B2B Infrastructures in the Process of Drug Discovery and Healthcare

In this paper we describe a demonstration of an innovative B2B infrastructure which can be used to support collaborations in the pharmaceutical industry to achieve the drug discovery goal. Based on experience gained in a wide range of collaborative projects in the areas of grid technology, semantics and data management we show future work and new topics in B2B infrastructures which arise when considering the use of patient records in the process of drug discovery and in healthcare applications

Determining citizens’ opinions about stories in the news media: analysing Google, Facebook and Twitter

We describe a method whereby a governmental policy maker can discover citizens’ reaction to news stories. This is particularly relevant in the political world, where governments’ policy statements are reported by the news media and discussed by citizens. The work here addresses two main questions: whereabouts are citizens discussing a news story, and what are they saying? Our strategy to answer the first question is to find news articles pertaining to the policy statements, then perform internet searches for references to the news articles’ headlines and URLs. We have created a software tool that schedules repeating Google searches for the news articles and collects the results in a database, enabling the user to aggregate and analyse them to produce ranked tables of sites that reference the news articles. Using data mining techniques we can analyse data so that resultant ranking reflects an overall aggregate score, taking into account multiple datasets, and this shows the most relevant places on the internet where the story is discussed. To answer the second question, we introduce the WeGov toolbox as a tool for analysing citizens’ comments and behaviour pertaining to news stories. We first use the tool for identifying social network discussions, using different strategies for Facebook and Twitter. We apply different analysis components to analyse the data to distil the essence of the social network users’ comments, to determine influential users and identify important comments

Business Process Risk Management and Simulation Modelling for Digital Audio-Visual Media Preservation.

Digitised and born-digital Audio-Visual (AV) content presents new challenges for preservation and Quality Assurance (QA) to ensure that cultural heritage is accessible for the long term. Digital archives have developed strategies for avoiding, mitigating and recovering from digital AV loss using IT-based systems, involving QA tools before ingesting files into the archive and utilising file-based replication to repair files that may be damaged while in the archive. However, while existing strategies are effective for addressing issues related to media degradation, issues such as format obsolescence and failures in processes and people pose significant risk to the long-term value of digital AV content. We present a Business Process Risk management framework (BPRisk) designed to support preservation experts in managing risks to long-term digital media preservation. This framework combines workflow and risk specification within a single risk management process designed to support continual improvement of workflows. A semantic model has been developed that allows the framework to incorporate expert knowledge from both preservation and security experts in order to intelligently aid workflow designers in creating and optimising workflows. The framework also provides workflow simulation functionality, allowing users to a) understand the key vulnerabilities in the workflows, b) target investments to address those vulnerabilities, and c) minimise the economic consequences of risks. The application of the BPRisk framework is demonstrated on a use case with the Austrian Broadcasting Corporation (ORF), discussing simulation results and an evaluation against the outcomes of executing the planned workflow

Determining citizens’ opinions about stories in the news media

We describe a method whereby a governmental policy maker can discover citizens’ reaction to news stories. This is particularly relevant in the political world, where governments’ policy statements are reported by the news media and discussed by citizens. The work here addresses two main questions: whereabouts are citizens discussing a news story, and what are they saying? Our strategy to answer the first question is to find news articles pertaining to the policy statements, then perform internet searches for references to the news articles’ headlines and URLs. We have created a software tool that schedules repeating Google searches for the news articles and collects the results in a database, enabling the user to aggregate and analyse them to produce ranked tables of sites that reference the news articles. Using data mining techniques we can analyse data so that resultant ranking reflects an overall aggregate score, taking into account multiple datasets, and this shows the most relevant places on the internet where the story is discussed. To answer the second question, we introduce the WeGov toolbox as a tool for analysing citizens’ comments and behaviour pertaining to news stories.  We first use the tool for identifying social network discussions, using different strategies for Facebook and Twitter. We apply different analysis components to analyse the data to distil the essence of the social network users’ comments, to determine influential users and identify important comments

Understanding human-machine networks: A cross-disciplinary survey

© 2017 ACM. In the current hyperconnected era, modern Information and Communication Technology (ICT) systems form sophisticated networks where not only do people interact with other people, but also machines take an increasingly visible and participatory role. Such Human-Machine Networks (HMNs) are embedded in the daily lives of people, both for personal and professional use. They can have a significant impact by producing synergy and innovations. The challenge in designing successful HMNs is that they cannot be developed and implemented in the same manner as networks of machines nodes alone, or following a wholly human-centric view of the network. The problem requires an interdisciplinary approach. Here, we review current research of relevance to HMNs across many disciplines. Extending the previous theoretical concepts of sociotechnical systems, actor-network theory, cyber-physical-social systems, and social machines, we concentrate on the interactions among humans and between humans and machines. We identify eight types of HMNs: public-resource computing, crowdsourcing, web search engines, crowdsensing, online markets, social media, multiplayer online games and virtual worlds, and mass collaboration. We systematically select literature on each of these types and review it with a focus on implications for designing HMNs. Moreover, we discuss risks associated with HMNs and identify emerging design and development trends

Analysis combining correlated glaucoma traits identifies five new risk loci for open-angle glaucoma

Open-angle glaucoma (OAG) is a major cause of blindness worldwide. To identify new risk loci for OAG, we performed a genome-wide association study in 3,071 OAG cases and 6,750 unscreened controls, and meta-analysed the results with GWAS data for intraocular pressure (IOP) and optic disc parameters (the overall meta-analysis sample size varying between 32,000 to 48,000 participants), which are glaucoma-related traits. We identified and independently validated four novel genome-wide significant associations within or near MYOF and CYP26A1, LINC02052 and CRYGS, LMX1B, and LMO7 using single variant tests, one additional locus (C9) using gene-based tests, and two genetic pathways - “response to fluid shear stress” and “abnormal retina morphology” - in pathway-based tests. Interestingly, some of the new risk loci contribute to risk of other genetically-correlated eye diseases including myopia and age-related macular degeneration. To our knowledge, this study is the first integrative study to combine genetic data from OAG and its correlated traits to identify new risk variants and genetic pathways, highlighting the future potential of combining genetic data from genetically-correlated eye traits for the purpose of gene discovery and mapping

ANSWER: A Semantic Approach to Film Direction

In this paper we present ANSWER, an innovative approach to film direction. Here we describe a methodology to semantically model the film domain in a way which is coherent with the director’s intent during film production. To achieve this, we are developing a system architecture which will provide the director with the necessary tools and services to author a scene description through intuitive gesture based graphical user interfaces, which will in turn populate the underlying model with a rich set of semantic descriptions. These semantic descriptions will be used to render the scene graphically through animated previsualizations. A director using the ANSWER methodology will be able to understand and assert certain film making decisions before film production begin

SNS-based eParticipation and cloud computing - a consideration of the issues raised

Social Networking Systems provide a significant opportunity for governmental policy-makers by allowing them to interact directly with citizens, for example by stimulating new discussions or participating in conversations that are already underway so as to gauge public opinion on a proposal. Because Social Networks are already widely adopted, they provide potential for a much wider citizen base than specialist eParticipation platforms. The WeGov project is building a software toolkit to help policy-makers make effective use of SNSs by stimulating debates, identifying hot and emerging topics and picking out influential individuals or clusters of sentiment. The data storage and processing requirements of these features are significant, and third-party Cloud Computing presented itself as an option to meet them in a way that would be affordable to cash-strapped public-sector organisation. However despite the popularity of Cloud Computing services in the business IT world, concerns about data protection and privacy led us to conclude that political conversations harvested from SNS networks could not legally and ethically be entrusted to such services at the current time. This paper presents our analysis and offers some recommendations to Cloud Providers that we believe must be adopted if the potential of the technology as an economical platform for eParticipation is to be realised

Roadmap for human-machine networks for Citizen Participation

This white paper presents a roadmap for human-machine networks for Citizen Participation. Based on a quantitative survey of 20 self-selecting stakeholders, key issues across stakeholders were identified along with potential conflicts between them. The challenges of developing and maintaining trust along with keeping motivation going are discussed. These are addressed in the first instance with manipulation of dimensions derived from the HUMANE typology to suggest ways in which conflict between stakeholders might be addressed. Finally, returning to the main concerns of trust and motivation, a non-linear timeline is proposed based on activities affecting HMNs and how such events might affect trust