OpenCorporates – Exploring the corporate world through data

Evening workshop looking at the data and tools for exploring the global corporate world.

18.30 – 21.00 Tuesday 27th June 2017
Federation House
Federation Street
Manchester
Register Here

If there is one thing that Panama Papers proved, it is that shell companies and opaque jurisdictions allow money and assets to be kept secret, making it difficult for investigators to detect corruption, money laundering and organized crime.

In 2010 OpenCorporates was founded as an effort to identify where companies were based and how they linked across the world. It is now the largest open database of companies and company data, with in excess of 100 million companies in a similarly large number of jurisdictions. Their primary goal is to make information on companies more usable and more widely available for the public benefit, particularly to tackle the use of companies for criminal or anti-social purposes, for example corruption, money laundering and organised crime.

This is a workshop that will enable people and organisations to harness the power of this huge pool of data. Whether you are an activist, organisation or just plain interested, this workshop will help give you the tools to explore the complex, connected world of corporate organisations.

Open Data Cooperation – Building a data cooperative

Last year Open Data Manchester held two workshops one in Berlin and the other in Manchester to explore whether cooperative structures could enable the creation of open data and personal data stores for mutual benefit. The idea of the mutual came out of an ongoing conversation between people within the cooperative movement and the open data world about the role of cooperatives, and the possibility that they could rebalance what many perceive as asymmetric relationship between data subjects (people with personal data) and data users (people who use data to develop services and products).

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Background

Our modern technologised societies exist on data. Mostly these data are invisible and unknown to us. The services that we interact with, the daily transactions that we make and the way we negotiate through our everyday generate data, building a picture of who we are and what we do.  In the age of the Quantified Self there is a growing trend for self monitoring allowing us to track what we do and how feel when we do it. These data are valuable. Aggregated they enable organisations to predict, personalise and intervene seamlessly and sometimes invisibly. Even for the most technically literate, keeping track of what we do and don’t give away is daunting. Personal Information Management Services (PIMS) are starting to emerge offering people the chance to stem the unbridled exploitation of personal data by both public and private organisations whilst also creating monetary rewards for their users. Many of these commercial organisations seek to act as a brokerage service for personal data. The creation of data cooperatives that can act as PIMS have the potential to empower individuals to have more control over their data, creating value for themselves and their communities, and for people to have more of a say in the services that are built.

The sensational revelations by Edward Snowdon shone a spotlight on the personal data that is collected through the IT software and hardware infrastructure that we rely on today. Although highlighting that we unintentionally give away a lot, it perhaps hasn’t built  a wider popular discussion around protection and usage of personal data. It is inevitable that as the awareness about the data that we produce rises there will be a demand for services that give people more control. PIMS offer to deliver monetary value to users, but how much value is up for debate as there are differing methodologies to quantify it [OECD 2013]. Value can also be context dependant – data about someone exhibiting behaviours that might indicate a large purchase might be deemed more valuable by companies that manufacture or sell that item.

Data cooperatives are starting to emerge that have a broader social and ethical outlook than simple monetary transaction. The Good Data which allows people to control data flow at a browser level with benefits going to social causes and the Swiss-based Health Bank where personal health data is aggregated for the advancement of medicine, are examples of this. As the principles of data custodianship for social good become understood there becomes an opportunity for more to emerge.

Data cooperatives can represent the interests of data subjects and data users

Cooperatives come in many flavours, traditionally coming out of the needs of the membership who subscribe to them. Structures of these cooperatives have generally been organised around a single class of member – workers, producers, consumers, etc. The single class structure although creating an equitable environment for members, can tend towards self interest and even though they may be bound by the notion of common good, the mechanism for the creation of the common good or commons is seldom explicit.

Internationally the creation of new forms of cooperatives that explicitly express the development of common good, across multiple classes of stakeholders are more abundant. Social co-ops in Italy and Solidarity coops in Canada often provide services such as health and social care, education as well as community infrastructure projects.

The ability to have multiple classes of stakeholders within a data cooperative has the potential to create a more equitable environment for both data users and data subjects to exchange data. The influence of different classes within the organisations could be managed by fair distribution of voting rights with a user such as a research organisation having the same voting rights as a data subject.

Michel Bauwens founder of the P2P Foundation talks about the creation of these new forms of cooperatives, and how they can build a commons both material and immaterial. This commons would be subscribed to by other commons creating entities and licenced to non-commons creating organisations. This suggests a federated relationship between such organisations where commons is shared, could exist. But the challenge would be how to define the exchange within this system and if a cooperative contained both producers and users how does this affect the production of commons?

Would a data cooperative necessarily adopt these newer forms of distributed and commons creating structure? There appears to be a consensus that commons creating, multi-stakeholders cooperatives are positive, but they come with increased complexity. Can individual circumstances especially when dealing with communities based around sensitive issues, create an environment for sharing beyond a single class of stakeholder? A single class cooperative may seem to be a simpler, immediate solution for a community of people who have specific needs and issues and where strong trust relationships need to be maintained.

The scale of data cooperatives

Data cooperatives have the potential to work at scale generating and trading in bulk, high worth data as well as forming around smaller communities of interest, such as around a particular health issue, to draw down or negotiate for a better services.

Creating a critical mass of data subjects that would allow the data cooperative to operate at scale would be challenging. Marcos Menendez from The Good Data sees that for PIMS such as themselves would need to create a minimum data subject base of around 500,000 people to be viable. There is potential for data cooperatives to partner with organisations or charities with a similar ethical outlook to build the data subject base.

It may be easier to form cooperatives around single issues as the community the cooperative seeks to represent will already be in existence. The value of such an organisation might be that it can help create a more informed decision making process with views of the data subject being represented. Within a multi-stakeholder model the service provider might also be part of the data cooperative such as a local authority or other public sector organisation

Making the purpose of the data cooperative understandable is key. Although single issue cooperatives are relatively simple to understand, the representation of data at scale may be challenging. Data cooperatives could act as a platform that builds consent and allowing the representation of personal data across a broader portfolio of interests.

Building trust and consent within the data cooperative

Trust and consent should be the foundations on which PIMS are built and data cooperatives have the potential to create both. Mutuality offers an opportunity – especially with a multi stakeholder model – to represent the interests of all stakeholders from individual data subjects to data users – creating an environment of mutual understanding and trust. The benefits of enhanced trust between the individual data subjects and data users could enable better data and context to be created by data subjects. Through understanding the ways that the data is being used and trusting that the data user understands the needs and concerns of the data subjects, could create a more enlightened and responsive relationship. Even without data users being part of the organisation, the data cooperative would be able to take on the role of trusted representative which in turn could create consent.

Informed consent across all data subjects in a cooperative could be challenging. It would be easy for a data organisation to empower those that already have knowledge and agency to maximise their data, but the data cooperative should have an interest in empowering everyone.

Increasing data literacy amongst members

Raising the level of data awareness amongst cooperative members would create more informed decision making, but this task would need to be delivered in a sympathetic and nuanced way. Ultimately some people may not engage because of service dependency, lack of choice. or a perception that it isn’t relevant or useful to engage.

For a data cooperative to represent its membership and control the flow of data it needs to have legitimacy, know and understand the data assets of the membership, and have the authority to negotiate with those data assets on the members behalf.

Decisions around data sharing and understanding the potential consequences are difficult and complex. As an intermediary the cooperative would need to ensure that individual members were able to give informed consent. Data literacy goes some way to achieving this but also mechanisms need to be created that can allow people to have agency over the way that their data is used.

Creating consent

Can one organisation be representative of the broader range of ethical positions held within a membership structure? For practical reasons the data cooperative might have a high level ethical policy but individuals within the cooperative may make data sharing choices based on their personal ethical standpoint. This could be enabled by proxy or preset data sharing preferences. The alternative could be to have smaller federated or distributed niche organisations that have specific restrictions on data reuse.

There exist many mechanisms for the creation of consent. These by and large create the environment for proxy voting in decision making processes. A mechanism such as Liquid Feedback – popularised by the Pirate Party, where an individual bestows voting rights to a proxy who aligns to their position, with the ‘liquid’ element allowing proxy rights to be revoked at any point. Other mechanisms might follow along the lines of the Platform Preferences initiative developed by W3C, which sought to create privacy policies that could be understood by browsers – ultimately considered too difficult to implement. A potentially easier solution might work on the basis of preset preferences based on trusted individuals or the creation of archetype or persona based preferences that people can select.

Creating a more equitable data relationship

How would the argument for greater individual data rights be made when service providers see that personal data mediated through their products as their intellectual property? Work has been done through the midata initiative and the developments of personal data passports – where individuals grant rights to organisations to use the data for delivery of service. UK Government has supported this initiative, but has backed away from underpinning the programme with changes in legislation. The lack of regulatory enforcement may limit the efficacy of any initiative that seeks to grant individuals’ rights and agency over their data.

At present there is a certain level of cynicism around voluntary codes of practice where power imbalances exist between stakeholders. The lack of legislation might also create a chilling effect on the ability of data cooperatives to gain the trust of their membership due to their inability to totally control the flow of data.

Existing UK data legislation does give data subjects rights to access personal data held by external organisations through Subject Access Requests. A data cooperative could act as a proxy for individual members automating regular Subject Access Requests. This model is being explored by Our Data Mutual in Leeds, UK. There are challenges with using Subject Access Requests at present. Organisations can charge up to £10 for each request and although provision of the data in digital format may be specified, responses usually take the form of reams of paper print outs with responses taking up to 40 days.

It has been mooted by the UK Government that the cost of Subject Access Requests will be reduced – potentially to zero and that organisations will be compelled to supply the data in digital format. This would go a long way to making the process of automated Subject Access Requests viable but in an ideal world data should be pushed rather than pulled.

Data supply

A challenge that all data cooperatives would face would be how they maintain a relationship with their membership so that services based upon, or value that is extracted from the data is not subject to unforeseen supply-side problems. If a data cooperative represented its membership and entered into licensing relationships with data users on behalf of its membership, what would be reasonable for a data user to expect, especially if data subjects had the right to revoke access to data at anytime? With larger scale data cooperatives this may not be too much of a problem as scale has the potential to damp down unforeseen effects. The Good Data proposes to get around these issues by only holding data for a limited amount of time essentially, minimising disruptions in data supply by creating a buffer. It may be necessary for the data cooperative to create terms and conditions for data subjects to minimise sudden supply-side issues.

Smaller data cooperatives, especially ones that are created around single issues may have difficulty in engaging in activity that requires service guarantees. Developing a mechanism for federation, cumulatively creating data at scale might be a potential solution, but creating a federated system of consent may be more difficult to achieve. As suggested previously economic activity might be a low priority for such organisations where the main purpose might be to represent members and create the environment for informed service provision.

The challenge facing federated data cooperatives and how they interact is undefined. It has been noted that building distributed and federated systems is difficult, and that centralised systems persist due to operational efficiencies. The advent of alternative forms of ‘block chain’ transaction could enable distributed organisations to coexist using ‘rules based’ or algorithmic democracy. But alternative transaction systems and currencies often face challenges when they interface with dominant and established forms of currency and value. How data cooperatives could practically use these new mechanisms for exchange needs to be explored.

The data cooperative and open data

Although the much of the discussion in the Berlin and Manchester meetings was based on rights and uses of personal data, data cooperatives do offer an interesting model for organisations that create open data, or those that seek to enhance open data with personal data.

An open data cooperative might be a good model for stakeholders who create and use data for public access. It may be a single class model where data suppliers such as public bodies work together or more interestingly a multi-stakeholder model where public data providers work with organisations that manage personal data – these in themselves could be data cooperatives

In summary data cooperatives;

  1. are owned by their membership and therefore should be more accountable;
  2. have the potential put a halt to the over collection of personal data through representing data subjects and advocating on their behalf;
  3. can create value for their membership;
  4. can form around single issues or scale with many data subjects;
  5. can become representative and be used to create change;
  6. could help their membership to understand how data is used – data literacy;
  7. can liberate personal data on members behalf through Subject Access Requests;
  8. can encourage better data and context to be produced by data subjects;
  9. build trust and consent within the organisation and
  10. can be a blend of open data and personal data organisations

Open : Data : Cooperatives – Synopsis

This is a synopsis of the meeting held in Berlin that forms the basis of the upcoming Open : Data : Cooperation event on the 20th October 2014

Open : Data  : Cooperatives.

On the evening of the 16th July 2014 in a small bar of SingerStraße in Berlin a group of Open Knowledge Festival attendees came together for a meeting, to discuss whether cooperatives offered the potential to create formalised structures for the creation and sharing of common data assets, and whether this would enable the creation of value for their stakeholders. This discussion is sets the framework for an event that will take place in Manchester UK on the 20th October 2014

The discussion was initially broken down into seven themes of

  • Models: How do the varied models of cooperative ownership fit to data, and do new forms of cooperative and commons based structure offer potential solutions?
  • Simplicity: Can one model fit all data or do different scenarios need tailored solutions
  • Transparency: How can a cooperative that is steered by its membership along ethical grounds also be considered open?
  • Representation: Do individuals have enough control over their data to enable third party organisations such as a cooperative, to represent their data?
  • Negotiation: How can cooperative members balance control over their data with use by third parties?

  • Governance: Is it possible to create an efficient system of governance that respected the wishes of all members?
  • Mechanisms of transaction: Can a data cooperative exist within a federated cooperative structure and how would it transact and create value.

This is a synopsis of the discussion

Why create a data cooperative?

Our modern, technologised society exists on data. Our everyday interactions leave a trace that is often invisible and unknown to us. The services that we interact with, the daily transactions that we make and the way we negotiate through our everyday generate data, building a picture of who we are and what we do. This data also enables aggregators to predict, personalise and intervene seamlessly and sometimes invisibly. Even for the most technically literate, keeping track of what we do and don’t give away is daunting. There is a need to stem the unbridled exploitation of personal data by both public and private organisations, to empower individuals to have more control over the data they create, and for people to have more of a say in the services that are built upon and informed by this data. Data cooperatives may help rebalance the relationship between those that create data and those that seek to exploit it whilst also creating the environment for fair and consensual exchange.

Structure

Cooperation for the creation of common good is a widely understood concept and in a world where value is often extracted by large organisations with opaque processes and ethics, they are starting to be seen as a way of reinvigorating value transactions within smaller, often under-represented communities of interest, and between organisations that create and use data.

Finding already existing data cooperatives is not easy. Examples such as The Good Data which allow people to control data flow at a browser level and the Swiss-based Health Bank are two known examples, and as the principles of data custodianship for social good become understood there is little to challenge that more would develop.

There are organisations that exhibit cooperative traits but may not themselves be cooperatives or co-owned structures. Open Street Map (OSM) is a resource that is essentially created and administered by the community, with the underlying motivation for OSM being for common good. The open source movement was cited as being the largest example of technological cooperativism, although the largest platform on which cooperative endeavour is expressed (GitHub) is a privately owned Silicon Valley entity.

There are many versions of coops. These have traditionally come out of the needs of the membership who subscribe to them. Structures of these cooperatives have generally been organised around a single class of member – workers, producers, consumers, etc. The single class structure, although creating an equitable environment for those that are members of a particular coop, can tend towards self interest and although they may be bound by the notion of the common good, the mechanism for the creation of the common good or commons is seldom explicit.

Internationally the creation of new forms of cooperatives that explicitly express the development of common good across multiple classes of stakeholders are more abundant. Social co-ops in Italy and Solidarity coops in Canada often provide services such as healthcare, education and social care. Could these types of cooperative be more relevant for our networked and distributed age?

Michel Bauwens founder of the P2P Foundation talks about the creation of these new forms of cooperatives, and how it is necessary to wean ourselves off the notion of cooperativism as a means of participation in a capitalist economy, to one that builds a commons both material and immaterial. This commons would be subscribed to by other commons creating entities and licenced to non-commons creating organisations.

Would a data cooperative necessarily adopt these newer forms of distributed and commons creating structure? There appears to be a consensus that commons creating, multi-stakeholders cooperatives are positive, but is this model easily understood? And can individual circumstances especially when dealing with communities based around sensitive issues, create an environment for sharing beyond a single class? A single class cooperative may seem to be a simpler, immediate solution for a community of people who have specific needs and issues and where strong trust relationships need to be maintained.

It is understood that personal data empowerment is not just about selling data to the highest bidder and any organisation acting as a data intermediary would need to be able to accommodate the complexity of reasons as to why people donate or give. Even though economic gain might seem an obvious attraction for people, motivations are more complex and often financial incentives can be detrimental to the process of participation and giving.

From The Good Data’s perspective data cooperatives should split the data layer from the service layer. The cooperative should control the data layer and enable/choose others to build the service layer as it is likely that data cooperatives would not have the capacity or expertise to create end to end solutions.

The structure of the data cooperative should encourage maximum participation and consent, although 100% participation and engagement is unrealistic. Flat structures have a tendency towards hierarchy through operational efficiency and founder endeavour. Even though the majority of members align with the aims of the cooperative, it doesn’t necessarily mean that they want to be constantly encumbered with the burden of governance.

A certain pragmatism and sensitivity needs to be adopted to the model of cooperative that a group may want to adopt. There are examples of communities maintaining informality to enable themselves to be less burdened by expectation, to maintain independence or minimise liability. Advocates of data cooperatives need to be sensitive to this.

Purpose

Data Cooperatives need to have a simplicity of purpose. What do they do, for whom and why? Is the building of data cooperative around particular issue enough? Or do we need to take a look at the data cooperative as being a platform that allows the representation of personal data across a broader portfolio of interests?

Although the there is a tendency to see a data cooperative as being a mechanism to generate bulk, high worth data that can then be used to draw down value from large organisations, a more appropriate application might be in enabling a smaller community of interest, perhaps around a particular health condition, to draw down certain services or to negotiate for a better deal. The notion of withholding data from public service providers might be seen to be detrimental to the delivery of that service, but it could also create a more balanced decision making process. It is also known that many providers of service collect more data than they actually need for the delivery of that service. Empowering people to take more control over their data may create a situation where the practice of excessive data gathering is curtailed.

Data literacy

Ideally for a data cooperative to be most effective, the level of data literacy amongst members would need to be raised so that members could make more informed decisions about what data was given away or used. This ideal might be difficult to achieve without a broader awareness raising campaign about the power of personal data. The revealing of the ways that security agencies collect data by Edward Snowdon was sensational and although it highlighted that we unintentionally give away a lot, it didn’t build a wider popular discourse around protection and usage of personal data.

Raising the level of data awareness amongst cooperative members would create more informed decision making, but this task would need to be delivered in a nuanced way and ultimately some people might not engage. This could be the case with people who are dependant on service and have little power or real choice as to their decisions.

For a data cooperative to represent its membership and control the flow of data it needs to have legitimacy, know and understand the data assets of the membership, and have the authority to negotiate with those data assets on the members behalf.

Decisions around data sharing and understanding the potential consequences are difficult and complex. As an intermediary the cooperative would need to ensure that individual members were able to give informed consent. We have to know what we have and what it does for us, in order to utilise it.

Mechanisms of consent

There already exist mechanisms for the creation of consent. These by and large create the environment for proxy voting in decision making processes. A mechanism such as Liquid Feedback – popularised by the Pirate Parties, where an individual bestows voting rights to a proxy who aligns to their position, is a representative democracy process, the ‘liquid’ element allows proxy rights to be revoked at any point in the decision making process. Other mechanisms might follow along the lines of the Platform Preferences initiative developed by W3C, which sought to create privacy policies that could be understood by browsers which was ultimately considered too difficult to implement. A potentially easier solution might work on the basis of preset preferences based on trusted individuals or the creation of archetype or persona based preferences that people can select.

Can one organisation be representative of the broader range of ethical positions held within a membership structure? For practical reasons the data cooperative might have a high level ethical policy but individuals within the cooperative are empowered to make data sharing choices based on their personal ethical standpoint. This could be enabled by proxy or preset data sharing preferences.

The alternative to having data coops with high level ethical aims that also represent multiple ethical standpoints could be to have smaller federated or distributed niche organisations where individuals could allow the organisation to use their data on their behalf.

 Right to personal data

In order for an individual to allow an organisation to use data on their behalf we need to have control over our individual personal data. Legislation in many countries offers a framework about how personal data is used and shared amongst organisations, but these don’t necessarily create a mechanism that allows users to retrieve their data and use it for other purposes. Often within the End User License Agreement (EULA) or Terms of Service that come with software products an individual may find that their data is inexorably tied up with the function of the service. A function of a data cooperative might be to help individuals understand these agreements and add to the commons of knowledge about them.

How would the argument for greater individual data rights be made when service providers see that personal data mediated through their product part of their intellectual property? Work has been done through the midata initiative and the development of personal data passports – where individuals grant rights to organisations to use the data for delivery of service. UK Government has supported this initiative, but has backed away from underpinning the programme with changes in legislation. This lack of regulatory enforcement may limit the efficacy of any initiative that seeks to grant individuals’ rights and agency over their data.

The development of a personal data licence may aid the creation of data cooperatives but the form of the licence and the mechanism for compliance might be weakened without an underpinning regulatory framework. At present there is a certain level of cynicism around voluntary codes of practice where power imbalances exist between stakeholders. The lack of legislation might also create a chilling effect on the ability of data cooperatives to gain the trust of their membership.

Data empowerment is promoted in Project VRM (Vendor Relation Management) developed by Doc Searls at Harvard University. The ability for an individual to have control over their data is an integral component of developing an open market for personal data-based services and theoretically giving more choice. The criticism voiced about midata and Project VRM is that they are too individualistic and focus on economic rather than social transaction with ethical aims. Even with these criticisms the development of a market logic to enable large organisations to engage with the process of individual data empowerment might be beneficial for the long term aims of data cooperatives and for the development of innovative service for social good.

Ultimately if the individual isn’t able to have control over their data or the data derived from them then the function of the cooperative would be inhibited.

Creating value from data

It could emerge that scale could dictate the eventual form of the data cooperative. Many potential clients of a data cooperative might require this, which would see the need to build a data asset that contained upwards of 500,000 users. The Good Data cooperative’s aim is to achieve this scale to become viable.

A challenge that all data cooperatives would face would be how they maintain a relationship with their membership so that service based upon, or value that is extracted from the data is not subject to unforeseen supply-side problems. If a data cooperative represented its membership and entered into licensing relationships with third party organisations on behalf of its membership, what would be reasonable for a client to expect, especially if individual members had the rights to revoke access to data at anytime? With larger scale data cooperatives this may not be too much of a problem as scale has the potential to damp down unforeseen effects. The Good Data proposes to get around these issues by only holding data for a limited amount of time essentially minimising disruptions in data supply by creating a buffer.

Smaller scale data cooperatives, especially ones that are created around single issues may have difficulty in engaging in activity that requires service guarantees. Developing a mechanism for federation, cumulatively creating data at scale might be a potential solution, but creating a federated system of consent may be more difficult to achieve. As suggested previously economic activity might be a low priority for such organisations where the main purpose might be to represent members and create the environment for informed service decisions.

The challenge facing federated data cooperatives and how they interact is undefined. It has been noted that building distributed and federated systems is difficult, and that centralised systems persist due to operational efficiencies. The advent of alternative forms of ‘block chain’ transaction could enable distributed organisations to coexist using ‘rules based’ or algorithmic democracy. But alternative transaction systems and currencies often face challenges when they interface with dominant and established forms of currency and value.

How data cooperatives could practically use these new mechanisms for exchange needs to be explored.

Attendees:

Reuben Binns
Mark Braggins
Alex Fink
Steven Flower
Robin Gower
Frank Kresin
Marcos Menendez
Annemarie Naylor
Julian Tait
Kristof van Tomme
Ben Webb

Open : Data : Cooperation – OKFEST Fringe Meeting 16th July 2014

OKF DE Office
3rd Floor
Singerstraße 109
10179 Berlin
Map

Wednesday 16th July, 6 – 8pm

Please sign up on Eventbrite here as numbers are limited.

Join us for an informal discussion around data cooperatives.  From personal data co-operatives, through to organisation-level collaboration, there is a lot of interest around the notion of a data cooperative. Whilst the idea of member-owned organisations and open data seems logical, a number of interesting discussion points arise:

Models: How do the varied models of cooperative ownership fit to data?
Simplicity: Can one model fit all data?
Transparency: How can a cooperative that is steered by its membership along ethical grounds also be considered open?
Representation: Do individuals have enough control over their data to enable third party organisations such as a cooperative, to represent their data?
Negotiation: How can cooperative members balance control over their data with use by third parties?
Governance: How would you create an efficient system of governance that respected the wishes of all members?

Open Data Manchester will be hosting an informal discussion around these issues in a fringe meeting at OK Festival in Berlin on Wednesday 16th July at 6pm 3rd Floor Singerstraße 109, 10179 Berlin. https://goo.gl/maps/q4Gvj

The meeting will is a precursor to a larger event around cooperatives and data to be hosted in Manchester, UK at the end of October

Further reading:
Annmarie Naylor – Common Futures
http://commonfutures.eu/developing-data-coops-for-community-benefit/
Julian Tait – Open Data Manchester
http://littlestarmedia.wordpress.com/2014/06/20/data-custodianship-and-cooperatives/

Open Data Manchester – May Edition

Tuesday 28th May

6.30 -8.30pm

MadLab, 36 – 40 Edge Street, Manchester M4 1HN

Sign up on Eventbrite here

As well as the usual opportunity to show people what we’ve all been up to, this month is a chance to catch up with other open data developments within Greater Manchester.

DataGM is due to be relaunched after a long development hiatus. When launched it will be an instance of the latest CKAN. One of the Trafford open data team will be here to talk it through and how you can get involved in the new fresh DataGM. For those that want a sneak preview you can find it here. NB this only has a few test datasets on it: http://datagm2.ckanhosted.com/

For the classic DataGM experience you can find it here: http://www.datagm.org.uk

We will get an update from Farida Vis and Steven Flower as to the first outings of the mapping for food growing walks that aim to uncover unused green space that could be used for growing food. This month saw two expeditions in Trafford. Further information can be found on the  Everyday Growing Cultures project website http://everydaygrowingcultures.org/

The Shakespeare Review was released last week https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/198752/13-744-shakespeare-review-of-public-sector-information.pdf
The review explores the growth opportunities of, and how to widen access to, the wealth of information held by the public sector. We will look at the recommendations that it makes to Government

For those that were around for the Innovation Challenge in March you will be aware of the development of CitySDK API. The logic behind it’s development is that it uses Open Street Map as a base layer in which other data is mapped over it. As it is being implemented by a number of European Cities it should theoretically make it easier to port applications across them thus increasing market. We should have the final specification.

There will also be an update on funding out there for your projects open data and otherwise.

If you have anything that you want to add just let us know, ODM is open and for everyone.

ODM Footer 600px

Developing the UK’s Open Government Action Plan

Wednesday 20th March 14:00-16:00. Four Piccadilly Place, Manchester M1 3BN

The UK is a founding member of the Open Government Partnership (OGP), a global effort to make governments better by promoting transparency, empowering citizens, fighting corruption, and harnessing new technologies to strengthen governance.

Work has already begun over the past five months on developing the action plan, with the Cabinet Office and a network of (mostly nationally and internationally focused) civil society organisations working together to develop a set of commitments. Together, these commitments will make government and other powerful institutions more transparent (including through opening up data), enable greater citizen participation in policymaking, improve the responsiveness of government, better public service delivery and enhance the accountability systems that, among other things, reveal and prevent corruption in public and private organisations.

The UK Government is working in collaboration with a network of civil society organisations to develop an open government plan with a set of concrete open government commitments.

We need your help to develop it further – telling us what’s missing, what works and what’s needed at a local level, and if/how you’d like to be involved in developing it in the coming months.

To sign up and for more information click here

Co-operating on Open Data

The new co-op HQ
The view of the new Co-op HQ from the 24th floor…

This week, way up on the 24th floor of the CIS Building in Manchester, we facilitated an event to look at how and why the Co-operative movement could engage with open data.

Alongside Co-operatives UK and The Co-operative News, a group of open data and co-op people gathered to hear from Chris Taggart of OpenCorporates, and then begin the discussion of how this movement could evolve.

We learnt that the Co-operative movement is vast and diverse – ranging from banking to funeral care, from software to snake catchers!  Equally, there is not *one* type of co-op. Variations such as worker, consumer, retail and volunteer co-operatives are just some – although all share the same ethos and relation to the guiding principles of mutal benefit for members and wider society.

Chris took us through some of the philosophical and practical issues around open data, summized in the classic line:

“Open data is the new democracy”

.. which certainly got people thinking.

I’ve picked up on two main themes that stood out from the workshop.  The Co-operative News have ably started to document and publish materials from the workshop – well worth a look.

1 – Open Data on Co-operatives

This was our starting point.  If co-ops were to openly publish data about their activities, what would represent their “added value” and “point of difference”.  Would this be data on membership, community activities and other measures? How would this be achieved?  What could be the “quick-win” datasets that co-ops could push out to engage people?

We discussed how an data standard for co-operatives could be one way to facilitate this – but this event was only two hours…

2 – Open Data by Co-operatives

This theme was something that struck to the heart if many it seemed.  One of the key values of the co-operative movement was knowing how to run successful businesses and organsations in a collaborative manner.  How could this be applied to open data?  Could open data projects be governed in a co-operative way?   There was some discussion around the notion of “prosumer co-operatives” in terms of data producers and consumers working in joint.  Certainly, there was an appetite for exploring this further…

What Next?

Open Data Manchester were proud to be a part of kicking off this discussion, and many thanks to all those that attended, and our collaborators at Co-operatives UK and The Co-operative News.  This October/November, the co-op world will arrive in Manchester to celebrate the end of the United Nations International Year of Co-operatives.

Please add your thoughts on how we can further stimulate the conversation in the run-up and during this event…