo software stack.

Open Definition

The Open Knowledge Definition is based on the OSI Open Source Software Definition (which OSGeo uses as a reference for acceptable software licenses). No restrictions on field of endeavour – non-commercial-use licenses are not open as in the OKD. An open data license will pass the cake test.

Open Data Commons

Open Data Commons is run by Jordan Hatcher, who started work on the Open Database License with support from Talis, later extensive negotiation with the OpenStreetmap community. ODbL is a ShareAlike license for data, that obviates the problems of inapplicability of copyright to facts, and greediness of the ShareAlike clause when it comes to use of maps in PDFs, etc.

PDDL is a license that implements the Science Commons protocol for open access data, explicitly placing it in the public domain.

The Panton Principles are four precepts for publishers of scientific research data who wish that data to be freely reusable. Being openly able to inspect, critique and re-analyse data is critical to the effectiveness of scientific research.

Open Data Grid

The Open Data Grid is a project in early incubation; based on the Tahoe distributed filesystem. It’s in need of development effort on Tahoe to really get going. Provide secure storage for open datasets around the edges of infrastructure that people are already running.

People are handwaving about the Cloud, but storage and backup are not problems that it is really meant to solve. People make different claims about the Cloud – cheaper, greener, more efficient, more flexible. Can we get these things in other ways?

There is a saying, “never underestimate the bandwidth of a truck full of DAT tapes”

Comprehensive Knowledge Archive Network (CKAN)

CKAN is inspired by free software package repositories, perl’s CPAN, R’s CRAN, python’s PyPi. It provides a wiki-like interface to create minimal metadata for packages with a versioned domain model and HTTP API.

CKAN supports groups, which can curate a package namespace – e.g. climate data – and assess priorities for turning into fully installable packages.

CKAN’s open source code is being used in the data package catalogue for the data.gov.uk project, part of the Making Public Data Public effort in the UK.


The Debian of Data – datapkg takes Debian’s apt tool as inspiration for fully automatable install of data packages, with dependencies between them. This is currently in usable alpha stage with a python implementation.

Where Does My Money Go?

The next challenge really is to bring the concerns and the solutions to a mainstream public. Agustín Lobo spoke of “a personal consciousness but not an institutional consciousness” when it comes to open source and open data. Media coverage, exemplary government implementations, help to create this kind of consciousness.

Pressure for increased open access is coming from academia – for the research data underlying papers, for the right to data mine and correlate different sources, for library data open for re-use. Pressure is also coming from within museums, libraries and archives – memory institutions who want to increase exposure to their collections with new technology, and recognise that open data, linked to a network of resources, will work for sustainability and not against it.

The next generation of researchers, who are kids in school now, will grow up with an expectation that code and data are naturally open. It will be interesting to see what they make!

Meanwhile OpenStreetmap is feeding several startups, and more commercial presence in open data space will be of benefit. Illustrative that one does not have to be proprietary to be commercial.

Now higher-profile government projects opening data are helping to mainstream. To what extent is open a fashionable position, to what extent is open reflected throughout the way of working?

Open process; early release, public sharing of bugs, public discussion of plans – everything in Nat Torkington’s post on Truly Open Data. The opportunity to fail in public, to learn from others’ problems, and self-interestedly collaborate.

I had a great time at SIG Libre 10. Oscar Fonts’ talk on OpenSearch Geospatial interfaces to popular services has me itching to add an OpenSearch +Geo interface to CKAN, as well as to work on getting the apparent version skew in the Geo extensions resolved amicably.

Genís Roca spoke thought-provokingly on Retorno y rentabilidad (there isn’t really an equivalent English word – “rentability” – less exploitative or focused than profitability). Rentability, especially for online services, can come in ways that sustain an organisation predictably, and don’t involve fishing in the pockets of ultimate end-users.

Ivan Sanchez showed areas of OpenStreetmap Spain with stunning level of detail, trees and fences, MasterMap-quality coverage. I’m inspired to pick up JOSM and Markaartor to add building-level detail from out of copyright 1:500 Edinburgh town plans at the National Library of Scotland’s map services.

Agustin Lobo talked about the distributed work and cross-institutional support and benefit of the R project, and the impact of open source on open access to data in science. He mentioned a Nature open peer review experiment that was discarded – am thinking it wasn’t curated enough. The talk helped me to connect the OKF’s work to the rest of the Jornadas.

The shiny slides prezi.com which many people asked for details of – this should show embedded in the page I hope. I stupidly forgot to put URLs on the slides which is partly why i have written this blog.

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