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Details of Grant 

EPSRC Reference: EP/J017728/1
Title: SOCIAM: The Theory and Practice of Social Machines
Principal Investigator: Shadbolt, Professor N
Other Investigators:
Moreau, Professor L Buneman, Professor OP schraefel, Professor m
De Roure, Professor D Hall, Professor Dame W Berners-Lee, Professor Sir TJ
Robertson, Professor D
Researcher Co-Investigators:
Project Partners:
Agency for Science Technology (A Star) Baxi Big White Wall Ltd
BT Cabinet Office Ctrl Shift Ltd
Deloitte UK Edelman ESRC
Google Group Partners Ltd Hampshire Constabulary
Home Office IBM KAIST
Microsoft Northwestern University Tsinghua University
Department: Electronics and Computer Science
Organisation: University of Southampton
Scheme: Programme Grants
Starts: 01 June 2012 Ends: 31 July 2015 Value (£): 6,219,059
EPSRC Research Topic Classifications:
Artificial Intelligence Human-Computer Interactions
Information & Knowledge Mgmt Science & Technology Studies
EPSRC Industrial Sector Classifications:
Information Technologies Financial Services
Communications
Related Grants:
Panel History:
Panel DatePanel NameOutcome
02 Feb 2012 Programme Grant Interviews - 2 February 2012 (ICT) Announced
Summary on Grant Application Form
SOCIAM - Social Machines - will research into pioneering methods of supporting purposeful human interaction on the World Wide Web, of the kind exemplified by phenomena such as Wikipedia and Galaxy Zoo. These collaborations are empowering, as communities identify and solve their own problems, harnessing their commitment, local knowledge and embedded skills, without having to rely on remote experts or governments.

Such interaction is characterised by a new kind of emergent, collective problem solving, in which we see (i) problems solved by very large scale human participation via the Web, (ii) access to, or the ability to generate, large amounts of relevant data using open data standards, (iii) confidence in the quality of the data and (iv) intuitive interfaces.

"Machines" used to be programmed by programmers and used by users. The Web, and the massive participation in it, has dissolved this boundary: we now see configurations of people interacting with content and each other, typified by social web sites. Rather than dividing between the human and machine parts of the collaboration (as computer science has traditionally done), we should draw a line around them and treat each such assembly as a machine in its own right comprising digital and human components - a Social Machine. This crucial transition in thinking acknowledges the reality of today's sociotechnical systems. This view is of an ecosystem not of humans and computers but of co-evolving Social Machines.

The ambition of SOCIAM is to enable us to build social machines that solve the routine tasks of daily life as well as the emergencies. Its aim is to develop the theory and practice so that we can create the next generation of decentralised, data intensive, social machines. Understanding the attributes of the current generation of successful social machines will help us build the next.

The research undertakes four necessary tasks. First, we need to discover how social computing can emerge given that society has to undertake much of the burden of identifying problems, designing solutions and dealing with the complexity of the problem solving. Online scaleable algorithms need to be put to the service of the users. This leads us to the second task, providing seamless access to a Web of Data including user generated data. Third, we need to understand how to make social machines accountable and to build the trust essential to their operation. Fourth, we need to design the interactions between all elements of social machines: between machine and human, between humans mediated by machines, and between machines, humans and the data they use and generate. SOCIAM's work will be empirically grounded by a Social Machines Observatory to track, monitor and classify existing social machines and new ones as they evolve, and act as an early warning facility for disruptive new social machines.

These lines of interlinked research will initially be tested and evaluated in the context of real-world applications in health, transport, policing and the drive towards open data cities (where all public data across an urban area is linked together) in collaboration with SOCIAM's partners. Putting research ideas into the field to encounter unvarnished reality provides a check as to their utility and durability. For example the Open City application will seek to harness citywide participation in shared problems (e.g. with health, transport and policing) exploiting common open data resources.

SOCIAM will undertake a breadth of integrated research, engaging with real application contexts, including the use of our observatory for longitudinal studies, to provide cutting edge theory and practice for social computation and social machines. It will support fundamental research; the creation of a multidisciplinary team; collaboration with industry and government in realization of the research; promote growth and innovation - most importantly - impact in changing the direction of ICT.
Key Findings
The SOCIAM team is undertaking research across 6 main themes:

THEME1: SOCIAM COMPUTATION

Workpackage 1.1 Design of Social Computation Through Interaction

The aim of this WP is to provide a means by which social computations may be specified; then (since we then have a language in which social computation intentions can be shared) to use this as a basis for generating social computations as a result of social activity. To this end, we have:

Devised a specification language, LSC, based on the earlier LCC specification system, for representing social computations. This operates in peer to peer contexts, where all knowledge germane to the computation must be explicitly shared – a key requirement for generalization across different social architectures with varying degrees of implicit knowledge underpinning the computation.

Shown how core aspects of provenance representation (focusing on PROV as a representation language) can be derived from specifications expressed in LSC, so that social interaction (in our general framework) allows production of some forms of provenance information as part of the “exhaust data” of social interaction.

Experimented (via a PhD studentship additional to SOCIAM) with one form of automated synthesis of LCC which uses abstract specifications for a class of reasoning task (in this case argumentation) as the basis for synthesis of LCC. This produced a system in which one specifies an argument (in a variant of the Argument Interchange Format) and the social interaction to support this can automatically be synthesized in LCC.

Workpackage 1.2 Enactment Through Social Dispersal

The aim of this WP is to explore means of enacting social computations that is based on the executable specification languages of WP 1.1 but extends the range of mechanisms through which these may be enacted, so as to exploit the Web and social media. To this end we have:

Built a mechanism for enacting LSC via a Web portal with the LSC specification being (effectively) a document that is updated via each access to the portal and retains within it the state of the social interaction. This gives access+enactment that requires only browser access with no computation within the browser.

Built (via a PhD studentship additional to SOCIAM) a mechanism that runs LCC social interactions within the browser (using a standard message passing protocol for information exchange). This requires computation within the browser but relieves the computation on the server.

Built a mechanism for enacting LCC by posting/reading to/from Twitter streams. This interacts with Twitter (and is intended to influence behaviours of Twitter users) but is not, itself, embedded within the Twitter infrastructure. In other words, it influences social behavioUr without intruding into the medium used to communicate.

The Edinburgh team has worked with the Southampton team to connect our process-based, interaction specifications to Southampton’s data representation and storage systems. This involves joint work on scenarios involving health data.

THEME 2: CURATED DATA AND SOCIAL COMPUTATION

Our goal here is to understand the requirements for storing and annotating data consumed, produced and calculated by social machines. An analysis of diverse data sets gathered from social machines is likely to require the ability to link data across formal data structures (such as RDF) using description logics (DL) for ontology languages. With a strong theoretical focus this stream has produced a series of significant papers on DL queries over the past 12 months. Future work will continue develop this theme and also the curation and preservation of the types of linked (open) data that will underpin social machines.

THEME 3: PRIVACY, TRUST AND ACCOUNTABILITY

Since the revelations regarding NSA privacy intrusions and potentially those of other groups globally the need to refine models underpinning requirements for personal privacy and the corresponding trust in services and systems has never been greater.

Our work has focussed on developing a theoretical model for subjective trust based on the recent PROV standard. Trusts flows from a knowledge/certainty of the source and authorship of data and we believe that PROV will continue to be highly significant in this space.

THEME 4: INTERACTION

This package has delivered a new personal data store (PDS) platform called INDX for the storage, processing and sharing of personal information between social machines. This platform seeks to go beyond the rigid workflows of "mechanical turk" like systems and yet retain more accuracy and control than purely human-mediated collaborations which are highly time and attention intensive. To compensate for fixed limited attentional resources, we focus on cognitively offloading information management to one’s personal data stores, with data capabilities including: background data collation, integration and consolidation, privacy management and longitudinal information maintenance.

THEME 5: SOCIAM MACHINE IMPLEMENTATIONS

Workpackage 5.2 Social Machines in Policing

A crime/social nuisance reporting app has been developed, which includes a technical infrastructure, and interaction models.

Workpackage 5.5 Social Machines in New Contexts

Delivering applications was not envisaged at the start of the project. We are working with two case studies of social machines ecosystems that we are directly engaged in outside the project: (1) scholarly social machines and (2) social machines in music.

THEME 6: SOCIAL MACHINE OBSERVATORY

Workpackage 6.1 Building the Observatory

Currently active in developing an appropriate infrastructure to support observing social machines, which includes the design and testing of various technical approaches for harvesting, storing, discovering, querying and linking datasets within and across Web Observatories. We are currently experimenting with different single and distributed storage and database technologies including Hadoop, MongoDB, SPARQL and SQL, along with using in-house solutions such as 4Store and RAGLD. We have also been developing a Web interface/portal which provides access for individuals (internal and external to Southampton/SOCIAM) to find, list, host and share datasets and visualisations. The sharing layer (access control) provides for dataset owners to provide control, visibility and access of datasets on a per-user basis, while the query interface provides for querying across datasets; this functionality at the moment is available for SPARQL endpoints but we plan to extend it for other storage technologies and to enable distributed queries over heterogeneous datasets. The initial build for the Web Observatory can be found at:

http://web-001.ecs.soton.ac.uk



There is also significant effort on developing the 'Personal Web Observatory' within the personal data store, INDX. The aim of this is to provide individuals with their own Web Observatory, enabling users to automatically collect their own 'social machine data' which they will be able to store, archive, and perform their own analytics on, potentially in combination with external Web Observatories. A future development will be to provide a discovery layer to enable users to share their data, using open standards.



Work Package 6.2 Observation of Social Machines

We have collected a number of datasets which provide an observational lens on different social machines, including, Twitter, Wikipedia, Weibo, Zooniverse and USEWOD datasets. The datasets collected are from various time periods, and magnitude (from 1 million to 7 billion records). These datasets are currently listed on the Web Observatory portal with its sharing and querying utilities. Some of those datasets are available in a range of storage technologies in order to assess the performance of those technologies for analytics.



Workpackage 6.4 Living Laboratory (producing an open platform for collaboration)

We are currently working on a workshop paper based on this work. This opens up Zooniverse as a laboratory not just for SOCIAM but for a broader community, i.e. It is an instance of an open platform for collaboration, benefiting from a huge community, considerable captivity and interest from researchers in studying it.

Workpackage 6.5 Social Science Interface

The development of the Web Observatory portal provides individuals with interfaces to query the various datasets listed. In addition to this, a number of visualisations and analytics have been developed or contributed by the community and they can promote further collaborative development. In addition to this, we have been working closely with Rensellaer Polytechnic Institute to define a Web Observatory ontology which will be used to describe the datasets, tools, visualisations, results and methods used within a Web Observatory project.
Potential use in non-academic contexts
We have engaged with Hampshire County Council (and through them, Hampshire Constabulary), the Hampshire Police and Crime Commissioner, and the College of Policing collaborating on use of the Web Observatory to monitor social media activity and also to specify use cases for a nuisance reporting app. Potential domains for exploitation include:understanding victim experience, witness experience, anti-social behaviour and intelligence gathering.

The collaboration with Hampshire County Council has produced a paper presented at a policing conference about the role that social machines technology could play in policing and crime management.
Impacts
No information has been submitted for this grant.
Sectors submitted by the Researcher
Information & Communication Technologies
Project URL: http://sociam.org/
Further Information:  
Organisation Website: http://www.soton.ac.uk