Knowledge Components and Methods for Policy Propagation in Data Flows

Data-oriented systems and applications are at the centre of current developments of the World Wide Web (WWW). On the Web of Data (WoD), information sources can be accessed and processed for many purposes. Users need to be aware of any licences or terms of use, which are associated with the data sources they want to use. Conversely, publishers need support in assigning the appropriate policies alongside the data they distribute. In this work, we tackle the problem of policy propagation in data flows - an expression that refers to the way data is consumed, manipulated and produced within processes. We pose the question of what kind of components are required, and how they can be acquired, managed, and deployed, to support users on deciding what policies propagate to the output of a data-intensive system from the ones associated with its input. We observe three scenarios: applications of the Semantic Web, workflow reuse in Open Science, and the exploitation of urban data in City Data Hubs. Starting from the analysis of Semantic Web applications, we propose a data-centric approach to semantically describe processes as data flows: the Datanode ontology, which comprises a hierarchy of the possible relations between data objects. By means of Policy Propagation Rules, it is possible to link data flow steps and policies derivable from semantic descriptions of data licences. We show how these components can be designed, how they can be effectively managed, and how to reason efficiently with them. In a second phase, the developed components are verified using a Smart City Data Hub as a case study, where we developed an end-to-end solution for policy propagation. Finally, we evaluate our approach and report on a user study aimed at assessing both the quality and the value of the proposed solution

A series of case studies to enhance the social utility of RSS

RSS (really simple syndication, rich site summary or RDF site summary) is a dialect of XML that provides a method of syndicating on-line content, where postings consist of frequently updated news items, blog entries and multimedia. RSS feeds, produced by organisations or individuals, are often aggregated, and delivered to users for consumption via readers. The semi-structured format of RSS also allows the delivery/exchange of machine-readable content between different platforms and systems. Articles on web pages frequently include icons that represent social media services which facilitate social data. Amongst these, RSS feeds deliver data which is typically presented in the journalistic style of headline, story and snapshot(s). Consequently, applications and academic research have employed RSS on this basis. Therefore, within the context of social media, the question arises: can the social function, i.e. utility, of RSS be enhanced by producing from it data which is actionable and effective? This thesis is based upon the hypothesis that the fluctuations in the keyword frequencies present in RSS can be mined to produce actionable and effective data, to enhance the technology's social utility. To this end, we present a series of laboratory-based case studies which demonstrate two novel and logically consistent RSS-mining paradigms. Our first paradigm allows users to define mining rules to mine data from feeds. The second paradigm employs a semi-automated classification of feeds and correlates this with sentiment. We visualise the outputs produced by the case studies for these paradigms, where they can benefit users in real-world scenarios, varying from statistics and trend analysis to mining financial and sporting data. The contributions of this thesis to web engineering and text mining are the demonstration of the proof of concept of our paradigms, through the integration of an array of open-source, third-party products into a coherent and innovative, alpha-version prototype software implemented in a Java JSP/servlet-based web application architecture

30th International Conference on Information Modelling and Knowledge Bases

Information modelling is becoming more and more important topic for researchers, designers, and users of information systems. The amount and complexity of information itself, the number of abstraction levels of information, and the size of databases and knowledge bases are continuously growing. Conceptual modelling is one of the sub-areas of information modelling. The aim of this conference is to bring together experts from different areas of computer science and other disciplines, who have a common interest in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. We also aim to recognize and study new areas on modelling and knowledge bases to which more attention should be paid. Therefore philosophy and logic, cognitive science, knowledge management, linguistics and management science are relevant areas, too. In the conference, there will be three categories of presentations, i.e. full papers, short papers and position papers

Operational Risk and Reputation in Financial Institutions: Does Media Tone Make a Difference?

Operational risk announcements are unexpected adverse media news that potentially harm the reputation of financial institutions. This paper examines the equity-based and debt-based reputational effects of financial sentiment tones in operational risk announcements and shows how such reputational effects are moderated by alternative sources of public information. Our analysis reveals that the net negative tone and litigious tone have adverse reputational effects, and the uncertainty tone mitigates the adverse reputational impact. Additionally, alternative, simultaneous sources of information neutralize the reputational effects of textual tones. First, third-party information about the event (i.e. regulatory announcements and final settlements) dissolves the favorable (adverse) reputational impact of the uncertainty tone (litigious tone). Second, loss amount disclosure and firm recognition substitute the reputational effects of the net negative tone and uncertainty tone only in Anglo-Saxon countries and market-based economies. Overall, our findings indicate that the reputational effects of the media materialize most when there is lack of certain, quantifiable and regulated public information about the operational risk event

The Role of Referrals in New Client Capture Within the Field of Independent Financial Advice

The field of regulated financial services has been ill-served by marketing theory. As a consequence: (1) the nature of marketing in this sector has been misunderstood; (2) the key mechanism for generating new business in the field, namely, referrals, has been the subject of serious misapprehension; and, (3) the guidance offered to practitioners has been negligible. In particular, the role of the independent financial advisor (IFA) appears to have been conceptualised as a sales role, and the nature of the relationship between the IFA and the client has been addressed as though it were a straightforward buyer-seller relationship, with the IFA selling products to the client. It is unlikely that these conceptualisations were ever satisfactory and following recent regulatory changes in the sector they have become even less relevant. Since January 1st 2013 commission-based selling of financial investment products to consumers has been prohibited so that independent financial advice has become largely a fee-based service. The focus of this research is on referrals as a method of generating new business; the research context is the UK independent financial advice industry. The objectives of the study are to: (1) define and conceptualise referrals in the context of the financial advice industry; (2) develop a framework of the referral process; (3) provide practitioners with empirical evidence in connection with their embedded beliefs about referrals in this industry; (4) explore whether (as many practitioner believe) it is possible to actively manage referral generation within a financial advice business; and, (5) to investigate the importance of referrals as a means of generating new business for advisors. It was found that practitioners believe they influence referrals in four main ways: excellent service, higher qualifications, contact frequency and speed of response. However the results of this study clearly indicate that referrals are not the outcome of agency; they are a random occurrence, determined by happenstance and the result of an opportunist conversation between a prospect and a client. In turn, contrary to the advice of consultancy providers, asking for referrals was found to be ineffective and not welcomed by consumers. While word-of-mouth (WOM) often instigates referral generation, the value of WOM, needs be treated with caution, since consumers were found to have limited understanding of the service provided by independent advisors. Despite the importance consumers attribute to investment performance practitioners do not, commonly, provide investment benchmarks nor do consumers use analytical tools to assess the performance of their advisor. The absence of performance measures connects with the finding that practitioners have difficulty in describing what they do hence consumers are uncertain how to describe the service and what to say about it when asked