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The state of open licensing in 2017

- June 8, 2017 in Global Open Data Index, Open Definition, Open Government Data, Open Knowledge

This blog post is part of our Global Open Data Index (GODI) blog series. Firstly, it discusses what open licensing is and why it is crucial for opening up data. Afterward, it outlines the most urgent issues around open licensing as identified in the latest edition of the Global Open Data Index and concludes with 10 recommendations how open data advocates can unlock this data. The blog post was jointly written by Danny Lämmerhirt and Freyja van den Boom.   Open data must be reusable by anyone and users need the right to access and use data freely, for any purpose. But legal conditions often block the effective use of data. Whoever wants to use existing data needs to know whether they have the right to do so. Researchers cannot use others’ data if they are unsure whether they would be violating intellectual property rights. For example, a developer wanting to locate multinational companies in different countries and visualize their paid taxes can’t do so unless they can find how this business information is licensed. Having clear and open licenses attached to the data, which allow for use with the least restrictions possible, are necessary to make this happen.   Yet, open licenses still have a long way to go. The Global Open Data Index (GODI) 2016/17 shows that only a small portion of government data can be used without legal restrictions. This blog post discusses the status of ‘legal’ openness. We start by explaining what open licenses are and discussing GODI’s most recent findings around open licensing. And we conclude by offering policy- and decisionmakers practical recommendations to improve open licensing.   What is an open license? As the Open Definition states, data is legally open “if the legal conditions under which data is provided allow for free use”.  For a license to be an open license it must comply with the conditions set out under the  Open Definition 2.1.  These legal conditions include specific requirements on use, non-discrimination, redistribution, modification, and no charge.   Why do we need open licenses? Data may fall under copyright protection. Copyright grants the author of an original work exclusive rights over that work. If you want to use a work under copyright protection you need to have permission. There are exceptions and limitations to copyright when permission is not needed for example when the data is in the ‘public domain’ it is not or no longer protected by copyright, or when your use is permitted under an exception.   Be aware that some countries also allow legal protection for databases which limit what use can be made of the data and the database. It is important to check what the national requirements are, as they may differ.   Because some types of data (papers, images) can fall under the scope of copyright protection we need data licensing. Data licensing helps solve problems in practice including not knowing whether the data is indeed copyright protected and how to get permission. Governments should therefore clearly state if their data is in the public domain or when the data falls under the scope of copyright protection what the license is.
  • When data is public domain it is recommended to use the CC0 Public Domain license for clarity.
  • When the data falls under the scope of copyright it is recommended to use an existing Open license such as CC-BY to improve interoperability.
Using Creative Commons or Open Data Commons licenses is best practice. Many governments already apply one of the Creative Commons licenses (see this wiki). Some governments have chosen however to write their own licenses or formulate ‘terms of use’ which grant use rights similar to widely acknowledged open licenses. This is problematic from the perspective of the user because of interoperability. The proliferation of ever more open government licenses has been criticized for a long time. By creating their own versions, governments may add unnecessary information for users, cause incompatibility and significantly reduce reusability of data.  Creative Commons licenses are designed to reduce these problems by clearly communicating use rights and to make the sharing and reuse of works possible.  

The state of open licensing in 2017

Initial results from the GODI 2016/17 show roughly that only 38 percent of the eligible datasets were openly licensed (this value may change slightly after the final publication on June 15). The other licenses include many use restrictions including use limitations to non-commercial purposes, restrictions on reuse and/or modifications of the data.     Where data is openly licensed, best practices are hardly ever followed In the majority of cases, our research team found governments apply general terms of use instead of specific licenses for the data. Open government licenses and Creative Commons licenses were seldom used. As outlined above, this is problematic. Using customized licenses or terms of use may impose additional requirements such as:
  • Require specific attribution statements desired by the publisher
  • Add clauses that make it unclear how data can be reused and modified.
  • Adapt licenses to local legislation
Throughout our assessment, we encountered unnecessary or ambivalent clauses, which in turn may cause legal concerns, especially when people consider to use data commercially. Sometimes we came across redundant clauses that cause more confusion than clarity.  For example clauses may forbid to use data in an unlawful way (see also the discussion here).   Standard open licenses are intended to reduce legal ambiguity and enable everyone to understand use rights. Yet many licenses and terms contain unclear clauses or are not obvious to what data they refer to. This can, for instance, mean that governments restrict the use of substantial parts of a database (and only allow the use of insignificant parts of it). We recommend that governments give clear examples which use cases are acceptable and which ones are not.   Licenses do not make clear enough to what data they apply.  Data should include a link to the license, but this is not commonly done. For instance, in Mexico, we found out that procurement information available via Compranet, the procurement platform for the Federal Government, was openly licensed, but the website does not state this clearly. Mexico hosts the same procurement data on datos.gob.mx and applies an open license to this data. As a government official told us, the procurement data is therefore openly licensed, regardless where it is hosted. But again this is not clear to the user who may find this data on a different website. Therefore we recommend to always have the data accompanied with a link to the license.  We also recommend to have a license notice attached or ‘in’ the data too. And to keep the links updated to avoid ‘link rot’.   The absence of links between data and legal terms makes an assessment of open licenses impossible Users may need to consult legal texts and see if the rights granted to comply with the open definition. Problems arise if there is not a clear explanation or translation available what specific licenses entail for the end user. One problem is that users need to translate the text and when the text is not in a machine-readable format they cannot use translation services. Our experience shows that it was a significant source of error in our assessment. If open data experts struggle to assess public domain status, this problem is even exacerbated for open data users. Assessing public domain status requires substantial knowledge of copyright – something the use of open licenses explicitly wants to avoid.   Copyright notices on websites can confuse users. In several cases, submitters and reviewers were unable to find any terms or conditions. In the absence of any other legal terms, submitters sometimes referred to copyright notices that they found in website footers. These copyright details, however, do not necessarily refer to the actual data. Often they are simply a standard copyright notice referring to the website.

Recommendations for data publishers

Based on our finding we prepared 10 recommendations that policymakers and other government officials should take into account:  
  1. Does the data and/or dataset fall under the scope of IP protection? Often government data does not fall under copyright protection and should not be presented as such. Governments should be aware and clear about the scope of intellectual property (IP) protection.
  2. Use standardized open licenses. Open licenses are easily understandable and should be the first choice. The Open Definition provides conformant licenses that are interoperable with one another.
  3. In some cases, governments might want to use a customized open government license. These should be as open as possible with the least restrictions necessary and compatible (see point 2). To guarantee a license is compatible, the best practice is to submit the license for approval under the Open Definition.
  4. Exactly pinpoint within the license what data it refers to and provide a timestamp when the data has been provided.
  5. Clearly, publish open licensing details next to the data. The license should be clearly attached to the data and be both human and machine-readable. It also helps to have a license notice ‘in’ the data.
  6. Maintain the links to licenses so that users can access license terms at all times.
  7. Highlight the license version and provide context how data can be used.
  8. Whenever possible, avoid restrictive clauses that are not included in standard licenses.
  9. Re-evaluate the web design and avoid confusing and contradictory copyright notices in website footers, as well as disclaimers and terms of use.
  10. When government data is in the public domain by default, make clear to end users what that means for them.
 

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Announcement – Open Definition 2.1

- November 10, 2015 in Open Definition, Open Knowledge

Today Open Knowledge and the Open Definition Advisory Council are pleased to announce the release of version 2.1 of the Open Definition. The definition “sets out principles that define openness in relation to data and content” and continues to play a key role in supporting the growing open ecosystem. The Open Definition was first published in 2005 by Open Knowledge and is maintained today by an expert Advisory Council. This new version is a refinement of version 2.0, which was the most significant revision in the Definition’s nearly eleven-year history. This version is a result of over one year of discussion and consultation with the community including input from experts involved in open data, open access, open culture, open education, open government, and open source. This version continues to adhere to the core principles while strengthening and clarifying the Definition in three main areas.

What’s New

Version 2.1 incorporates the following changes:
  • Section 1.1 Open License or Status, formerly named Open License, has been changed to more clearly and explicitly include works that while not released under a license per se, are still considered open, such as works in the public domain.
  • In Version 2.0, section 1.3 specified the requirement for both machine readability and open formats. In Version 2.1 these requirements are now separated into their own sections 1.3 Machine Readability and 1.4 Open Format.
  • The new 1.4 Open Format section has been strengthened such that in order to be considered open, the work has to be able to be both in a format which places no restrictions, monetary or otherwise and it has to be able to be fully processed by at least one free/libre/open-source software tool. In version 2.0 only one of these conditions was needed to satisfy the requirement.
  • An attribution addendum has been added to recognize the work that the definition is based on.
Version 2.1 also includes several other less significant changes to enhance clarity and better convey the requirements and acceptable conditions.

More Information

Authors

This post was written by Herb Lainchbury, Chair of the Open Definition Advisory Council and Rufus Pollock, President and Founder of Open Knowledge.

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Open Definition: versione 2.0

- November 9, 2014 in Licenze, Open Data, Open Definition, openknowledge, Riuso

Lo scorso 7 ottobre Open Knowledge in collaborazione con Open Definition Advisory Council ha annunciato il rilascio della versione 2.0 della Open Definition. In italiano trovate on line la traduzione della versione 1.0 qui. Nella Open Definition si dichiarano i principi di base che definiscono il significato di “openness”, apertura, in relazione a dati e contenuti. La Open […]

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Open Definition: versione 2.0

- November 9, 2014 in Licenze, Open Data, Open Definition, openknowledge, Riuso

Lo scorso 7 ottobre Open Knowledge in collaborazione con Open Definition Advisory Council ha annunciato il rilascio della versione 2.0 della Open Definition. In italiano trovate on line la traduzione della versione 1.0 qui. Nella Open Definition si dichiarano i principi di base che definiscono il significato di “openness”, apertura, in relazione a dati e contenuti. La Open […]

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Open Definition: versione 2.0

- November 9, 2014 in Licenze, Open Data, Open Definition, openknowledge, Riuso

Lo scorso 7 ottobre Open Knowledge in collaborazione con Open Definition Advisory Council ha annunciato il rilascio della versione 2.0 della Open Definition. In italiano trovate on line la traduzione della versione 1.0 qui. Nella Open Definition si dichiarano i principi di base che definiscono il significato di “openness”, apertura, in relazione a dati e contenuti. La Open […]

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Veröffentlichung Open Definition 2.0 & deutsche Übersetzung

- October 21, 2014 in Featured, offene Daten, Open Definition, Open Knowledge Foundation

open-definition-deBereits vor knapp zwei Wochen wurde die zweite Version der Open Definition veröffentlicht. Sie definiert Grundprinzipien für Open Data, Open Content und schreibt unsere Grundprinzipien für Offenheit bei Open Data und offenen Inhalten aller Art jenseits von Open-Source-Software fest. Seit 7. Oktober ist sie in der überarbeiteten Version 2.0 verfügbar. Ziel der Open Definition war und ist es OpenWashing identifizierbar zu machen und zu vermeiden, sowie rechtliche Probleme auf Grund der Verwendung falscher oder nicht kompatibler Open-Lizenzen präventiv zu verhindern. Ebenfalls neu: die Daten-Deutschland-Lizenz 2.0 wurde in diesem Zusammenhang als kompatible Lizenz mit aufgenommen (wie bereits angekündigt). Auch wenn es bereits Kritikpunkte an der neuen Version der Defintition gibt, rufen Christian Hauschke und Adrian Pohl dazu auf bei der Übersetzung der Version 2.0 in die deutsche Sprache zu helfen. Dabei sollen eventuellen Schwächen in der Definition nicht Aufgabe der Übersetzung sein. Wir unterstützen diesen Aufruf. Bei der Übersetzung kann im Pad unter https://pad.okfn.org/p/OpenDefinitionde geholfen werden.

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Open Definition v2.0 Released – Major Update of Essential Standard for Open Data and Open Content

- October 7, 2014 in Featured, News, Open Content, Open Data, Open Definition

Today Open Knowledge and the Open Definition Advisory Council are pleased to announce the release of version 2.0 of the Open Definition. The Definition “sets out principles that define openness in relation to data and content” and plays a key role in supporting the growing open data ecosystem. Recent years have seen an explosion in the release of open data by dozens of governments including the G8. Recent estimates by McKinsey put the potential benefits of open data at over $1 trillion and others estimates put benefits at more than 1% of global GDP. However, these benefits are at significant risk both from quality problems such as “open-washing” (non-open data being passed off as open) and from fragmentation of the open data ecosystem due to incompatibility between the growing number of “open” licenses. The Open Definition eliminates these risks and ensures we realize the full benefits of open by guaranteeing quality and preventing incompatibility.See this recent post for more about why the Open Definition is so important. The Open Definition was published in 2005 by Open Knowledge and is maintained today by an expert Advisory Council. This new version of the Open Definition is the most significant revision in the Definition’s nearly ten-year history. It reflects more than a year of discussion and consultation with the community including input from experts involved in open data, open access, open culture, open education, open government, and open source. Whilst there are no changes to the core principles, the Definition has been completely reworked with a new structure and new text as well as a new process for reviewing licenses (which has been trialled with governments including the UK). Herb Lainchbury, Chair of the Open Definition Advisory Council, said:
“The Open Definition describes the principles that define “openness” in relation to data and content, and is used to assess whether a particular licence meets that standard. A key goal of this new version is to make it easier to assess whether the growing number of open licenses actually make the grade. The more we can increase everyone’s confidence in their use of open works, the more they will be able to focus on creating value with open works.”
Rufus Pollock, President and Founder of Open Knowledge said:
“Since we created the Open Definition in 2005 it has played a key role in the growing open data and open content communities. It acts as the “gold standard” for open data and content guaranteeing quality and preventing incompatibility. As a standard, the Open Definition plays a key role in underpinning the “open knowledge economy” with a potential value that runs into the hundreds of billions – or even trillions – worldwide.”

What’s New

In process for more than a year, the new version was collaboratively and openly developed with input from experts involved in open access, open culture, open data, open education, open government, open source and wiki communities. The new version of the definition:
  • Has a complete rewrite of the core principles – preserving their meaning but using simpler language and clarifying key aspects.
  • Introduces a clear separation of the definition of an open license from an open work (with the latter depending on the former). This not only simplifies the conceptual structure but provides a proper definition of open license and makes it easier to “self-assess” licenses for conformance with the Open Definition.
  • The definition of an Open Work within the Open Definition is now a set of three key principles:
    • Open License: The work must be available under an open license (as defined in the following section but this includes freedom to use, build on, modify and share).
    • Access: The work shall be available as a whole and at no more than a reasonable one-time reproduction cost, preferably downloadable via the Internet without charge
    • Open Format: The work must be provided in a convenient and modifiable form such that there are no unnecessary technological obstacles to the performance of the licensed rights. Specifically, data should be machine-readable, available in bulk, and provided in an open format or, at the very least, can be processed with at least one free/libre/open-source software tool.
  • Includes improved license approval process to make it easier for license creators to check conformance of their license with the Open Definition and to encourage reuse of existing open licenses (rrareuse and outlines the process for submitting a license so that it can be checked for conformance against the Open Definition.

More Information

  • For more information about the Open Definition including the updated version visit: http://opendefinition.org/
  • For background on why the Open Definition matters, read the recent article ‘Why the Open Definition Matters’

Authors

This post was written by Herb Lainchbury, Chair of the Open Definition Advisory Council and Rufus Pollock, President and Founder of Open Knowledge

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Why the Open Definition Matters for Open Data: Quality, Compatibility and Simplicity

- September 30, 2014 in Featured, Open Data, Open Definition, Policy

The Open Definition performs an essential function as a “standard”, ensuring that when you say “open data” and I say “open data” we both mean the same thing. This standardization, in turn, ensures the quality, compatibility and simplicity essential to realizing one of the main practical benefits of “openness”: the greatly increased ability to combine different datasets together to drive innovation, insight and change. This post explores in more detail why it’s important to have a clear standard in the form of the Open Definition for what open means for data.

Three Reasons

There are three main reasons why the Open Definition matters for open data: Quality: open data should mean the freedom for anyone to access, modify and share that data. However, without a well-defined standard detailing what that means we could quickly see “open” being diluted as lots of people claim their data is “open” without actually providing the essential freedoms (for example, claiming data is open but actually requiring payment for commercial use). In this sense the Open Definition is about “quality control”. Compatibility: without an agreed definition it becomes impossible to know if your “open” is the same as my “open”. This means we cannot know whether it’s OK to connect your open data and my open data together since the terms of use may, in fact, be incompatible (at the very least I’ll have to start consulting lawyers just to find out!). The Open Definition helps guarantee compatibility and thus the free ability to mix and combine different open datasets which is one of the key benefits that open data offers. Simplicity: a big promise of open data is simplicity and ease of use. This is not just in the sense of not having to pay for the data itself, its about not having to hire a lawyer to read the license or contract, not having to think about what you can and can’t do and what it means for, say, your business or for your research. A clear, agreed definition ensures that you do not have to worry about complex limitations on how you can use and share open data. Let’s flesh these out in a bit more detail:

Quality Control (avoiding “open-washing” and “dilution” of open)

A key promise of open data is that it can freely accessed and used. Without a clear definition of what exactly that means (e.g. used by whom, for what purpose) there is a risk of dilution especially as open data is attractive for data users. For example, you could quickly find people putting out what they call “open data” but only non-commercial organizations can access the data freely. Thus, without good quality control we risk devaluing open data as a term and concept, as well as excluding key participants and fracturing the community (as we end up with competing and incompatible sets of “open” data).

Compatibility

A single piece of data on its own is rarely useful. Instead data becomes useful when connected or intermixed with other data. If I want to know about the risk of my home getting flooded I need to have geographic data about where my house is located relative to the river and I need to know how often the river floods (and how much). That’s why “open data”, as defined by the Open Definition, isn’t just about the freedom to access a piece of data, but also about the freedom connect or intermix that dataset with others. Unfortunately, we cannot take compatibility for granted. Without a standard like the Open Definition it becomes impossible to know if your “open” is the same as my “open”. This means, in turn, that we cannot know whether it’s OK to connect (or mix) your open data and my open data together (without consulting lawyers!) – and it may turn out that we can’t because your open data license is incompatible with my open data license. Think of power sockets around the world. Imagine if every electrical device had a different plug and needed a different power socket. When I came over to your house I’d need to bring an adapter! Thanks to standardization at least in a given country power-sockets are almost always the same – so I bring my laptop over to your house without a problem. However, when you travel abroad you may have to take adapter with you. What drives this is standardization (or its lack): within your own country everyone has standardized on the same socket type but different countries may not share a standard and hence you need to get an adapter (or run out of power!). For open data, the risk of incompatibility is growing as more open data is released and more and more open data publishers such as governments write their own “open data licenses” (with the potential for these different licenses to be mutually incompatible). The Open Definition helps prevent incompatibility by:

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« Open Washing » : la différence entre ouvrir vos données ou simplement y donner accès

- March 19, 2014 in api, google maps, licence ouverte, Open Data, Open Definition, Open Street Map

(Cet article est la version française, dérivée de la version anglaise, “Open-washing” – The difference between opening your data and simply making them available publié par Christian Villum sur le blog de l’OKF. Il a été traduit et adapté dans sa version française par Samuel Azoulay, Samuel Goëta et François Roels.) 

Le 3 février 2014, le service de vélos en libre service parisien Vélib se réjouissait sur son blog d’ « une nouvelle utilisation de l’open data Velib« . En effet, le travail d’Etienne Côme avec les données origine/destination des trajets donne à voir le trafic cyclable à Paris sous un nouveau jour. Sauf que vous pouvez chercher longtemps les données sur le site developer.jcdecaux.com, elles n’y sont pas et n’y ont jamais été. Les données proviennent en effet d’un partenariat de recherche.

Capture d’écran 2014-03-18 à 12.22.23

…qui n’utilise pas l’open data de Velib !

Récemment aussi, Open Street Map remarquait que La Poste communiquait beaucoup sur l’open data alors que seulement deux jeux de données sont en ligne : la liste des bureaux de poste et espaces de retrait Colissimo ainsi que leurs horaires d’ouverture. A l’occasion d’un concours de services open data, de nouvelles données ont été mises à disposition des participants mais uniquement pour la durée de l’évenement ; il était même interdit de les utiliser par la suite.

Enfin, le 14 mars, un article de 01Net annonçait que la Banque Publique d’Investissement (BPI) allait ouvrir ses données. Pourtant, le site « Le Lab »  qui donne accès à « 578 études, enquêtes et séries statistiques » ne présente principalement que des fichiers PDF souvent accessibles uniquement via une interface en flash, une technologie pas des plus ouvertes. Toujours sur ce site, la Banque se réjouit que « Bpifrance est ainsi la première banque française à initier une démarche « d’open data » mais « dans un environnement parfaitement sécurisé ». En effet, pour accéder aux données, il faut montrer patte blanche : appartenir à une institution scientifique, proposer une analyse nouvelle et traiter de la thématique des PME.

Cette manière très particulière de fournir des données nous amène au problème auquel nous faisons face : connaître la différence entre rendre les données accessibles et les rendre ouvertes. Cela rejoint un argument très récurrent qui consiste à considérer que Google Maps fait de l’open data puisque le service fournit une interface de programmation (API). Les données ouvertes ne sont pas seulement caractérisées par leur disponibilité mais par le double fait qu’elles sont légalement ouvertes (fournies sous une licence ouverte qui autorise une réutilisation libre et entière, avec au plus la mention de la source et la même licence) et techniquement disponibles dans des formats bruts et lisibles par les machines – au contraire de ce que propose Google Maps. Leurs données sont peut-être disponibles mais elles ne sont pas ouvertes. Voici pourquoi – entre autres raisons – la communauté autour de l’alternative 100% ouverte Open Street Map croît rapidement et pourquoi un nombre croissant d’entreprises choisissent de baser leurs services sur cette initiative ouverte. Mais pourquoi est-il si important que les données soient ouvertes et pas seulement accessibles ? Les données ouvertes consolident la société et constituent une ressource partagée où tous les citoyens et les entreprises s’enrichissent et se renforcent, et pas seulement les collecteurs de données et leurs diffuseurs. « Mais pourquoi les entreprises dépenseraient de l’argent à collecter des données pour ensuite les abandonner ? » demanderez-vous. Ouvrir vos données et faire du profit ne sont pas deux choses mutuellement exclusives. Une rapide recherche sur Google montre que beaucoup d’entreprises proposent des données ouvertes, tout en les valorisant.
Un exemple est celui de la compagnie anglaise OpenCorporates, laquelle propose son référentiel de données sur les entreprises en accès ouvert, et se positionne ainsi comme un référence incontournable dans son domaine. Cette approche renforce les opportunités de proposer des services de conseil, d’analyse de données et autres services pour, à la fois, les entreprises et le secteur public. Les autres entreprises sont incitées à utiliser les données, même pour un usage concurrent ou pour créer d’autres services, mais uniquement sous des termes de licence identiques – et fournissent ainsi une ressource dérivée qui peut être utile à OpenCorporates. Ici réside la réelle innovation et la démarche durable – décloisonnant les silos et créant de la valeur pour la société, pas seulement les entreprises concernées. Les données ouvertes créent de la croissance et de l’innovation dans notre société – quand la manière qu’a Google de proposer ses données crée probablement principalement de la croissance pour… Google.
Capture d’écran 2014-03-18 à 12.30.38
Nous constatons une tendance croissante à ce que l’on peut appeler l’open-washing » (inspiré du «greenwashing» ou éco-blanchiment) où les producteurs de données proclament leurs données ouvertes, même si ce n’est pas le cas dans les faits : les données sont juste disponibles sous des termes limitatifs. Si nous ne sommes pas attentifs à cette différence, nous finirons par mettre nos flux de données vitales dans des infrastructures en silos construites et détenues par des entreprises internationales. Et nous ferons alors l’éloge d’un mode de développement technologique néfaste et non-soutenable.

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Creative Commons 4.0 BY and BY-SA licenses approved conformant with the Open Definition

- January 8, 2014 in Open Definition

cc40-itshere-2751 This post by Timothy Vollmer, Manager of Policy and Data at Creative Commons, originally appeared on the creativecommons.org website. In November we released version 4.0 of the Creative Commons license suite, and today the Open Definition Advisory Council approved the CC 4.0 Attribution (BY) and Attribution-ShareAlike (BY-SA) International licenses as conformant with the Open Definition.
The Open Definition sets out principles that define “openness” in relation to data and content…It can be summed up in the statement that: “A piece of data or content is open if anyone is free to use, reuse, and redistribute it — subject only, at most, to the requirement to attribute and/or share-alike.”

Prior versions of Creative Commons BY and BY-SA licenses (1.0 – 3.0, including jurisdiction ports) are also aligned with the Open Definition, as is the CC0 Public Domain Dedication. Here’s the complete list of conformant licenses. None of the Creative Commons NonCommercial or NoDerivatives licenses comply with the Definition. The Open Definition is an important marker that communicates the fundamental legal conditions that make content and data open, and CC is working on ways to better display which of our licenses conform to the Definition. We appreciate the open and participatory process conducted by the Open Definition Advisory Council in evaluating licenses and providing expert assistance and advice to license stewards. Individuals interested in participating in the Open Definition license review process may join the OD-discuss email list.

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