Modelling Requirements for Content Recommendation Systems

This paper addresses the modelling of requirements for a content Recommendation System (RS) for Online Social Networks (OSNs). On OSNs, a user switches roles constantly between content generator and content receiver. The goals and softgoals are different when the user is generating a post, as opposed as replying to a post. In other words, the user is generating instances of different entities, depending on the role she has: a generator generates instances of a "post", while the receiver generates instances of a "reply". Therefore, we believe that when addressing Requirements Engineering (RE) for RS, it is necessary to distinguish these roles clearly. We aim to model an essential dynamic on OSN, namely that when a user creates (posts) content, other users can ignore that content, or themselves start generating new content in reply, or react to the initial posting. This dynamic is key to designing OSNs, because it influences how active users are, and how attractive the OSN is for existing, and to new users. We apply a well-known Goal Oriented RE (GORE) technique, namely i-star, and show that this language fails to capture this dynamic, and thus cannot be used alone to model the problem domain. Hence, in order to represent this dynamic, its relationships to other OSNs' requirements, and to capture all relevant information, we suggest using another modelling language, namely Petri Nets, on top of i-star for the modelling of the problem domain. We use Petri Nets because it is a tool that is used to simulate the dynamic and concurrent activities of a system and can be used by both practitioners and theoreticians.Comment: 28 pages, 7 figure

Political attention to environmental issues: Analyzing policy punctuations in the Netherlands

One of the most dramatized features in Al Gore's movie The Inconvenient Truth is the effects of a rising sea-level in the Netherlands. The film is an example of how the mobilization of bias in the Netherlands resulted in sudden high levels of attention for climate change problems. We analyze agenda setting on Dutch environmental policy, using various policy issue datasets about parliamentary activities, media, and expert organizations and focusing on the interrelations between these policy venues. All datasets are coded by the same topic codebook. The findings show that interest in environmental issues is largely determined by the state of the economy, unexpected incidents, and the competition for attention with other issues in the political arena. We show that political interest in environmental issues has initially been flagging, since the environment was mostly seen as a European topic, and Europe has not been popular since the referendum on a European Constitution. However, once the climate change problem was translated to a national problem, popular attention increased enormously. We conclude that climate change framed as a European problem does not increase attention, nationalization of the problem does

Managing construction workers and their tacit knowledge in a knowledge environment: A conceptual framework

Within the construction industry, it is increasingly being acknowledged that knowledge management can bring about the much needed innovation and improved performance the industry requires. Nevertheless, sufficient attention is still to be received for the concept of the knowledge worker and their tacit knowledge within construction industry. Yet, proper understanding and management of this resource is of immense importance for the achievement of better organisational performance. Hence, this paper aims to devise a theoretical framework for managing construction knowledge worker and their tacit knowledge based on review and synthesis of literature. Paper stresses the importance of construction knowledge worker and tacit knowledge through review of literature and highlights prevailing gap due to lack of attention and recognition given to the tacit knowledge in the construction industry. Based on identified gap research aim, objectives and hypotheses are devised. As the specific research methodology, the social constructionism stance in terms of epistemological undertakings and idealistic approach under the ontological assumptions with value laden purposes are suggested. Further, it recommends the deployment of multiple exploratory case studies approach with triangulation techniques

Goal-oriented requirements engineering: an extended systematic mapping study.

Over the last two decades, much attention has been paid to the area of goal-oriented requirements engineering (GORE), where goals are used as a useful conceptualization to elicit, model, and analyze requirements, capturing alternatives and conflicts. Goal modeling has been adapted and applied to many sub-topics within requirements engineering (RE) and beyond, such as agent orientation, aspect orientation, business intelligence, model-driven development, and security. Despite extensive efforts in this field, the RE community lacks a recent, general systematic literature review of the area. In this work, we present a systematic mapping study, covering the 246 top-cited GORE-related conference and journal papers, according to Scopus. Our literature map addresses several research questions: we classify the types of papers (e.g., proposals, formalizations, meta-studies), look at the presence of evaluation, the topics covered (e.g., security, agents, scenarios), frameworks used, venues, citations, author networks, and overall publication numbers. For most questions, we evaluate trends over time. Our findings show a proliferation of papers with new ideas and few citations, with a small number of authors and papers dominating citations; however, there is a slight rise in papers which build upon past work (implementations, integrations, and extensions). We see a rise in papers concerning adaptation/variability/evolution and a slight rise in case studies. Overall, interest in GORE has increased. We use our analysis results to make recommendations concerning future GORE research and make our data publicly available

Advancing functional connectivity research from association to causation

Cognition and behavior emerge from brain network interactions, such that investigating causal interactions should be central to the study of brain function. Approaches that characterize statistical associations among neural time series-functional connectivity (FC) methods-are likely a good starting point for estimating brain network interactions. Yet only a subset of FC methods ('effective connectivity') is explicitly designed to infer causal interactions from statistical associations. Here we incorporate best practices from diverse areas of FC research to illustrate how FC methods can be refined to improve inferences about neural mechanisms, with properties of causal neural interactions as a common ontology to facilitate cumulative progress across FC approaches. We further demonstrate how the most common FC measures (correlation and coherence) reduce the set of likely causal models, facilitating causal inferences despite major limitations. Alternative FC measures are suggested to immediately start improving causal inferences beyond these common FC measures

Tacit knowledge generation and utilisation in the construction industry

The importance of knowledge as a key determinant of organisational competitiveness and better performance is increasingly appreciated by both academics and practitioners. However, the concept of tacit knowledge still lacks sufficient attention within the construction industry, despite the fact that proper understanding and management of this resource is of immense importance for the achievement of better organisational performance. As the initial step towards the management of tacit knowledge, this paper examines the factors affecting tacit knowledge generation and utilisation in the construction industry. The study integrates theories of experiential learning, cognitive science and knowledge creation, in order to articulate the process of tacit knowledge generation and utilisation. The exploratory phase of the case study identified several factors affecting tacit knowledge generation and utilisation in an organisational context in terms of Individual level: Intra-personal drivers; Group level: Inter-personal drivers; and Organisational level: Situational drivers