Understanding Suicide and Help-seeking in Urban and Rural Areas in Northern Ireland

Funded by HSC R&D Division, Public Health Agency Why did we start? Most people who complete suicide are in contact with their family doctors or other services in the months prior to death. A better understanding of the nature of these contacts and the various pathways experienced by suicidal people should reveal the gaps and barriers to effective service provision. We also need better information about the difficulties experienced by family carers, both prior to the death and afterwards. Of particular interest to policy makers in Northern Ireland was a concern that people from rural areas may be at increasing risk of suicide. We were commissioned by the Health and Social Care R&D Division of the Northern Ireland Public Health Agency to address the gaps in our understanding of suicide in NI. What did we do? We undertook a mixed methods study in which we examined the records of 403 people who took their own lives over a two-year period between March 2007 and February 2009. We linked these data to GP records and then examined help-seeking pathways of people and their contacts with services. We did in-depth face-to-face interviews with 72 bereaved relatives and friends who discussed their understanding of the events and circumstances surrounding the death, the experience of seeking help for the family member, the personal impact of the suicide, and use of support services. Additionally, we interviewed 19 General Practitioners about their experiences of managing people who died by suicide.            

Capturing and indexing rehearsals: the design and usage of a digital archive of performing arts

Preserving the cultural heritage of the performing arts raises difficult and sensitive issues, as each performance is unique by nature and the juxtaposition between the performers and the audience cannot be easily recorded. In this paper, we report on an experimental research project to preserve another aspect of the performing arts—the history of their rehearsals. We have specifically designed non-intrusive video recording and on-site documentation techniques to make this process transparent to the creative crew, and have developed a complete workflow to publish the recorded video data and their corresponding meta-data online as Open Data using state-of-the-art audio and video processing to maximize non-linear navigation and hypervideo linking. The resulting open archive is made publicly available to researchers and amateurs alike and offers a unique account of the inner workings of the worlds of theater and opera.

Social machines dictating social behaviors – When context is missing what is the fallout of uberveillance?

Abstract: In the mid-1990s when I worked for a telecommunications giant I struggled to gain access to basic geodemographic data. It cost hundreds of thousands of dollars at the time to simply purchase a tile of satellite imagery from Marconi, and it was often cheaper to create my own maps using a digitizer and A0 paper maps. Everything from granular administrative boundaries to right-of-ways to points of interest and geocoding capabilities were either unavailable for the places I was working in throughout Asia or very limited. The control of this data was either in a government’s census and statistical bureau or was created by a handful of forward thinking corporations. Twenty years on we find ourselves inundated with data (location and other) that we are challenged to amalgamate, and much of it still “dirty” in nature. Open data initiatives such as ODI give us great hope for how we might be able to share information together and capitalize not only in the crowdsourcing behavior but in the implications for positive usage for the environment and for the advancement of humanity. We are already gathering and amassing a great deal of data and insight through excellent citizen science participatory projects across the globe. In early 2015, I delivered a keynote at the Data Made Me Do It conference at UC Berkeley, and in the preceding year an invited talk at the inaugural QSymposium. In gathering research for these presentations, I began to ponder on the effect that social machines (in effect, autonomous data collection subjects and objects) might have on social behaviors. I focused on studying the problem of data from various veillance perspectives, with an emphasis on the shortcomings of uberveillance which included the potential for misinformation, misinterpretation, and information manipulation when context was entirely missing. As we build advanced systems that rely almost entirely on social machines, we need to ponder on the risks associated with following a purely technocratic approach where machines devoid of intelligence may one day dictate what humans do at the fundamental praxis level. What might be the fallout of uberveillance? Bio: Dr Katina Michael is a professor in the School of Computing and Information Technology at the University of Wollongong. She presently holds the position of Associate Dean – International in the Faculty of Engineering and Information Sciences. Katina is the IEEE Technology and Society Magazine editor-in-chief, and IEEE Consumer Electronics Magazine senior editor. Since 2008 she has been a board member of the Australian Privacy Foundation, and until recently was the Vice-Chair. Michael researches on the socio-ethical implications of emerging technologies with an emphasis on an all-hazards approach to national security. She has written and edited six books, guest edited numerous special issue journals on themes related to radio-frequency identification (RFID) tags, supply chain management, location-based services, innovation and surveillance/ uberveillance for Proceedings of the IEEE, Computer and IEEE Potentials. Prior to academia, Katina worked for Nortel Networks as a senior network engineer in Asia, and also in information systems for OTIS and Andersen Consulting. She holds cross-disciplinary qualifications in technology and law.

Avoimen datan käyttäminen peleissä

Tämä kandidaatintyö keskittyy avoimen datan käyttämiseen peleissä nyt ja tulevaisuudessa. Sen tavoitteena on tutkia avoimen datan hyötyjä, saatavuutta ja mahdollisuuksia. Tuloksena selvisi, että useimmissa tapauksissa datan avaamisesta hyötyvät kaikki osapuolet. Runsaasti erilaista avointa dataa on saatavilla monissa erilaissa tiedostomuodoissa, moniin eri tarkoituksiin. Avoin data on hyödyllistä peleissä, koska sen avulla voidaan luoda monenlaista sisältöä niihin. Joitakin onnistuneita kokeiluja on jo tehty peleillä ja avoimella datalla, joten se voi olla hyvin tärkeä osa pelialaa tulevaisuudessa.

WikiRate.org - Leveraging collective awareness to understand companies' environmental, social and governance performance

Abstract. WikiRate is a Collective Awareness Platform for Sustainability and Social Innovation (CAPS) project with the aim of \crowdsourcing better companies" through analysis of their Environmental Social and Governance (ESG) performance. Research to inform the design of the platform involved surveying the current corporate ESG information landscape, and identifying ways in which an open approach and peer production ethos could be e ffectively mobilised to improve this landscape's fertility. The key requirement identi ed is for an open public repository of data tracking companies' ESG performance. Corporate Social Responsibility reporting is conducted in public, but there are barriers to accessing the information in a standardised analysable format. Analyses of and ratings built upon this data can exert power over companies' behaviour in certain circumstances, but the public at large have no access to the data or the most infuential ratings that utilise it. WikiRate aims to build an open repository for this data along with tools for analysis, to increase public demand for the data, allow a broader range of stakeholders to participate in its interpretation, and in turn drive companies to behave in a more ethical manner. This paper describes the quantitative Metrics system that has been designed to meet those objectives and some early examples of its use.

Capturing and indexing rehearsals: the design and usage of a digital archive of performing arts

Preserving the cultural heritage of the performing arts raises difficult and sensitive issues, as each performance is unique by nature and the juxtaposition between the performers and the audience cannot be easily recorded. In this paper, we report on an experimental research project to preserve another aspect of the performing arts—the history of their rehearsals. We have specifically designed non-intrusive video recording and on-site documentation techniques to make this process transparent to the creative crew, and have developed a complete workflow to publish the recorded video data and their corresponding meta-data online as Open Data using state-of-the-art audio and video processing to maximize non-linear navigation and hypervideo linking. The resulting open archive is made publicly available to researchers and amateurs alike and offers a unique account of the inner workings of the worlds of theater and opera.

MINING AND VERIFICATION OF TEMPORAL EVENTS WITH APPLICATIONS IN COMPUTER MICRO-ARCHITECTURE RESEARCH

Computer simulation programs are essential tools for scientists and engineers to understand a particular system of interest. As expected, the complexity of the software increases with the depth of the model used. In addition to the exigent demands of software engineering, verification of simulation programs is especially challenging because the models represented are complex and ridden with unknowns that will be discovered by developers in an iterative process. To manage such complexity, advanced verification techniques for continually matching the intended model to the implemented model are necessary. Therefore, the main goal of this research work is to design a useful verification and validation framework that is able to identify model representation errors and is applicable to generic simulators. The framework that was developed and implemented consists of two parts. The first part is First-Order Logic Constraint Specification Language (FOLCSL) that enables users to specify the invariants of a model under consideration. From the first-order logic specification, the FOLCSL translator automatically synthesizes a verification program that reads the event trace generated by a simulator and signals whether all invariants are respected. The second part consists of mining the temporal flow of events using a newly developed representation called State Flow Temporal Analysis Graph (SFTAG). While the first part seeks an assurance of implementation correctness by checking that the model invariants hold, the second part derives an extended model of the implementation and hence enables a deeper understanding of what was implemented. The main application studied in this work is the validation of the timing behavior of micro-architecture simulators. The study includes SFTAGs generated for a wide set of benchmark programs and their analysis using several artificial intelligence algorithms. This work improves the computer architecture research and verification processes as shown by the case studies and experiments that have been conducted.

Incidencia de la gestión de Frontex y el gobierno italiano en la acentuación de la crisis humanitaria de la Isla de Lampedusa entre 2011 y 2015

El presente estudio de caso busca examinar la incidencia de las medidas migratorias de control fronterizo implementadas por el Frontex y el gobierno Italiano en las condiciones mínimas de supervivencia de los migrantes irregulares, económicos y solicitantes de asilo en la Isla de Lampedusa, en el periodo 2011-2015. De esta manera, se identifican las medidas migratorias de control fronterizo implementadas por Frontex y el gobierno Italiano. Se examina la situación de la seguridad humana en la crisis migratoria de la Isla, y se analiza la relación entre las medidas migratorias de control fronterizo y las condiciones mínimas de supervivencia de los migrantes. El resultado de la investigación permite plasmar, las consecuencias negativas que han tenido las medidas migratorias en cuanto a las condiciones mínimas de supervivencia, lo que ha desembocado en una crisis humanitaria.

Landslide susceptibility in the Belt and Road Initiative

The Belt and Road Initiative (BRI) is a project launched by the Chinese Government whose main goal is to connect more than 65 countries in Asia, Europe, Africa and Oceania developing infrastructures and facilities. To support the prevention or mitigation of landslide hazards, which may affect the mainland infrastructures of BRI, a landslide susceptibility analysis in the countries involved has been carried out. Due to the large study area, the analysis has been carried out using a multi-scale approach which consists of mapping susceptibility firstly at continental scale, and then at national scale. The study area selected for the continental assessment is the south-Asia, where a pixel-based landslide susceptibility map has been carried out using the Weight of Evidence method and validated by Receiving Operating Characteristic (ROC) curves. Then, we selected the regions of west Tajikistan and north-east India to be investigated at national scale. Data scarcity is a common condition for many countries involved into the Initiative. Therefore in addition to the landslide susceptibility assessment of west Tajikistan, which has been conducted using a Generalized Additive Model and validated by ROC curves, we have examined, in the same study area, the effect of incomplete landslide dataset on the prediction capacity of statistical models. The entire PhD research activity has been conducted using only open data and open-source software. In this context, to support the analysis of the last years an open-source plugin for QGIS has been implemented. The SZ-tool allows the user to make susceptibility assessments from the data preprocessing, susceptibility mapping, to the final classification. All the output data of the analysis conducted are freely available and downloadable. This text describes the research activity of the last three years. Each chapter reports the text of the articles published in international scientific journal during the PhD.

Fedora 4 as a Shared Linked Data repository for the Art Institute of Chicago Collections

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Opening up climate research: A linked data approach to publishing data provenance

Traditionally, the formal scientific output in most fields of natural science has been limited to peer- reviewed academic journal publications, with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. In effect, this has constrained the representation and verification of the data provenance to the confines of the related publications. Detailed knowledge of a dataset’s provenance is essential to establish the pedigree of the data for its effective re-use, and to avoid redundant re-enactment of the experiment or computation involved. It is increasingly important for open-access data to determine their authenticity and quality, especially considering the growing volumes of datasets appearing in the public domain. To address these issues, we present an approach that combines the Digital Object Identifier (DOI) – a widely adopted citation technique – with existing, widely adopted climate science data standards to formally publish detailed provenance of a climate research dataset as an associated scientific workflow. This is integrated with linked-data compliant data re-use standards (e.g. OAI-ORE) to enable a seamless link between a publication and the complete trail of lineage of the corresponding dataset, including the dataset itself.

A new approach for publishing workflows: abstractions, standards, and linked data

In recent years, a variety of systems have been developed that export the workflows used to analyze data and make them part of published articles. We argue that the workflows that are published in current approaches are dependent on the specific codes used for execution, the specific workflow system used, and the specific workflow catalogs where they are published. In this paper, we describe a new approach that addresses these shortcomings and makes workflows more reusable through: 1) the use of abstract workflows to complement executable workflows to make them reusable when the execution environment is different, 2) the publication of both abstract and executable workflows using standards such as the Open Provenance Model that can be imported by other workflow systems, 3) the publication of workflows as Linked Data that results in open web accessible workflow repositories. We illustrate this approach using a complex workflow that we re-created from an influential publication that describes the generation of 'drugomes'.

Linked Opinions: Describing Sentiments on the Structured Web of Data

In the paper we report on the results of our experiments on the construction of the opinion ontology. Our aim is to show the benefits of publishing in the open, on the Web, the results of the opinion mining process in a structured form. On the road to achieving this, we attempt to answer the research question to what extent opinion information can be formalized in a unified way. Furthermore, as part of the evaluation, we experiment with the usage of Semantic Web technologies and show particular use cases that support our claims.

Exploiting Structured Linked Data in Enterprise Knowledge Management Systems: An Idea Management Case Study

In parallel to the effort of creating Open Linked Data for the World Wide Web there is a number of projects aimed for developing the same technologies but in the context of their usage in closed environments such as private enterprises. In the paper, we present results of research on interlinking structured data for use in Idea Management Systems - a still rare breed of knowledge management systems dedicated to innovation management. In our study, we show the process of extending an ontology that initially covers only the Idea Management System structure towards the concept of linking with distributed enterprise data and public data using Semantic Web technologies. Furthermore we point out how the established links can help to solve the key problems of contemporary Idea Management Systems

Combining data mining and ontology engineering to enrich ontologies and linked data

In this position paper, we claim that the need for time consuming data preparation and result interpretation tasks in knowledge discovery, as well as for costly expert consultation and consensus building activities required for ontology building can be reduced through exploiting the interplay of data mining and ontology engineering. The aim is to obtain in a semi-automatic way new knowledge from distributed data sources that can be used for inference and reasoning, as well as to guide the extraction of further knowledge from these data sources. The proposed approach is based on the creation of a novel knowledge discovery method relying on the combination, through an iterative ?feedbackloop?, of (a) data mining techniques to make emerge implicit models from data and (b) pattern-based ontology engineering to capture these models in reusable, conceptual and inferable artefacts.