Pragmatic but Principled: Background report on Integrated Water Resource Management

IWRM is about integrated and "joined-up" management. It is about promoting integration across sectors, applications, groups in society and time, based upon an agreed set of principles. IWRM has been widely applied and aims for more coordinated use of land and water and is divided into full (wholly integrated activities) and light (applying the principles at the local level). The main criticisms of IWRM are the failure to translate the theory into action and the lack of change on the ground. There is a need for both light and full IWRM, but future projects need to increase participation and engagement.Water and Sanitation for the Urban Poo

User interaction and uptake challenges to successfully deploying Semantic Web technologies

The Semantic Web community could benefit greatly from 'eating its own dog food' in order to better understand the challenges and opportunities of a Semantic Web from the user perspective. In this paper we describe the deployment of Semantic Web applications and services at the 3rd European Semantic Web Conference (ESWC2006), before presenting results of an evaluation into how these technologies were experienced by delegates. Based on themes identified in the evaluation we highlight seven user interaction and uptake challenges raised by the conference experience, and discuss how these may generalize to the widespread deployment of Semantic Web technologies

Computing word-of-mouth trust relationships in social networks from Semantic Web and Web 2.0 data sources

Social networks can serve as both a rich source of new information and as a filter to identify the information most relevant to our specific needs. In this paper we present a methodology and algorithms that, by exploiting existing Semantic Web and Web2.0 data sources, help individuals identify who in their social network knows what, and who is the most trustworthy source of information on that topic. Our approach improves upon previous work in a number of ways, such as incorporating topic-specific rather than global trust metrics. This is achieved by generating topic experience profiles for each network member, based on data from Revyu and del.icio.us, to indicate who knows what. Identification of the most trustworthy sources is enabled by a rich trust model of information and recommendation seeking in social networks. Reviews and ratings created on Revyu provide source data for algorithms that generate topic expertise and person to person affinity metrics. Combining these metrics, we are implementing a user-oriented application for searching and automated ranking of information sources within social networks

Linked Data - the story so far

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward

Information-seeking on the Web with Trusted Social Networks - from Theory to Systems

This research investigates how synergies between the Web and social networks can enhance the process of obtaining relevant and trustworthy information. A review of literature on personalised search, social search, recommender systems, social networks and trust propagation reveals limitations of existing technology in areas such as relevance, collaboration, task-adaptivity and trust. In response to these limitations I present a Web-based approach to information-seeking using social networks. This approach takes a source-centric perspective on the information-seeking process, aiming to identify trustworthy sources of relevant information from within the user's social network. An empirical study of source-selection decisions in information- and recommendation-seeking identified five factors that influence the choice of source, and its perceived trustworthiness. The priority given to each of these factors was found to vary according to the criticality and subjectivity of the task. A series of algorithms have been developed that operationalise three of these factors (expertise, experience, affinity) and generate from various data sources a number of trust metrics for use in social network-based information seeking. The most significant of these data sources is Revyu.com, a reviewing and rating Web site implemented as part of this research, that takes input from regular users and makes it available on the Semantic Web for easy re-use by the implemented algorithms. Output of the algorithms is used in Hoonoh.com, a Semantic Web-based system that has been developed to support users in identifying relevant and trustworthy information sources within their social networks. Evaluation of this system's ability to predict source selections showed more promising results for the experience factor than for expertise or affinity. This may be attributed to the greater demands these two factors place in terms of input data. Limitations of the work and opportunities for future research are discussed

Revyu: Linking reviews and ratings into the Web of Data

Revyu is a live, publicly accessible reviewing and rating Web site, designed to be usable by humans whilst transparently generating machine-readable RDF metadata for the Semantic Web, based on user input. The site uses Semantic Web specifications such as RDF and SPARQL, and the latest Linked Data best practices to create a major node in a potentially Web-wide ecosystem of reviews and related data. Throughout the implementation of Revyu design decisions have been made that aim to minimize the burden on users, by maximizing the reuse of external data sources, and allowing less structured human input (in the form of Web 2.0-style tagging) from which stronger semantics can later be derived. Links to external sources such as DBpedia are exploited to create human-oriented mashups at the HTML level, whilst links are also made in RDF to ensure Revyu plays a first class role in the blossoming Web of Data. In this paper we document design decisions made during the implementation of Revyu, discuss the techniques used for linking Revyu data with external sources, and outline how data from the site is being used to infer the trustworthiness of reviewers as sources of information and recommendations

Softly Thro\u27 The Summer Night : Juliska & Laczi

https://digitalcommons.library.umaine.edu/mmb-vp/2477/thumbnail.jp

Ha - za - zaa

https://digitalcommons.library.umaine.edu/mmb-vp/3606/thumbnail.jp

A timeline analysis of Open Data development in the UK

In this paper, we conceptualize Open Data ecosystems by analysing the major stakeholders in the UK. The conceptualization is based on a review of popular Open Data definitions and business ecosystem theories, which we applied to empirical data using a timeline analysis. Our work is informed by a combination of discourse analysis and in-depth interviews, undertaken during the summer of 2013. Drawing on the UK as a best practice example, we identify a set of structural business ecosystem properties: circular flow of resources, sustainability, demand that encourages supply, and dependence developing between suppliers, intermediaries, and users. However, significant gaps and shortcomings are found to remain. Most prominently, demand is not yet fully encouraging supply and actors have yet to experience fully mutual interdependence