The development of open data infrastructures, knowledge co-creation platforms, wireless sensor networks, decentralized social networking,
In the DSI Network Data-Set, there are a total of 285 organisations with a total of 178 activities as of 13 december 2013.
the biggest open source data platform in Europe that is underpinning a new bottom up ecosystem for digital public services;(
and analysing real-time environmental data, and Safecast a project that enables citizens to capture and share measurement on radiation levels;(
and Santander pioneering new practices in Open Data and open sensor networks; and mesh networks projects such as Guifi. net, projects such as Confine, Commotion,
and Tor that are using bottom up privacy-preserving decentralised infrastructure for the open Internet constituted by open standards, open data, free and open software,
open hardware and open data infrastructures. The selected organizations have been classified into four types: Different typology of organisations (e g.
The main technological trends the organisations and their activities fit under (open data, open networks, open knowledge, open hardware;
including the types of technologies underpinning DSI services that combine novel technology trends such as distributed networks, knowledge co-production platforms, open data, open hardware, open content,
and merging novel technology trends such as open data, crowd-mapping, open hardware, open distributed networking,
The development of open data infrastructures, knowledge co-creation platforms, wireless sensor networks, and open hardware, can potentially serve collective action and awareness.
as apps need access to social data held on third-party sites. The lack of standards forces developers to create multiple versions of the same social application for different closed platforms,
and patents, appropriating users data, and discriminating network traffic. By centralising computing, data storage and service provision (via the Cloud),
The development of open data infrastructures and citizens-controlled wireless sensor networks, and the long-awaited deployment of the semantic web, can potentially serve collective action and awareness.
Honest competition based on open standards, protocols and formats are essential to deploy interoperability between data, devices, services and networks.
The tools of collective intelligence include new technologies for sharing data and knowledge, such as crowdsourcing platforms,
They include analytical tools that allow vast amounts of complex data often from different sources, to be mined and understood.
Innovations, such as those which draw on the expertise of data scientists around the world to develop algorithms to solve large-scale problems,
In this way, the Internet offers unprecedented opportunities for collective intelligence via its increasing ubiquity and its massive amounts of data available for collective transformation into knowledge.
a process where people collectively identified their own high-carbon intensive behavior via data-collection and visualisation,
and Settingsframing the Research Questionsour research starting point proposes that democratized ICT and open digital infrastructures, data,
and use of their data and contents. This research will look into the type of regulations that can strengthen enabling frameworks for free
and data, such as enhancing public domain and making digital contents and information more accessible and reusable by all citizens.
At a socioeconomic level the study will assess new business models and socioeconomic mechanisms‘beyond GDP',based on the valorisation of social data and common information resources for collective use and public benefit beyond monetisation
together with quantitative analysis underpinned by open data gathered though a generative European-wide survey. This mixed methodology was selected because of the exploratory nature of the study.
whose goal is to understand current and complex social phenomena in real life settings, gathering tick data and asking the‘‘how''and‘‘why''questions (Yin 1994.
or experiment with innovative combinations of the selected technology trends (open data, open source and open hardware developments), leveraging social networks (or distributed social networking, sensor networks and the Internet of things,
for individual and collective awareness, relying on collaboration and or aggregation between users and/or their data.
the main technological trends the organisations and their activities fit under (open data, open networks, open knowledge, open hardware;
All data captured about organisations and organisational relationships is made available as an open data set on the website for users to download
and investigate, just as any custom code developed in the course of developing the Website, Database and Dynamic Visualisations will be shared back with the relevant open source communities.
Open data about the mapping of organisations include: Geographic map featuring filters that can be manipulated to reveal information trends
embeddable data visualisations to demonstrate key features of DSI in Europe 19 Data collection To enable the mapping of organisations
and their activities we considered three different methods with which we could capture the relevant organisational data.
Through an early assessment of the three options it became clear that capturing data through a survey would be preferred the option,
as the other two options would not result in good data. Existing datasets such as the Social Innovation Exchange (SIX) membership database, had issues with typologies,
Similar challenges arose around the possibility of scraping data in addition to a number of technical, validation and provenance issues surrounding scraped data.
Since this field of practice is unexplored relatively, there is a lack of relevant existing data to help in the mapping process.
The dynamic mapping tool will, however, have the functionality to integrate existing or scraped data should this become relevant for future iterations of the mapping.
Mapping networks through a Generative Survey (ENDNODE) The data captured and its structure determines the mapping capabilities of the website.
Therefore the survey has been designed so that it captures the relevant data needed to understand the different types of DSI organisations and their activities.
It also includes a generative function which is needed in order to capture relational (network) data. The survey has been broken down in to three sections:
Capturing organisational data Capturing data about projects and activities Capturing data about networks and relations between organisations.
First phase: The first section‘Put Yourself on the Map'asks organisations a short series of questions to self-identify as a DSI organisation,
and provide information on geographical location, size and type of organisation (e g. government and public sector, business, academia and research, social enterprise, charity or foundation,
The data on organisational attributes will generate a dot on the geographical map. Second phase:
Networks between organisations and relational data will be determined through mapping the DSI activities that the different organisations collaborate on. 20 Third phase:
These were asked then to enter data regarding their organisation and to enter information regarding partners who have worked with them on projects.
A digest email encourages users to complete any missing data in respect of this. Therefore, any organisation can exist on the map
Data visualisationto understand the DSI landscape in Europe the mapping and visualisation takes three main forms:
and work on the open survey data set. The mapping and visualisations are designed around the data that is acquired through the processes listed above.
The proposed approach to mapping and visualisation exploits the flexibility of linked data. All data points will have their own URIS that will allow mapping to Open Street Map objects.
Effectively, different types of data can be layered on top of these URIS to create a more robust and extensible database.
The diagram above reflects this approach with an Open Street Map base layer with actor location data, network relationships,
communication density and user generated data applied. Currently the website is focused on the geographic mapping of organisations.
Over the next stage of the DSI report, various info-graphics that highlight important aspects of the data will be added. 22 Chapter 3-Defining DSI Interim Findings An emerging typology
of the DSI field: Clustering organisations and activities Digital Social Innovation is a relatively new field of study,
uses the beta data to show how the generative element of the survey has begun to create initial links across the organisations to reveal networks both within Europe
or linking currencies to data. 25 2. New ways of making A vibrant ecosystem of makers is developing across Europe and globally.
and tools to enable collaborative communities to undertake large scale projects that can lead to innovative results in open business, open government or open data.
DIY culture, open source software and open data. Projects like Safecast or open source Geiger, the Smart Citizen Kit,
Technological driven developments such as sensor networks and open data connected with a sustainable user-centric design can support organisations and individuals in addressing challenges of the future. 3. Participatory mechanisms, feedback,
the biggest repository of open data in Europe that is underpinning a new bottom-up ecosystem for digital public services.
businesses and society by pioneering new practices in open data and open sensor networks that are changing the provision and delivery of public services;
and communities are beginning to aggregate the layers of data that increasingly permeate the urban environment
and Digital Commonsmany activities in this area exploit the power of Open Data, Open APIS, and Citizens Science such as Open Data Challenge and Open Cities that provide citizens better public services,
wile Citysdk is defining interoperable interfaces for city-scale applications. Other projects are exploring the potential of federated social networking
and Tor are using bottom-up privacy-preserving decentralised infrastructure for the open Internet constituted by open standards, open data, free and open software,
culture & education Smart public services Open Networks Confine Opengarden. net Everyaware Commons 4eu Tor project Make sense Freecoin Smart Santander Open Data Wikiprogress Open Corporates
and public sector organisationsproviding funding for experiments/R&dproviding nonfinancial resources (i e. opening up public data sets) Delivering
Data and access to data is the fuel that drives much digital social innovation. Through opening up and sharing public data sets national and local government have enabled citizens
and organisations to create public good services that were not previously in place. The work by the local government in Vienna on Open Government Data Vienna led to citizens developing a raft of innovations,
such as the Fruitfly, a map of public fruit trees with free fruit across the city. The partnership between the not-for-profit Praxis and the Estonian Government on opening up and visualising government budget data, created more transparency around public spending. 30 SMESFROM small start-ups to larger companies,
innovative companies play a big role in pioneering new practices delivering DSI services that enable users
and the health data they create, and the organisation behind Github, the collaborative service for open software writers.
one of the most widely used open-source data portal platforms is an example of a not-for-profit providing a service that enables more DSI to happen by making it easier for large institutions to open up their data.
it is possible to capture data by filtered the DSI map by‘Activity type'.'The full distribution across the 289 activities noted on the map is registered in the Table below:
If we analyse these data based on all 289 organisations, and looking at in the light of the case study work,
The Open Data Institute's ODI start-up programme which has supported organisations like Open Corporate and Provenance to grow their Open Data projects,
is another. Although incubators and accelerators have been always around, their presence in aiming to address social challenges has been limited rather to date. 33 Traditional business accelerators offer advice
for digital fabrication and hacking data that entrepreneurs can access freely. There are now 96 known active hacker spaces worldwide, with 29 in the United states, according to Hackerspaces. org.
'or the Open Data Institutes (UK) open data training sessions for charities. Real empowerment through access to knowledge and education happens
'This grouping is based on the classification towards creating a data-driven Ecology suggested by MIT (Bollier and Clippinger 2013:
, p2p infrastructures Tor Confine Guifi. net Smart Santander Open Data innovative ways to capture, use, analyse,
and interpret open data coming from people and from the environment Open Vienna City SDK Open knowledge co-production of new knowledge and crowd mobilisation based on open content,
and on Open Data to share and analyse the data captured across all of the Geiger counters.
Figure 10the chart above shows the‘Tech focus'of those on the DSI map to date.
and to pass their data through the network to a single or replicated data-processing location.
and stored as it uses public data from different sensors and forwards the gathered information to the central point within a wireless environment.
They are key infrastructures of a smart city by providing basic data on the usage of energy, pollution, geodata, traffic, geography & meteorological, tourism and so on.
which would be fed by Open Data from the OSN. A number of European cities have established sensors that detect traffic density
in order to provide external parties a single point to consume this data. Community networking (also known as bottom-up networking) is an emerging model for the Future Internet across Europe and beyond,
Open Data The explosion of new types of data analytics and machine learning means that it is no longer only government
and analyse data. By making data open, governments and other large organisations and companies that hold or generate data about society have the opportunity to enable citizens to hold government to account for
what it spends, the contracts it gives and the assets it holds. When the European commission published its Directive on the reuse of public sector information (PSI) in 2003 many member states,
and implement open data policies. The directive provided an EU-wide framework for governments at all levels, to begin opening data.
The European commission estimates the economic value of the PSI market at approximately €40 billion per annum. The 2013 revision of the European commission Directive on the reuse of public sector information will further enable the opening of public sector data in a harmonised and more transparent way,
and create the conditions for generating value, both economic and social, from this data. Local authorities are playing a leading role in implementing open data policies
and driving forward the open data movement. The social benefits of open government vary from citizen engagement to increased transparency and accountability
as well as enhanced interaction between governments, other institutions, and the public. Open data (both static or available in real time) favours the transformation of city authorities into ecosystem orchestrators that are able to shape
and foster the innovation process, whilst engaging all key stakeholders and delivering public goods, maximising returns for all citizens.
For instance, citizens are gaining greater insight into how their tax payments are being spent. Furthermore, citizens can create more knowledge in a distributed way,
Beyond the social aspects, open data also supports public sector innovation by breaking the competitive advantage gained by proprietary access to data
and data lock in. Innovation is most likely to occur when data is available online in open, structured,
computer-friendly formats for anyone to download, use, and analyse, as long as the privacy and data protection of all citizens is preserved
Thus, open data, together with open and standardised APIS is crucial for innovation, as developers are able to access
and use public data and mesh it with other sources of data produced by the crowd to build novel applications that have a social utility and produce public good.
For instance, with its Open Data in Vienna programme the city of Vienna has demonstrated the potential in opening up its data.
The city opened its data records to the population businesses and the scientific community. Released data ranges from statistics and geographic data on traffic
and transport to economic figures. It then invited programmers and developers to make apps and web services based on the data,
which to date have resulted in more than 60 applications for citizens. Other pioneering examples include the work by the Estonian Government and the not for profit Praxis on the Meiraha project,
which focuses on opening up and visualising the Estonian budget. The Citizen Science project Globe at Night is yet another example of this,
thereby effectively coupling open data and citizen science. The movement for more and better open data has grown significantly over the last few years through projects funded by the European commission, such as City SDK.
This is a European consortium of partners helping cities to standardize their interfaces so that services can be integrated into the City's backend system
boosting the diffusion of open data is the Mobile Internet and the increasing number of mobile devices.
mobile devices are generating ever-larger streams of personal behavioural data that have many potentially valuable public, personal and commercial uses.
Data-flows are also burgeoning as the Internet of things integrates a vast universe of network aware sensors, actuators, video cameras,
and the smart city that coordinates mobile cellular and GPS data to dynamically allocate resources and direct traffic.
and measure data about real-world activity. These data streams can be location reports from objects, people and cars,
This smart infrastructure is also increasingly getting to know people by aggregating personal and social data in massive data centres with little privacy and security.
and that promotes Internet as a fundamental channel for allowing an increasingly active role of users (individuals, groups, communities) as providers of data, content,
Analysing network data: Exploring DSI Network effectin order to analyse the relationship data from the mapping,
we are adopting social network analysis to detect patterns of relations, arguing that causation is located in the social structure.
Currently, as we are still collecting data, it would be premature to do a conclusive data-driven analysis. However,
in this section we explain the methodology. 41 The emergent network represents DSI organisations and their social relationships mapped in the form of graph that is a collection of nodes
One of the primary problems facing the mapping of an open-ended field such as DSI is how to direct the multiple diverse streams of data from interviews to social media into a central repository capable of giving a big picture of European
Through our approach of mixing open data analytics with human-centric interviews/case-studies we can better understand complex phenomena and socioeconomic and environmental trends,
and if the data-set is currently able to answer those questions. The network of concepts that determines the kinds of questions is the theoretical framework.
Only with such a framework can data and hypotheses be interpreted in a sensible manner without projecting preconceived,
and often wrong, opinions onto the data-set. Phrasing both the null hypothesis and alternative hypotheses in terms of network theory must be done with care.
There must then be enough data to adequately test the hypotheses, using mathematical techniques that can statistically quantify the level of confidence in the proof of the data for any given hypothesis. In particular,
this requires significance testing, as network-based data often assumes a non-Gaussian distribution such as a power-law.
For non-Gaussian distributions such as power-laws, traditional t-tests against Gaussian distributions and even traditional statistics around averages and means are scientifically invalid.
and everyone else being between 5 and 6 feet tall. 42 In the DSI Network Data-Set,
However, a snapshot of the data on the 1st of December indicated we have 243 organisations and 146 activities.
For any two parametric models that embody a hypothesis over our empirical data, the model with the larger likelihood fit is the better model,
when both likelihoods are given by maximum likelihood fitting of distributions representing hypotheses to the empirical data.
different hypotheses (H')could be tested over different data-sets and compared (N'as opposed to N in the denominator).
How much data is given necessary, (N we are assuming a non-Gaussian distribution, to do the network analysis? Using our current data from the survey,
we can run the above algorithms on it to determine if the data is sufficient. The MATLAB code developed by Aaron Clauset at the Santa fe Institute was used (http://tuvalu. santafe. edu/aaronc/powerlaws/.
/The results were, at this stage, not significant for the fitting of the proposed nonparametric power-law.
The harder question is the proper value of N. This can be estimated by simulating data distributions with a large enough N from two different distributions (in this case,
a power-law versus a log-normal) that would then be matched against the Monte carlo data and likelihood rations.
what amount of data is necessary and what likelihood ratios match with p<.1. For our simulation,
This is because distributions such as the log-normal and exponential distribution are difficult to differentiate from power-laws due to the difficulty in proving the existence of the long tail with small data-samples. 43 2
If the data-set is of reasonable size (less than 10,000 organisations) we will use the Newman algorithm to identify communities.
While we have let the organisations label themselves around predefined categories like Open Data and Open Knowledge,
New clustering and categories will then emerge from the empirical data. Within each community, there will be certain organisations that have a high centrality, the movers and shakers of social innovation.
However, currently this analysis is difficult to do as we have revealed that there is either a problem with the scarcity of data
or it may just be disconnected a highly network more data is needed to find out, since we are at the very early stage of engaging DSI communities. 4
In general, before beginning rigorous network analysis (1) we must collect more data and that (2) our hypotheses will have to be quite broad
This means for the second phase of the report we need approximately double the data we gathered in the first phase, if not more.
if we are comparing hypotheses involving (possible mutually exclusive) different kinds of subsets of the network data, such as comparing two different kinds of communities (such as Italian vs. non-Italian organisations
and in fact, private institutions have near-monopolies over social networks and search engine data, giving them nearly exclusive access to the data
and algorithms needed for innovative digital research. Yet, perhaps surprising, even as these digitally native companies are reaching the state of
Open data such as the Open data Vienna initiative allow for citizens to mine previously closed sources of knowledge for problems and new opportunities.
Digital means that any data exist in binary form and in standardised formats so that can be aggregated
Digital innovation today focuses mainly on data mash-up process, which synthesize new information by connecting,
The challenge of balancing quality and quantity within the data set is an aspect that we are constantly monitoring
Lastly, Task 2. 5 will create infographics based on the data that can help visualize the most salient results of the survey.
-What kind of projects (type of DSI activity)- Basic taxonomy by technology trends (open data, open knowledge, open networks,
and relational data 2. Mapping Resources and Founding for DSI in Europe 3. Promoting & Socialising main activities, events,
public funding) and investors Future development tasks Code and data Full information on the development so far and open source code can be found on the Github page here:
All public data is stored in a Fuseki triple store, and accessed via the ORM-like Tripod API.
All private data is stored in Mongodb. The current homepage visualization has been created using Openstreetmaps. Access to the Open Linked Data is provided in multiple formats:
http://data. digitalsocial. eu/data. The following list is a priority list for future development:
Improve the UI Allow organisations entering data to self-tag descriptions of their organisations/activities
and for these to feed into a Tag cloud navigation UI Add another Taxonomy, allowing to brows
In this manner, the website would become not only a data source but also a kind of learning tool to understand what digital social innovation concretely means.
Create better visualisation with the current relational data that can be exported (see here an example of the current visualisations) Better internal search system Addition of social network functionalities to the DSI mapping,
As the platform matures, data and information can be validated by the community through recommendation and reputation mechanisms.
Exploring the potential of different mechanisms such as open data, crowdsourcing/crowdfunding, Living Labs, etc. and comparing these to more traditional approaches.
one of these Arduino@Heart is the Smart Citizen Kit a hardware kit to gather environmental data,
in spite of giving away all the data required to build Arduinos completely free. Some commentators have gone further to suggest that Arduino has circuited also short most conventional industrial infrastructure by‘placing the ability to create wealth directly in the hands of private individuals.'
and in general, for systematic measurements and internationally comparable data. These would enable better assessment of the long-term importance of Social Computing trends in terms of their socioeconomic impact,
comparative data would enable researchers to identify which regions have had greater successes through e-petitions,
Open Network, Open Data, Open Hardware, Open Knowledge DSI activities: A Network Key facts: Citysdk consist of 23 partners, 9 countries, 3 open source APIS Website:
to open data, while giving developers the tools they need to develop applications that scale.
and was set up with the purpose of helping cities to open their data and giving developers the tools they need,
With governments around the world looking at open data as a kick start for their economies,
Citysdk aims to provide better and easier ways for the cities throughout Europe to release their data in a format that is easy for the developers to reuse. 74 Taking the best practices around the world the project will foresee the development of a toolkit Citysdk
along with links to the open data from the various partner cities, and developers will be encouraged to work with this to create new ideas and applications for the partner cities and others.
Creating a European-wide market for tourism applications based on Open Data made available by public or private entities.
and products using open data. It fosters and facilitates international knowledge sharing around the best practices,
Another is the Open Data Globe showing the dynamics of European cities based on the available open data.
There are several applications related to mobility, such as the Greater manchester Realtime Scheduling application, the Park Shark City Platform and the City Navigator, a fully Open source, mobile HTML5 public transport journey planner and navigation application for on the go-go use.
disseminate knowledge and data. Open source Software, which enables the uptake and extension of the software by the development community forgoing stifling discussions on IP and closed development silos Open Data,
as it builds software to publish Linked Open Data in standardised formats that enables app developers to make royalty-free applications that scale Open API's,
that provide a nonproprietary way for data-owners to publish (real-time) datasets use those in applications Agile Software Development, by way of SCRUM tools and methodologies Next to these,
standards are used like GTFS (General Transit Feed Specification) and Open 311, and languages like JSON and RDF API's written in Ruby and Sinatra.
Data stored in Postgresql/Postgis database. Collaboration using digital technologies is done mainly using e-mail, video conferences and Google docs for communication and Github to share code and specifications.
The Open Data policies implemented by the EU and individual countries facilitate the building of Citysdk as well as its rapid spreading and uptake.
DSI network effect Through the apps and services it is developing Citysdk aim is to build smart services where user generated data make up the core activity of the service.
or incapable of opening high quality data that is in high demand, e g..real-time traffic data. Governments and civil servants demand results too quickly.
It takes perseverance as well as investment in time, money and relationships before good outcomes happen. Business cases for implementing the resulting API's are currently missing;
instilling goodwill and overcoming barriers regarding opening data, implementing API's and working with the local development community.
A lot of effort is spent is connecting data owners, technicians and domain experts. This pays off in the end.
It turns out this actually works well for the development community and data owners alike.
Open Data; Open Networks; Open source DSI activities: Operating a DSI service, Network Key facts: As part of the project the consortia developed Europe commons, a catalogue of applications with demonstrable impact Website:
It simultaneously taps into current technological trends such as open data, open source, as well as digital volunteerism (crowdsourcing), in a way that has a clear social impact.
Open government data and public sector information: COMMUNIA policy paper on the proposal to amend the European Directive on reuse of Public sector Information;
Open access to scientific publications and open scientific data: COMMUNIA Position on EC Horizon 2020 Open Access policy;
Therefore, the project also wants to generate open data sets for research that will allow for outside participation and research collaboration,
Actually, the open data efforts will be focused more on the Future Internet context of CONFINE rather than the test bed itself.
This central catalog points to open data available from the different CONFINE partners With CKAN,
while maintaining the privacy of their data and the data they relay. This leads to different threat models and a new notion of trust between users.
What helps to reach goals and overcome barriers? Community networks are an emerging eld to provide citizens with connectivity in a sustainable and distributed manner in which the owners of the networks are the users themselves.
Open Networks, Open Data, Open Knowledge DSI activities: An event, A network, Running/hosting maker spaces
Open networks, Open data, Open knowledge, Open hardware DSI activities: Research project, network, operating web service providing education & training Key facts:
The project does this by providing capabilities for environmental monitoring, data aggregation, and information presentation to users by means of mobile and web-based devices such as smartphones, computers and sensors.
which Everyaware refers to as‘subjective data'.'It pairs this with‘objective environmental data'from sources such as static sensors.
The aim of this is to undertake a comparison between sensor data and subjective opinions which will expose the mechanisms by which the individual perception of a known phenomenon is translated into its social perception and eventually into choices and actions.
A central server efficiently collects, analyses and visualises data sent from arbitrary sources. The Everyaware platform will handle both sensor and subjective data acquisition.
It will host a modular system based on two hardware components: a smartphone controlling the data acquisition and a modular sensor box with several pluggable sensors.
This approach guarantees high scalability of the overall system and allows for an optimal distribution of sensors (e g.,
, wearable sensors for air or noise pollution. At the same time, web-interfaces allow users to easily upload their sensor readings,
storing and analysing relevant environmental data. Case studies: Case studies concerning different numbers of participants will test the scalability of the platform,
which shows the collected data and indicates the noise pollution levels all over the world. At the same time Widenoise also visualises the data to explain to users in a more accessible manner how they might gain a deeper understanding of the problem.
Sensorbox, Airprobe, a dedicated Web server and Web application, together form a system that measures concentrations of pollutants in the air and localises them through a GPS.
and also makes it possible for users to access the aggregate data gathered by the community,
which allow effective data and opinion collection, and real-time information spreading processes. In addition, theoretical and modelling tools developed by physicists,
interpret and visualize complex data sets. The integration of participatory sensing with the monitoring of subjective opinions is novel and crucial,
which the local perception of an environmental issue, corroborated by quantitative data, evolves into socially shared opinions, eventually driving behavioural changes.
Generating data and sharing opinion in a user-friendly manner: The combination of sensor-based data generation and online sharing provides the possibility of gathering opinions in a user-friendly manner.
Sensor-based gathering of temperature and noise-level information, for example, allows collection of data on totally new levels of scale.
Use of mobile phones for this purpose seems a particularly powerful way of getting ordinary people involved,
as it could integrate subjective data (such as moods or opinions) as well as scientific readings. It is possible to make more sense of the collected data
when they are displayed over a base map of the local streets either via GPS readings or by captures through a map interface. 103 Raising awareness and effecting decision and policy making:
This focuses on the question of whether‘socially accepted'data gathered in this way could induce widespread opinion dynamics leading to changes in behaviour.
The appropriate and personalised representation of the collected data to users has the potential of triggering a bottom-up improvement of citizens'behaviours.
The comparison between sensor data and subjective opinions aims to expose the mechanisms by which the individual perception of a known phenomenon is translated into its social perception and eventually into more informed choices and actions.
It will be a resource for capturing new types of data across EU. 104 105 Fablab Amsterdam At a glance:
a platform set up with the aim of helping governments become more open source, open data, and open government.
relies on open data. How is funded the organisation? The Spanish Minister of Culture has helped co-fund (amount unclear) the early development of the Platform.
Open data; Open knowledge DSI activities: Advocating and campaigning; Operating a web service Key facts:
MAPIT-Mapit Global's API uses Openstreetmap data to‘establish the location of different administrative boundaries, anywhere in the world.'
'Boundaries data is essential for anyone creating geographic web and mobile services that rely on locating a particular point within the correct country, district, county, city or region.
One of the candidates running for President in the 2013 Kenyan Election contacted the site personally to query the data behind their scorecard rating. mysociety emphasize the fact that,
Open networks, Open data DSI activities: Operating a web service Key facts: has released 160 datasets
In simpler terms the Open Government Vienna project has seen the city adopt an open data policy and share data related to population, economics and science.
Relevant data also comes from around the areas of statistics, geospatial, transportation and economics. This shift to transparency
History and Mission The Open Government initiative of the City of Vienna started in May 2011 with opening up datasets on data. wien. gv. at.
Furthermore the data and spin-off apps that come about as a result of the Open Government Data strategy are hoped to have positive impact on citizen engagement and participation;
business and research; and administration in the city of Vienna. 144 What does it do,
and development coming out from the open data generated to deal with the particular needs of citizens in the city,
One particularly novel application that has been created is Fruit fly an app that offers users a visual map that captures data on all fruit trees on public ground in Vienna.
Crowdsourced data is used also to index which fruit is ripe or in season. The result is a quirky app that citizens
In opening its data records to the public, the City of Vienna is taking an important step towards implementing its Open Government Strategy.
A summary of the city's Open Government activities and the first edition of the Open Data catalogue are available online,
Presently 109 apps and visualisations have been made that make use of Open Government Data Vienna, and the community of over 500 users is made up by a diverse demographic of students,
and government organisations that bring forward the most important improvements with regards to technological and strategic issues in the field of Linked Open Government Data (such as strategy forms and consultation).
The Open Government Vienna initiative has clearly been influenced heavily by recent technology trends around open data and open networks.
In addition to this, the City of Vienna launched an Open Data portal and an Open Government Portal in 2011.
and for the first time the aggregated data has been made open to the public as an Open Data Catalogue. Lastly 109 apps and visualisations were created by the community, some
'Open Government Implementation Model'suggests that a‘focused look at public sector data management has been missing so far In public Management
'and that‘a control gap has become evident due to the trend toward the release of data in Open Government Data Portals.'
'It also concedes that the Open Government Data Implementation Model‘is a contribution toward closing this gap'by producing‘data catalogues,
implementing evaluations in the context of internal data monitoring and the planning and implementation of approval cycles in the first stage of Open Government constitute a contribution to Data Management and Data Governance as new disciplines of Public Management.'
'Yet advances in public management of this sort would doubtlessly be impossible without the improvements in computing storage and high levels of Internet penetration.
Data quality: data management tools like CKAN are necessary to build up a range of datasets that are of a high standard,
and that can in turn generate useful cross-referenceable findings. Data islands: transferring data over from older devices posed a challenge for the Open Government's push for open data.
What really helps to achieve goals? Political buy in: the scope and breadth of what Open Government Vienna has achieved would not have been had possible the city authority not voted to make open data a major priority focus.
How to achieve better European collaboration? The model implemented in the Open Government Vienna initiative has already been used by other Authorities in Austria (e g.
Environment Agency Austria, small municipality of Engerwitzdorf, City of Graz, Region of Styria and others.
according to data released by the International Telecommunications Union in June 2012) more needs to be done to understand some of the potential barriers that might exist
Open networks, Open data, Open Knowledge DSI activities: Operating a web service Key facts: Created open data sets with more than 60 million companies registered Website:
http://opencorporates. com/Organisation Name Opencorporates Short description Opencorporates is the largest open database of companies in the world.
which shares data on corporate entities as open data under the share-alike attribution Open Database Licence.
It aims at creating a URL with such data for every corporate entity in the world,
as well as importing government data relating to companies and matching it to specific companies. The site also shows groups of companies that are legally part of the same conglomerate,
Basic company information is available as open data in XML or JSON format. Today the site has grown from 3 territories and a few million companies to over 75 jurisdictions and 60 million companies,
and is working with the open data community to add more each week. Type of organisation Opencorporates is a for-profit company, based in the UK.
Opencorporates seeks to do this through opening up data and providing tools for analysing it. To do this, Opencorporates is
and an open data community, to make the open information sharing more open, and thus effective.
The core business of Opencorporates is to collect data on companies through web scraping tools
and then visualize the data. Web scraping data: The main activity within Opencorporates is to collaborate with Scraperwiki,
a platform for doing data science on the web, to help get the company data. The basics that are needed
in order to create a company record at Opencorporates are the company number, the jurisdiction and the company's name.
if there is not standard data available for this already. The Opencorporates database has been built by the open data community, under a bounty scheme in conjunction with Scraperwiki,
by offering a small fee for new jurisdictions opened up (explained in more detail below).
Web scraping (web harvesting or web data extraction) is a computer software technique of extracting information from websites.
in order to encourage people around the world helping them open up data sets. It offered £100 for any jurisdiction that had not yet been done and £250 for those territories that Opencorporates saw as a priority (such as Australia, France, Spain.
and neither the code nor the data will belong to Opencorporates, but to the open data community.
Data visualisation: The main output from Opencorporates work on capturing data is searchable maps and visualisations of complex corporate structures with multiple layers of control below the headquarter of the organisation and it in some cases thousands of subsidiaries.
One example of this is how Opencorporates visualised the complex corporate structure of Goldman sachs's based on data from public filings and company registrations in the U s.,New zealand, the Cayman islands, Luxembourg and the UK.
This helped visualise how Goldman has 1, 475 subsidiaries registered in the U s. and 739 in the Caymans alone.
That's the sort of thing you could have done as an academic study based on this data, but maybe half a dozen people would have read it.
and a number of other people in the open data community had around access to data,
since its inception been lauded for its work on opening up data. In 2011 it won the 3rd prize in the EU funded open data challenge
and was recognised by the vice president of the European commission, Neelie Kroos as‘the kind of resource the (Digital) Single Market needs'.
Getting and Returning Data Making open data more open: Opencorporates inspires a social sharing concept to people who want to get data from it.
All Opencorporate's data where the company has the right to share it, is made openly available under the share-alike attribution Open Database Licence.
In return, any product of that data must also be open for others to use. For organisations that don't want to give back data,
they pay Opencorporates a fee. Innovating data driven journalism: As part of the development of their offer Opencorporates is making a new open database of corporate officers and directors available to the world.
This will enable journalists to be able to search not just all the companies with directors for a given name in a given state,
but across multiple states. What it the role of the organisation within the DSI ecosystem?
Open data: Open data sit at the core of all Opencorporates work. This is both a tool to scrape,
capture and analyse data, as well as a way for the organisation to release data to a community of collaborators.
Open source: Opencorporates wants to make its product and the database accessible and scalable. It would not be possible without a huge number of open source programmes, tools and resources, such as Twitter Bootstrap and Linux.
It is mostly feasible to have the open data database as well as the community accessible online.
Within five years the database has expanded to over 61 million companies, without the Internet and the participation through Internet,
The company is being incubated in the UK Open Data Institute, and has received also a grant from the Alfred P Sloan Foundation.
Access to data: The main driver behind Opencorporates is access to data on the businesses
whose corporate structures they want to capture and release data on. However, accessibility to good data varies significantly from country to country,
depending on governments'willingness and capability to release this. New zealand as an example have easily accessible data sets
which Opencorporates with very simple coding can integrate into their data base, where as others release data in pdf files,
which makes scraping and accessing the data significantly harder. Linked to this is the varying quality of data available.
When mapping US companies data from The Federal reserve system is for example more granular structured and detailed than data from the Securities and exchange commission.
To address issues around quality of Opencorporates assing data confidences to links, with higher or lower confidence depending on data they were able to access.
What helps to reach goals and overcome barriers? Just as lack of access to data can be a barrier,
the easy access to open data sets from countries like New zealand has helped Opencorporates grow their database.
Building on this it can be argued that the ability to access a global open data community who as part of the bounty scheme helped Opencorporates scrape data from countries around the world has played a big role in their growth of the dataset.
Finally, the incubation within the Open Data Institute helped Opencorporates grow their business model and receive expert support from open data peers.
How does it achieve better European collaboration? Not applicable 157 Open Garden At a glance:
Type of Organisation: Private business Aim: Participation and democracy, other Technology Trends: Open networks, Open Knowledge DSI activities:
Operating a web service Key facts: 3 million users in 2013, which is tripled from 1 million a year before registered Website:
http://opengarden. com Organisation Name Open Garden Short description Open Garden is based a San francisco start up,
focusing on innovating in Internet use, through its mobile app and network building, and creating new ways to grow the Internet.
The simple mobile app enables users to connect to each other seamlessly and share their Internet connection.
mobile consumers have become data users, and data transfer activities are constantly taking place among mobile users.
Skyrocketing consumption of mobile data is becoming curbed by a finite amount of licensed spectrum and the capacity limitations of cellular networks.
Capacity and spectrum limitations can impact the user experience in very important and very negative ways.
They can produce inconsistent data services that leave consumers wondering when and where they can access the network,
Open Garden provides a way to access more data at faster speeds in more locations.
Open Garden provides a way to access more data at faster speeds in more locations.
which requires the network provider to go beyond the traditional mobile data solution. Open Garden therefore wishes to speed up innovation from both the technology perspective and social perspective,
Open Garden's technology provides an opportunity for carriers to address the shortcomings of cellular networks even as they deliver a superior experience for mobile data users.
It minimizes network traffic without the use of data caps and network throttling, which consumers abhor.
such as mobile data costumers, makers, hackers, the DIY community, urbanites and crowds, events attendees and organizers.
Open networks, Open data, Open Knowledge DSI activities: Participation and democracy Key facts: Developed CKAN Website:
The Open Knowledge Foundation is dedicated to promoting open data and open content in all their forms including government data, publicly funded research and public domain cultural content.
The Foundation is sees itself as an international leader in its field and has extensive experience in building tools
Through developing software OKF are trying to create tools that support a global open knowledge and open data community.
One of the most prominent of these is the Comprehensive Knowledge Archive Network (CKAN), one of the world's leading free open source data portal platforms.
CKAN is aimed at data publishers (national and regional governments, companies and organisations) wanting to make their data open and available.
CKAN also has a number of built-in features catered to data users, enabling users to browse
and find the data they need, and preview it using maps, graphs and tables-whether they are developers,
journalists, researchers, NGOS, citizens or professionals. CKAN also offers a powerful Application programming interface (API) which allows third-party applications
and services to be built using the published data. It was developed originally in 2006 by the OKF to run Thedatahub. org, a public registry of open knowledge datasets.
As a powerful data management system which makes data accessible, discoverable and presentable on the web by providing tools to streamline publishing,
sharing, finding and using data; its obvious usefulness has been evidenced by its wider adoption. CKAN now powers more than 40 data hubs around the world,
including portals for local, national and international government, such as the UK's data. gov. uk and the European union's publicdata. eu. Open Data Training:
In addition to building software tools for open data the OKFN also seeks to build the open data skills and capacity of governments and civil society organisations,
through providing a range of open data training programmes. Challenges: In 2011 the Foundation ran the Open Data Challenge,
which was Europe's biggest open data competition to date, attracting 430 entries from 24 Member States.
Events: Finally the OKFN seeks to stimulate the debate about open knowledge through events, from small scale policy workshops and coding sessions to its annual international OKFESTIVAL and OKCONFERENCE events.
What is the social impact it is seeking, including any evidence of impact to date? The OKFN overarching goal is a vibrant open knowledge commons that empowers citizens
and more rapid reuse of material and open data and content are the key raw ingredients for the development of new innovative tools and services.
The open source software is used by more than 70 organisations from Berlin to Nigeria globally to release their data in to open data sets.
Some of the most prominent users of CKAN include the UK's data. gov. uk website, the United states government's Data. gov and the Australian government's data. gov. au.
The open data challenge, for example, helped identify more than 430 open data entries for the challenge.
it supports organisations on furthering their work on, for example, open data. Just as the engagement of tens of thousands of people in Open Knowledge events help further the debate.
Naturally most of its projects rely heavily on open data, open data and open source standards.
and distribute large quantities of data. How is funded the organisation? The primary funding source is from grants to provide advice
Open Knowledge, Open Data DSI activities: A network, A research project, Operating a web service Key facts:
To data it has organised two annual physical meet-ups in Belgium and the UK, and also have some national groups organsing meetings in Netherlands and Greece.
Patientslikeme allows members to input real-world data on their conditions, treatment history, side effects, hospitalizations, symptoms, disease-specific functional scores, weight, mood,
Answers come in the form of shared longitudinal data from other patients with the same condition (s),
Its research professionals have completed studies with real-world data that have helped refute and preempt traditional randomised clinical trials.
The list of available trials is refreshed each night from the open data from Clinicaltrials. gov,
Sharing and selling data: Both a part of Patientlikeme's business model as well as its mission to create better treatments for its members,
Patientlikeme sells aggregated de-identified health data from patients to relevant parties such as companies that are developing
and do not do with their data. Memebers, Patientslikeme argue, are compelled to get involved as their sharing of this information,
it has helped published more than 35 research studies based on its patient data and it has generated over 1 million treatment & symptom reports.
With its community's growth at Patientslikeme, the practical and individual data and information from patients becomes extremely useful for clinic research,
because when patients share real-world data, collaboration on a global scale becomes possible, new treatments become possible,
where patients share data about their treatments, symptoms, and disease outcomes. Internet: Patientslikeme has used to Internet to cooperate online
and to allow for greater democratisation of patient medical data. Social networking and Community Power: Peer-to-peer networks are becoming the cornerstone for a new era of patient-centered health care.
and contribute data directly to research. Patientslikeme also combines an enhancing collaboration with the actual measurement of medicine,
and share their personal health data. The more data generated from users, the more detailed insights the network can garner from the data
and in return provide a higher value service for its members. How is funded the organisation? Patientslikeme has been funded by a group of philanthropic organisations and investment companies such as Commercenet, Omidyar Network, LLC, and Invus.
Commercenet was an key part of Patientslikeme's success as they provided the seed capital, guidance, additional management experience,
Most time hospitals do not have data or keep a long-time track of information from patients that they treated.
Currently, most healthcare data is inaccessible due to privacy regulations or proprietary tactics. As a result, research is slowed,
if people share data, and open up the healthcare system. In this way people can learn what's working for others,
In spite of the structural barriers in accessing patient medical data Patientslikeme's fast uptake illustrates the obvious need for services of its kind. 178 179 Peerby At a glance:
Open Data, Open Knowledge DSI activities: Operating a web service Key Facts: About 15,000 members in September 2013 Website:
These range from making your own retro Pi-powered arcade machine to adapting your Raspberry Pi to log all relevant data in your own weather station.
Open Networks, Open Hardware, Open Data, Open Knowledge DSI activities: An event, A network, Running/hosting maker spaces
and freely share their radiation measurements in open data sets. The overarching aim of Safecast is to encourage people to actively contribute to the generation of a body of data that might alleviate environmental problems.
The original impetus for the Geiger counter and network was the lack of good and open hard
In an effort to help, the partnership decided to take part in surfacing data on radiation levels across Japan,
and there were massive holes in the public radiation data sets available. As a response to this
and help launch a sensor network where bgiegie owners could share the data they were collecting.
which amongst others enabled users to mount the counter on the outside of a car and use GPS technology to timestamp the data and log the location.
Later on Ray Ozzie a data expert based in Boston joined the conversation when the question of how to release
and analyse the data arose. Looking beyond Japan: While Safecast was focused initially on mapping radiation levels in Japan the network has gone now global.
999 grant from the US based Knight Foundation to build a network of low-cost air quality monitoring devices and data collection in Los angeles and Detroit,
measurement data per se cannot be a useful resource for nuclear risk knowledge production. Volunteer Geiger counter users and social media users among others are necessary to produce specific type of nuclear risk knowledge.
The majority of data is captured through the bgeigie mobile sensor. A Geiger counter designed to be mounted on a vehicle,
All data captured via the Geiger counters is captured and released in an open data set, and the radiation measurements are color-coded
and plotted on a radiation level map which lets people easily understand the radiation level in a given geographical area.
the engine behind the success of the project is the large group of volunteers who use the Geiger counters to capture the data that makes the platform a valued resource.
the main drivers for Sean Bonner and his Safecast cofounders was a belief that people needed more and better radiation data,
and that currently a lot of governmental data is not adequate or transparent. Building on this Safecast intends to bring the attitude of citizen help themselves where the government failed.
collecting and sharing open data, as well as educating, without input from government. To date, this has enabled Safecast volunteers to map radiation levels of over 11 million data points,
As a pro-data organisation, Safecast generates nuclear risk knowledge by harnessing measurement data in multiple ways.
Open Data: As mentioned earlier, a cornerstone of Safecast is its commitment to open data,
which means that anyone with an interest in global radiation can freely contribute to and access the large data sets created by the Safecast community.
In addition to this, the team behind Safecast also seek a social impact by conducting radiation measurements on request, conducting seminars,
or pro nuclear but pro data. The goal is to provide more informative data where it didn't exist
so that people can make more informed decisions based on facts rather than the fear and speculation that comes from uninformed sources.
The goal is not to single out any individual source of data as untrustworthy, but rather to contribute to the existing measurement data
and make it more robust. 194 What is the role of the organisation within the DSI ecosystem?
Open data: Safecast provides an Open Application programming interface (API), allowing people to access raw measurement data.
More importantly, Safecast presents useful information on measurement data such as geo-location information and time of upload.
Such information not only makes it possible to locate when and where each datum was captured and uploaded,
but also allows people to process the huge volume of raw measurement data for their own ends.
Finally, Safecast visualizes measurement data on the Safecast Map in six coloured layers. This provides information for people on the level of nuclear radiation in areas across Japan.
The web-based online platform also enabled a sharing of data collected by citizens, to citizens, at a scale not possible before the advance of the Internet.
The richness of radiation data grows as people use and share radiation data. Equally, the variations and development of different Geiger counters grows,
adding value to the overall service, as DIY makers develop new types of counters which can be used by the network.
This provides a barrier in access to public data as well as distribution of data through public channels.
a lack of open and accurate measurement data, combined with intense media attention in the wake of the Fukushima disaster.
Open Networks, Open Data, Open Knowledge, Open Hardware DSI activities: A network, operating a web service Key facts:
These tools enable anyone who purchases the kit to contribute to the collection of environmental data,
Through connecting data, people and knowledge, the objective of the platform is to serve as a node for building productive and open indicators
it wants to produce new types of data and information which people previously couldn't get good access to.
and bringing the capture and analysis of city data as close to the public as possible.
Therefore he has always been interested in different data that is around the city, as well as how citizens interact with it.
Believing that citizens can interact with the city data more often and in an easier way,
and share data themselves, and make this a tool that could be used by citizens. At the IAAC Tomas met a group of people who were working on similar project prototype.
the‘kit'itself and the platform used to share data between people operating a kit.
equipped with sensors that can capture data on air quality, temperature, noise, humidity and light. The board also contains a solar charger
and a Wifi antenna that enables the direct upload data from the sensors in real time to the online platform Anyone who has owns a kit,
collate and share their data online on smartcitizen. me/pages/sck online platform. The platform is open to anyone
With the sensors the team tries to make it possible for citizens to know the data,
fosters participation of the general public in the process of producing open data used for the purpose of monitoring the environment.
from the bits to geography. 199 While the focus is generated on citizen data, the Smart Citizen Kit has attracted the attention of cities across Europe, such as Barcelona and Amsterdam,
and compare data and information in real time. On a grander scale, however, the very ideas underpinning the Smart Citizen project is one that is being adopted readily in a number of cities across Europe, such as Barcelona.
Open Data and Open source: The web platform is developed with Open-Streetmap, Leaflet, Raphaël, jquery, Cakephp, and many more.
and distribution of data The generation of analysis and further research as a result of this open data being generated Enhancing collaboration and engagement:
To be sustainable in working the data, motivate users to send data Smart Citizen kit has its own community,
where users collect and share the data online. But to keep users being motivated and therefore to keep the community active,
is essential to what Smart Citizen Kit wants to achieve. In response to this challenge, the team is frequently designing new features
To make the data and the technology meaningful: The team consider their Smart Citizen Kit as very effective data producers.
The next step is to find how people can make use of the data and how the data can help people to participate.
To achieve this, Tomas believe that it is necessary to make more and more people aware that they all can do something good with the data.
I think for Smart Citizen Kit it is important that people will feel it as a big name,
like same important as IBM, otherwise it won't Work on one hand, the project is now slowly by slowly generating more attention,
The original data, including its destination, are encrypted and re-encrypted multiple times, and are sent through a virtual circuit comprising successive, randomly selected Tor relays.
in order to pass the remaining encrypted data on to it. The final relay decrypts the last layer of encryption and sends the original data,
without revealing or even knowing its sender, to the destination. This method reduces the chance of the original data being understood in transit and
more notably, conceals the routing of it. Needless to say, the connection between a global network of volunteers who help reroute traffic would not have been possible with technological advances in sensor networks and the development of the web itself.
Open data*;*Open Knowledge Organisation Name Ushahidi Short description Ushahidi is a nonprofit tech company that specializes in developing free and open source software for the collection, visualisation and interactive mapping of information.
The Department of state analysts for the USG interagency task force used Ushahidi in at least one case to help triangulate conclusions about the situation on the ground US military organisations used Ushahidi data
Ushahidi has announced the development of a USSD (unstructured supplementary services data) app to reduce the time it takes to process reports
211 In the initial stages, event data generated by UHP did not meet the rigid requirements of traditional crisis response organisations.
Interviews also revealed some general suspicion of the crowd and related questions about the representativeness and quality of the data.
Unlike many early Internet-based citizen science projects (such as SETI@home which used spare computer processing power to analyse data, known as volunteer computing,
it is clear that Galaxy Zoo (Zooniverse's pilot project) first came about as a means of handling the enormous volumes of data by enlisting the help of public volunteers.
Overburdened academic departments very often have neither the time nor the resources to dedicate to processing this backlog of data.
Some of the most important data is in forms that computers still can't process,
'and open data forms a powerful synergy; using the web to provide a means of reaching a much larger audience willing to devote their free time to collaborative projects through crowdsourcing initiatives like Zooniverse.
With the launch of Zoo Tools (discussed more fully below) volunteers who seek to interact with the data in a deeper way are given a greater platform to do so.
volunteers are directly assisting cancer research scientists to accelerate the analysis of this data and‘bring forward the cures for cancers.'
and advance research through open knowledge and open data. What technological methods and tools is it using,
As mentioned above, the project was launched in 2007 to help process a data set made up of a million galaxies imaged by the Sloan Digital Sky Survey
Furthermore, data analysed through crowdsourcing in this way provides quantitative estimates of error thanks to multiple independent interactions with the data. 216 Enhancing collaboration and engagement:
CRUK) that allows the massive volumes of data to be processed through a platform of open data.
For instance, the data collected from the various projects has led to the publication of dozens of scientific papers.
With the launch of Zoo Tools users have been given yet another platform to collaborate with the data generated even further.
This application will offer community members tools of analysis to enable them to interact more deeply with the data generated.
In addition to this, the decision February 2013 to start making Zooniverse officially open source has allowed for new avenues for collaboration to be pursued other than the analysis of data.
While it the origins of the initiative might be thought principally of as a means of handling huge volumes of data,
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