Visualisation of quality information for geospatial and remote sensing data:providing the GIS community with the decision support tools for geospatial dataset quality evaluation

The evaluation of geospatial data quality and trustworthiness presents a major challenge to geospatial data users when making a dataset selection decision. The research presented here therefore focused on defining and developing a GEO label – a decision support mechanism to assist data users in efficient and effective geospatial dataset selection on the basis of quality, trustworthiness and fitness for use. This thesis thus presents six phases of research and development conducted to: (a) identify the informational aspects upon which users rely when assessing geospatial dataset quality and trustworthiness; (2) elicit initial user views on the GEO label role in supporting dataset comparison and selection; (3) evaluate prototype label visualisations; (4) develop a Web service to support GEO label generation; (5) develop a prototype GEO label-based dataset discovery and intercomparison decision support tool; and (6) evaluate the prototype tool in a controlled human-subject study. The results of the studies revealed, and subsequently confirmed, eight geospatial data informational aspects that were considered important by users when evaluating geospatial dataset quality and trustworthiness, namely: producer information, producer comments, lineage information, compliance with standards, quantitative quality information, user feedback, expert reviews, and citations information. Following an iterative user-centred design (UCD) approach, it was established that the GEO label should visually summarise availability and allow interrogation of these key informational aspects. A Web service was developed to support generation of dynamic GEO label representations and integrated into a number of real-world GIS applications. The service was also utilised in the development of the GEO LINC tool – a GEO label-based dataset discovery and intercomparison decision support tool. The results of the final evaluation study indicated that (a) the GEO label effectively communicates the availability of dataset quality and trustworthiness information and (b) GEO LINC successfully facilitates ‘at a glance’ dataset intercomparison and fitness for purpose-based dataset selection

Geospatial data quality indicators

Indicators which summarise the characteristics of spatiotemporal data coverages significantly simplify quality evaluation, decision making and justification processes by providing a number of quality cues that are easy to manage and avoiding information overflow. Criteria which are commonly prioritised in evaluating spatial data quality and assessing a dataset’s fitness for use include lineage, completeness, logical consistency, positional accuracy, temporal and attribute accuracy. However, user requirements may go far beyond these broadlyaccepted spatial quality metrics, to incorporate specific and complex factors which are less easily measured. This paper discusses the results of a study of high level user requirements in geospatial data selection and data quality evaluation. It reports on the geospatial data quality indicators which were identified as user priorities, and which can potentially be standardised to enable intercomparison of datasets against user requirements. We briefly describe the implications for tools and standards to support the communication and intercomparison of data quality, and the ways in which these can contribute to the generation of a GEO label

Towards accessible mental healthcare through augmented reality and self-assessment tools

Mental health presents a growing public health concern worldwide with mental illnesses affecting people's quality of life and causing an economic impact on societies. The rapidly increasing demand for mental healthcare is calling for new ways of disseminating mental health knowledge and for supporting people with mental health illnesses. As an alternative to traditional mental health therapies and treatments, mental health self-assessment and self-management tools become widely available to the public. While such tools can potentially offer more timely personalised support, individuals seeking help are faced with the challenge of making an appropriate choice from an exhaustive number of online tools, mobile apps, and support programs. In this article, we present myGRaCE-a self-assessment and self-management mental health tool made accessible to users via Augmented Reality technologies. The advantage of the system is that it provides a direct pathway to relevant and reliable mental health resources and offers a positive incentive and interventions for at-risk users. To investigate the usability and intuitiveness of the system, we conducted a pilot evaluation study with 10 participants. The results showed that the majority of study participants found the system intuitive and easy to use

Gaining insights into road traffic data through genetic improvement

We argue that Genetic Improvement can be successfully used for enhancing road traffc data mining. This would support the relevant decision makers with extending the existing network of devices that sense and control city traffc, with the end goal of improving vehicle Flow and reducing the frequency of road accidents. Our position results from a set of preliminary observations emerging from the analysis of open access road trafic data collected in real time by the Birmingham City Council

GEO Label Web Services for Dynamic and Effective Communication of Geospatial Metadata Quality

We present demonstrations of the GEO label Web services and their integration into a prototype extension of the GEOSS portal (http://scgeoviqua.sapienzaconsulting.com/web/guest/geo_home), the GMU portal (http://gis.csiss.gmu.edu/GADMFS/) and a GeoNetwork catalog application (http://uncertdata.aston.ac.uk:8080/geonetwork/srv/eng/main.home). The GEO label is designed to communicate, and facilitate interrogation of, geospatial quality information with a view to supporting efficient and effective dataset selection on the basis of quality, trustworthiness and fitness for use. The GEO label which we propose was developed and evaluated according to a user-centred design (UCD) approach in order to maximise the likelihood of user acceptance once deployed. The resulting label is dynamically generated from producer metadata in ISO or FDGC format, and incorporates user feedback on dataset usage, ratings and discovered issues, in order to supply a highly informative summary of metadata completeness and quality. The label was easily incorporated into a community portal as part of the GEO Architecture Implementation Programme (AIP-6) and has been successfully integrated into a prototype extension of the GEOSS portal, as well as the popular metadata catalog and editor, GeoNetwork. The design of the GEO label was based on 4 user studies conducted to: (1) elicit initial user requirements; (2) investigate initial user views on the concept of a GEO label and its potential role; (3) evaluate prototype label visualizations; and (4) evaluate and validate physical GEO label prototypes. The results of these studies indicated that users and producers support the concept of a label with drill-down interrogation facility, combining eight geospatial data informational aspects, namely: producer profile, producer comments, lineage information, standards compliance, quality information, user feedback, expert reviews, and citations information. These are delivered as eight facets of a wheel-like label, which are coloured according to metadata availability and are clickable to allow a user to engage with the original metadata and explore specific aspects in more detail. To support this graphical representation and allow for wider deployment architectures we have implemented two Web services, a PHP and a Java implementation, that generate GEO label representations by combining producer metadata (from standard catalogues or other published locations) with structured user feedback. Both services accept encoded URLs of publicly available metadata documents or metadata XML files as HTTP POST and GET requests and apply XPath and XSLT mappings to transform producer and feedback XML documents into clickable SVG GEO label representations. The label and services are underpinned by two XML-based quality models. The first is a producer model that extends ISO 19115 and 19157 to allow fuller citation of reference data, presentation of pixel- and dataset- level statistical quality information, and encoding of 'traceability' information on the lineage of an actual quality assessment. The second is a user quality model (realised as a feedback server and client) which allows reporting and query of ratings, usage reports, citations, comments and other domain knowledge. Both services are Open Source and are available on GitHub at https://github.com/lushv/geolabel-service and https://github.com/52North/GEO-label-java. The functionality of these services can be tested using our GEO label generation demos, available online at http://www.geolabel.net/demo.html and http://geoviqua.dev.52north.org/glbservice/index.jsf

The Use of Retinal Microvascular Function and Telomere Length in Age and Blood Pressure Prediction in Individuals with Low Cardiovascular Risk

Ageing represents a major risk factor for many pathologies that limit human lifespan, including cardiovascular diseases. Biological ageing is a good biomarker to assess early individual risk for CVD. However, finding good measurements of biological ageing is an ongoing quest. This study aims to assess the use retinal microvascular function, separate or in combination with telomere length, as a predictor for age and systemic blood pressure in individuals with low cardiovascular risk. In all, 123 healthy participants with low cardiovascular risk were recruited and divided into three groups: group 1 (less than 30 years old), group 2 (31-50 years old) and group 3 (over 50 years old). Relative telomere length (RTL), parameters of retinal microvascular function, CVD circulatory markers and blood pressure (BP) were measured in all individuals. Symbolic regression- analysis was used to infer chronological age and systemic BP measurements using either RTL or a combination of RTL and parameters for retinal microvascular function. RTL decreased significantly with age ( = 0.010). There were also age-related differences between the study groups in retinal arterial time to maximum dilation ( = 0.005), maximum constriction ( = 0.007) and maximum constriction percentage ( = 0.010). In the youngest participants, the error between predicted versus actual values for the chronological age were smallest in the case of using both retinal vascular functions only ( = 0.039) or the combination of this parameter with RTL ( = 0.0045). Systolic BP was better predicted by RTL also only in younger individuals ( = 0.043). The assessment of retinal arterial vascular function is a better predictor than RTL for non-modifiable variables such as age, and only in younger individuals. In the same age group, RTL is better than microvascular function when inferring modifiable risk factors for CVDs. In older individuals, the accumulation of physiological and structural biological changes makes such predictions unreliable

Effects of Fluids on the Macro- and Microcirculations.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2018. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2018. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901