Open Data: European Ambitions and Local Efforts. Experiences from Austria

The member states of the European Union are faced with the challenges of handling “big data” as well as with a growing impact of the supranational level. Given that the success of efforts at European level strongly depends on corresponding national and local activities, i.e., the quality of implementation and the degree of consistency, this chapter centers upon the coherence of European strategies and national implementations concerning the reuse of public sector information. Taking the City of Vienna’s open data activities as an illustrative example, we seek an answer to the question whether and to what extent developments at European level and other factors have an effect on local efforts towards open data. We find that the European Commission’s ambitions are driven by a strong economic argumentation, while the efforts of the City of Vienna have only very little to do with the European orientation and are rather dominated by lifestyle and administrative reform arguments. Hence, we observe a decoupling of supranational strategies and national implementation activities. The very reluctant attitude at Austrian federal level might be one reason for this, nationally induced barriers—such as the administrative culture—might be another. In order to enhance the correspondence between the strategies of the supranational level and those of the implementers at national and regional levels, the strengthening of soft law measures could be promising.

Bereavement After Informal Caregiving: Assessing Mental Health Burden Using Linked Population Data

Methods. We linked prescription records for antidepressant and anxiolytic drugs to characteristics and life-event data of members of the Northern Ireland Longitudinal Study (n = 317 264). Using a case-control design, we fitted logistic regression models, stratified by age, to model relative likelihood of mental health problems, using the proxy measures of mental health–related prescription.

Results. Both caregivers and bereaved individuals were estimated to be at between 20% and 50% greater risk for mental health problems than noncaregivers in similar circumstances (for bereaved working-age caregivers, odds ratio = 1.41; 95% confidence interval = 1.27, 1.56). For older people, there was no evidence of additional risk to bereaved caregivers, though there was for working-age people. Older people appeared to recover more quickly from caregiver bereavement.

The first WASP public data release

The WASP (wide angle search for planets) project is an exoplanet transit survey that has been automatically taking wide field images since 2004. Two instruments, one in La Palma and the other in South Africa, continually monitor the night sky, building up light curves of millions of unique objects. These light curves are used to search for the characteristics of exoplanetary transits. This first public data release (DR1) of the WASP archive makes available all the light curve data and images from 2004 up to 2008 in both the Northern and Southern hemispheres. A web interface () to the data allows easy access over the Internet. The data set contains 3 631 972 raw images and 17 970 937 light curves. In total the light curves have 119 930 299 362 data points available between them.

The Antibiotic Resistance and Prescribing in European Children Project: A Neonatal and Pediatric Antimicrobial Web-based Point Prevalence Survey in 73 Hospitals Worldwide

BACKGROUND: The neonatal and pediatric antimicrobial point prevalence survey (PPS) of the Antibiotic Resistance and Prescribing in European Children project (http://www.arpecproject.eu/) aims to standardize a method for surveillance of antimicrobial use in children and neonates admitted to the hospital within Europe. This article describes the audit criteria used and reports overall country-specific proportions of antimicrobial use. An analytical review presents methodologies on antimicrobial use.

METHODS: A 1-day PPS on antimicrobial use in hospitalized children was organized in September 2011, using a previously validated and standardized method. The survey included all inpatient pediatric and neonatal beds and identified all children receiving an antimicrobial treatment on the day of survey. Mandatory data were age, gender, (birth) weight, underlying diagnosis, antimicrobial agent, dose and indication for treatment. Data were entered through a web-based system for data-entry and reporting, based on the WebPPS program developed for the European Surveillance of Antimicrobial Consumption project.

RESULTS: There were 2760 and 1565 pediatric versus 1154 and 589 neonatal inpatients reported among 50 European (n = 14 countries) and 23 non-European hospitals (n = 9 countries), respectively. Overall, antibiotic pediatric and neonatal use was significantly higher in non-European (43.8%; 95% confidence interval [CI]: 41.3-46.3% and 39.4%; 95% CI: 35.5-43.4%) compared with that in European hospitals (35.4; 95% CI: 33.6-37.2% and 21.8%; 95% CI: 19.4-24.2%). Proportions of antibiotic use were highest in hematology/oncology wards (61.3%; 95% CI: 56.2-66.4%) and pediatric intensive care units (55.8%; 95% CI: 50.3-61.3%).

CONCLUSIONS: An Antibiotic Resistance and Prescribing in European Children standardized web-based method for a 1-day PPS was successfully developed and conducted in 73 hospitals worldwide. It offers a simple, feasible and sustainable way of data collection that can be used globally.

MixKMeans: Clustering Question-Answer Archives

Community-driven Question Answering (CQA) systems that crowdsource experiential information in the form of questions and answers and have accumulated valuable reusable knowledge. Clustering of QA datasets from CQA systems provides a means of organizing the content to ease tasks such as manual curation and tagging. In this paper, we present a clustering method that exploits the two-part question-answer structure in QA datasets to improve clustering quality. Our method, {\it MixKMeans}, composes question and answer space similarities in a way that the space on which the match is higher is allowed to dominate. This construction is motivated by our observation that semantic similarity between question-answer data (QAs) could get localized in either space. We empirically evaluate our method on a variety of real-world labeled datasets. Our results indicate that our method significantly outperforms state-of-the-art clustering methods for the task of clustering question-answer archives.

A marine reservoir correction database and on-line interface

Calibration is essential for interpretation of radiocarbon dates, especially when the 14C dates are compared to historical or climatic records with a different chronological basis. 14C ages of samples from the marine environment, such as shells or fish bones, or samples with a marine component, such as human bone in coastal regions, require an additional consideration because of the reservoir age of the ocean. While the pre-industrial global mean reservoir correction, R(t), is about 400 years, local variations (?R) can be several hundred years or more. ?R compilations on a global scale have been undertaken previously (Stuiver et al. 1986; Stuiver and Braziunas 1993), but have not been updated recently. Here we describe an on-line reservoir correction database accessed via mapping software. Rather than publishing a static ?R compilation, new data will be incorporated when it becomes available. The on-line marine reservoir correction database can be accessed at the website http://www.calib.org/.

A Lightweight Tool for Anomaly Detection in Cloud Data Centres

Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting anomalies often use machine learning techniques, application instance behaviours or system metrics distribu- tion, which are complex to implement in Cloud computing environments as they require training, access to application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre- lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second (IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when an application stresses the disk, indicating a node-level anomaly.

Prying into the intimate secrets of animal lives; software beyond hardware for comprehensive annotation in 'Daily Diary' tags

BACKGROUND: Smart tags attached to freely-roaming animals recording multiple parameters at infra-second rates are becoming commonplace, and are transforming our understanding of the way wild animals behave. Interpretation of such data is complex and currently limits the ability of biologists to realise the value of their recorded information.

DESCRIPTION: This work presents Framework4, an all-encompassing software suite which operates on smart sensor data to determine the 4 key elements considered pivotal for movement analysis from such tags (Endangered Species Res 4: 123-37, 2008). These are; animal trajectory, behaviour, energy expenditure and quantification of the environment in which the animal moves. The program transforms smart sensor data into dead-reckoned movements, template-matched behaviours, dynamic body acceleration-derived energetics and position-linked environmental data before outputting it all into a single file. Biologists are thus left with a single data set where animal actions and environmental conditions can be linked across time and space.

CONCLUSIONS: Framework4 is a user-friendly software that assists biologists in elucidating 4 key aspects of wild animal ecology using data derived from tags with multiple sensors recording at high rates. Its use should enhance the ability of biologists to derive meaningful data rapidly from complex data.

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

Background: Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results: We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts.Conclusions: QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions.

Patterns and predictors of help-seeking contacts with health services and general practitioner detection of suicidality prior to suicide: a cohort analysis of suicides occurring over a two-year period

Background: Contact with primary care and psychiatric services prior to suicide may be considerable, presenting
opportunities for intervention. However, there is scant knowledge on the frequency, nature and determinants of
contact.
Method: Retrospective cohort study-an analysis of deaths recorded as suicide by the Northern Ireland Coroner’s
Office linked with data from General Practice patient records over a 2 year period
Results: Eighty-seven per cent of suicides were in contact with General Practice services in the 12 months before
suicide. The frequency of contact with services was considerable, particularly among patients with a common
mental disorder or substance misuse problems. A diagnosis of psychiatric problems was absent in 40 % of suicides.
Excluding suicide attempts, the main predictors of a noted general practitioner concern for patient suicidality are
male gender, frequency of consultations, diagnosis of mental illness and substance misuse.
Conclusions: Despite widespread and frequent contact, a substantial proportion of suicidal people were
undiagnosed and untreated for mental health problems. General Practitioner alertness to suicidality may be too
narrowly focused.