Social Transparency in Enterprise Information Systems: Peculiarities and Assessment Factors

Social transparency within an organisation refers to the intentional sharing by individuals of information relating to themselves and their group to others in the workplace. This includes announcingpersonal interests, activity status, prioritiesandpersonal achievements. Such transparency is typically intendedto increase relatedness, motivation and trust amongst colleagues.Social networking features are being embedded within organisational information systems,allowing an online version of social transparency.An ad-hoc implementation of such transparency can poseissues such as information overload, motivating unwantedgrouping amongst colleagues and increasingpressureto perform in a certain manner. This results in organisational problems such asreduced productivity, unproductive competition and high turnover rates. Our ultimate aim isto address these issues by proposing an assessmentmethod for online social transparency to detect and minimise its negative impact on employees and organisations. In this paper, we report on empirical study results and present (1) a set of peculiarities of implementing online transparency in enterprise information systems and (2) a set of essential factors that relate to the assessment process

How analysts think: a preliminary study of human needs and demands for AI-based conversational agents

For conversational agents to provide benefit to intelligence analysis they need to be able to recognise and respond to the analysts intentions. Furthermore, they must provide transparency to their algorithms and be able to adapt to new situations and lines of inquiry. We present a preliminary analysis as a first step towards developing conversational agents for intelligence analysis: that of understanding and modeling analyst intentions so they can be recognised by conversational agents. We describe in-depth interviews conducted with experienced intelligence analysts and implications for designing conversational agent intentions using Formal Concept Analysis

e-Social Science and Evidence-Based Policy Assessment : Challenges and Solutions

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Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

The Political Economy of Fiscal Policy: Survey

This paper surveys the recent literature on the political economy of fiscal policy, in particular the accumulation of government debt. We examine three possible determinants of fiscal balances: opportunistic behavior by policymakers, heterogeneous fiscal preferences of either voters or politicians, and budget institutions. We focus on the contributions of the last 10 years and emphasize findings related to developing countries. We include a recent body of literature on the fiscal preferences of voters, which, interestingly, seems to suggest that voters do not favor high-spending governments. We also report some original empirical evidence. First, we test different hypotheses from the political economy literature in a simultaneous manner for a large set of both developed and developing countries. We find that less-fragmented governments and a greater ability of voters to monitor fiscal policy are related to lower deficits; the estimated effects are larger than when the two hypotheses are evaluated separately, as the existing literature does. Second, we suggest the role of the courts in the determination of fiscal policy as a promising new avenue of research, and present some suggestive novel evidence on the importance of this channel.

Research Objects: Towards Exchange and Reuse of Digital Knowledge

What will researchers be publishing in the future? Whilst there is little question that the Web will be the publication platform, as scholars move away from paper towards digital content, there is a need for mechanisms that support the production of self-contained units of knowledge and facilitate the publication, sharing and reuse of such entities.

 In this paper we discuss the notion of _research objects_, semantically rich aggregations of resources, that can possess some scientific intent or support some research objective. We present a number of principles that we expect such objects and their associated services to follow

An analysis of expertise in intelligence analysis to support the design of human-centered artificial intelligence

Intelligence analysis involves unpredictable processes and decision making about complex domains where analysts rely upon expertise. Artificial Intelligence (AI) systems could support analysts as they perform analysis tasks, to enhance their expertise. However, systems must also be cognisant about how expertise is gained and designed so that this is not impinged. In this paper, we describe the results of Cognitive Task Analysis interviews with 6 experienced intelligence analysts. We capture themes, in terms of their decision making paths during an analysis task, and highlight how each theme is both influenced by expertise and an influence upon expertise. We also identify important interdependencies between themes. We propose that our findings can be used to help design Human-Centered AI (HCAI) systems for supporting intelligence analysts

Integrated urban data visualising and decision-making framework

The work package (WP) 2 on Basic Exploration, Stakeholder Studies and Requirement Analysis created the scientific fundament of the project and produced essential knowledge for the conceptualisation of UrbanData2Decide. Task 2.5 brought together the previous research results and elaborated an integrated research model as well as a stakeholder requirements catalogue with first use case scenarios. In this integrated deliverable previous results of WP2 were combined to define a first blueprint for the UrbanData2Decide system as it will be developed later in the project

Implementing E-government Processes Distribution with Transparency using Multi-Agent Systems

E-government processes need transparency in order to allow citizens to understand and access valuable information in a democratic society. In this article, we present a multi-agent system (MAS) to process distribution that implements transparency characteristics. We demonstrate that the MAS paradigm stresses the organizational operating environment and the information systems alignment, being adequate to maintain process transparency. An agent-oriented software development methodology is used to define the soft goals of agents according to Tropos. The MAS architecture and the prototype were defined, implemented and illustrated with lawsuits distribution data from the Superior Labor Court of Brazil