Understanding the process of recovery from heroin addiction : initiating and maintaining factors

There is increasing recognition that recovery from heroin addiction is possible but there is limited understanding of the recovery process and of how services can support people in that process. At present, most of the research concerning recovery from heroin addiction comes from the United States where the treatment system is very different to that in the UK. This study aimed to gain a better understanding of the recovery process from the perspective of people who are in recovery from heroin addiction, with the aim of informing service development and delivery in the South Wales area. This study employed a grounded theory qualitative methodology to analyse data collected from ten interviews with people in recovery from heroin addiction in the South Wales area. The results revealed four core categories: i) initiating recovery, including the triggers for recovery and what helps; ii) maintaining recovery, consisting of thought changes, lifestyle changes and the role of supportive networks; iii) the reality of recovery, encompassing the process of recovery and obstacles faced; and iv) service provision, encompassing current problems, how support needs can be met and how wider needs can be addressed. The findings highlighted some important considerations for the development of services specifically designed to meet the needs of this client group, thus facilitating long term stable recovery. The findings are reviewed in relation to the wider literature regarding recovery from heroin addiction. Implications for clinical practice and service delivery are also reviewed, and suggestions provided for how services can incorporate recovery-orientated principles. Suggestions for future research are also considered.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Representing Topological Relationships by Using 3D Objects: an Empirical Survey

In this paper we present a survey conducted in order to understand how simple 3D objects, named geometaphors, can be composed for building a model that permits to represent topological relationships in a 3D space. The research was conducted on twenty participants who were familiar with geographical information systems (GIS) and the notion of topological relationship. The subjects participating to the survey were asked to put in relation textual labels related to topological relationships with visual compositions of geometaphors pairs. The result is an interpretation model of the visual compositions that represents an important component for the building of visual query environments compliant with the users’ mental model, contributing therefore to augment significantly the usability of such systems

Representing Topological Relationships by Using 3D objects: An Empirical Survey

International audienceIn this paper we present a survey conducted in order to understand how simple 3D objects, named geometaphors, can be arranged for building a model permitting to represent topological relationships in a threedimensional space. The research was conducted on twenty participants who were familiar with geographical information systems (GIS) and the notion of topological relationship. The users participating to the survey were asked to put in relation textual labels related to topological relationships with visual arrangements of geometaphors pairs. While the results of the survey often show a convergence towards specific associations, in other cases users indicate a set of associations complementary to the main choice. Therefore, in order to reduce the ambiguity, the anwsers to the survey were filtered with a set of rules that take into consideration the priority of the relationships, the category of the geometaphors and the order they are selected; the result is an interpretation model of the visual arrangements that takes into account all the answers and, in particular, takes advantage of the set of complementary associations when the primary ones can’t be applied because they are not congruent with certain categories of geometries. Such model represents an important component for the building of visual query environments compliant with the users’ mental model, contributing therefore to augment significantly the usability of such systems

A Preliminary Study of Metrics and Methods for Readable Spatial OLAP Maps: VGI4Bio Case Study

International audienceSpatial OLAP systems are GeoBusiness Intelligence systems allowing the exploration and analysis of huge volume of spatial data by means of tabular, graphic and cartographic displays. Although map readability is crucial for decision-making processes, readability of SOLAP maps has not been deeply investigated. In this paper, a initial study on readability metrics for SOLAP maps and methods to improve them are presented and discussed. The results are validated by using a real case study concerning farmland biodiversity analysis. Some open issues associated to this topic are also discussed

Visualizing Geographical Information Through Tag Clouds

In the last decade, the need to support decision makers in solving problems related to a territory and its phenomena has stimulated Geographic Information Visualization (GeoVis) researchers to propose highly interactive visualization tools able to both synthesize information from large datasets and perform complex analytical tasks. The goal of the present paper is to propose a GeoVis method based on a recent InfoVis technique, known as Tag Cloud, which combines tag clouds with advanced GeoVis techniques for visualizing geographic data and related spatio-temporal phenomena. The method elaborates a simplified map containing a georeferenced cloud of tags, placed where the associated information is appropriate and significant. As initial result a system prototype has been realized in order to obtain an overview of data distribution and classification. It is focused on data extraction and aggregation, and output visualization, and adopts various techniques to allow users to select data to visualize starting from a geographic dataset

CONDIVIDERE IL PATRIMONIO CARTOGRAFICO TRAMITE UN SISTEMA BASATO SU UN CORE DI METADATI GEOGRAFICI

National audience

Comprehending geographic scenarios through visual summaries

In the last decade, the need to support decision makers in solving problems related to a territory and its phenomena has stimulated Geographic Information Visualization (GeoVis) researchers to propose highly interactive visualization tools able to both synthesize information from large datasets and perform complex analytical tasks. The goal of the present paper is to propose two GeoVis methods based on a recent InfoVis technique, known as Chorem and Tag Cloud, which combines advanced GeoVis techniques for visualizing and analyzing geographic data and related spatio-temporal phenomena. The methods elaborate a simplified maps in order to help to identify significant geospatial information, data, and knowledge by supporting analytical processes that join innate human abilities of vision and cognition with computer based visual interfaces. As initial result a system prototypes have been realized in order to obtain an overview of large dataset. They are focused on data extraction and aggregation, and output visualization, and adopt various techniques to allow users to select data to visualize starting from a geographic dataset

Querying Spatial and Temporal Data by Condition Tree: Two Examples Based on Environmental Issues

The need to perform complex analysis and decision making tasks has motivated growing interest in Geographic Information Systems (GIS) as a means to compare different scenarios and simulate the evolution of phenomena. However, data and function complexity may critically affect human interaction and system performances during planning and prevention activities. This is especially true when the scenarios of interest involve space or time in imprecise contexts. In this paper we propose a visual language which drives users to perform queries involving discrete objects by considering their temporal component. Moreover, in order to allow queries closer to the user mental model we add a specific hint for relaxing constraints and allowing fuzzy conditions. The visual language will be tested on two specific contexts concerning with the fire risk and the air pollution