Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Enhancing Software Project Outcomes: Using Machine Learning and Open Source Data to Employ Software Project Performance Determinants

Many factors can influence the ongoing management and execution of technology projects. Some of these elements are known a priori during the project planning phase. Others require real-time data gathering and analysis throughout the lifetime of a project. These real-time project data elements are often neglected, misclassified, or otherwise misinterpreted during the project execution phase resulting in increased risk of delays, quality issues, and missed business opportunities. The overarching motivation for this research endeavor is to offer reliable improvements in software technology management and delivery. The primary purpose is to discover and analyze the impact, role, and level of influence of various project related data on the ongoing management of technology projects. The study leverages open source data regarding software performance attributes. The goal is to temper the subjectivity currently used by project managers (PMs) with quantifiable measures when assessing project execution progress. Modern-day PMs who manage software development projects are charged with an arduous task. Often, they obtain their inputs from technical leads who tend to be significantly more technical. When assessing software projects, PMs perform their role subject to the limitations of their capabilities and competencies. PMs are required to contend with the stresses of the business environment, the policies, and procedures dictated by their organizations, and resource constraints. The second purpose of this research study is to propose methods by which conventional project assessment processes can be enhanced using quantitative methods that utilize real-time project execution data. Transferability of academic research to industry application is specifically addressed vis-à-vis a delivery framework to provide meaningful data to industry practitioners

Desertification

IPCC SPECIAL REPORT ON CLIMATE CHANGE AND LAND (SRCCL) Chapter 3: Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystem

Towards a global participatory platform: Democratising open data, complexity science and collective intelligence

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project's own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed. Graphical abstrac

Driving and Inhibiting Factors in the Adoption of Open Source Software in Organisations

The aim of this research is to investigate the extent to which Open Source Software (OSS) adoption behaviour can empirically be shown to be governed by a set of self-reported (driving and inhibiting) salient beliefs of key informants in a sample of organisations. Traditional IS adoption/usage theory, methodology and practice are drawn on. These are then augmented with theoretical constructs derived from IT governance and organisational diagnostics to propose an artefact that aids the understanding of organisational OSS adoption behaviour, stimulates debate and aids operational management interventions. For this research, a combination of quantitative methods (via Fisher’s Exact Test) and complimentary qualitative method (via Content Analysis) were used using self-selection sampling techniques. In addition, a combination of data and methods were used to establish a set of mixed-methods results (or meta-inferences). From a dataset of 32 completed questionnaires in the pilot study, and 45 in the main study, a relatively parsimonious set of statistically significant driving and inhibiting factors were successfully established (ranging from 95% to 99.5% confidence levels) for a variety for organisational OSS adoption behaviours (i.e. by year, by software category and by stage of adoption). In addition, in terms of mixed-methods, combined quantitative and qualitative data yielded a number of factors limited to a relatively small number of organisational OSS adoption behaviour. The findings of this research are that a relatively small set of driving and inhibiting salient beliefs (e.g. Security, Perpetuity, Unsustainable Business Model, Second Best Perception, Colleagues in IT Dept., Ease of Implementation and Organisation is an Active User) have proven very accurate in predicting certain organisational OSS adoption behaviour (e.g. self-reported Intention to Adopt OSS in 2014) via Binomial Logistic Regression Analysis

Privacy Leakage in Mobile Computing: Tools, Methods, and Characteristics

The number of smartphones, tablets, sensors, and connected wearable devices are rapidly increasing. Today, in many parts of the globe, the penetration of mobile computers has overtaken the number of traditional personal computers. This trend and the always-on nature of these devices have resulted in increasing concerns over the intrusive nature of these devices and the privacy risks that they impose on users or those associated with them. In this paper, we survey the current state of the art on mobile computing research, focusing on privacy risks and data leakage effects. We then discuss a number of methods, recommendations, and ongoing research in limiting the privacy leakages and associated risks by mobile computing

On History-Aware Multi-Activity Expertise Models

Durant l’évolution d’un projet de logiciel, les contributions individuelles d’un developeur present dans le projet vont lentement se faire remplacer par les contributions d’autre dévelopeurs. Ceci engendrera l’érosion de l’empreinte des contributions de ce developeur. Bien que les connaissances de ce dévelopeur n’ont pas disparu du jour au lendemain, pour une personne externe au projet, l’expertise de ce developeur est devenue invisible. Grace à une étude empirique sur une periode de 5 années de developement de Linux, nous étudions le phénomène de l’érosion de l’expertise en créant un modèle bidimentionnel. La première dimention de notre modèle prend en compte les différentes activités entreprises par les membres de la communauté de développement de Linux, comme les contributions en termes de code, les contributions aux revues de code soumit par d’autre dévelopeurs, ou encore la soumission de code d’autres dévelopeurs en amont. La deuxiéme dimention de notre modèle prend en compte l’historique des contributions citées plus haut pour chaque dévelopeurs. En applicant ce modèle, nous decouvrons que, bien que les empreintes de contributions de certain dévelopeurs diminuent avec le temps, leurs expertise survit grace à leurs implications dans les divereses activités mentionées plus haut.----------ABSTRACT: As software evolves, a maintainer’s contributions will gradually vanish as they are being replaced by other developers’ code, resulting in a slow erosion of the maintainer’s footprint in the software project. Even though this maintainer’s knowledge of the file did not disappear overnight, to outsiders, the maintainer and her expertise have become invisible. Through an empirical study on 5 years of Linux development history, this paper analyses this phenomenon of expertise erosion by building a 2-dimensional model of maintainer expertise involving a range of maintainer activity data on more than one release. Using these models, we found that although many Linux maintainers’ own coding footprint has regressed over time, their expertise is perpetuated through involvement in other development activities such as patch reviews and committing upstream on behalf of other developers. Considering such activities over time further improves recommendation models

Local and regional desertification indicators in a global perspective: Seminar proceedings

This volume contains the proceedings of the International Seminar on Local and Regional Desertification Indicators in a Global Perspective held in Beijing, China, in May 2005. Aim of the seminar was to provide a precious opportunity to exchange information and experiences about the identification and use of desertification B&I among representatives of UNCCD Annexes, while contributing to strengthen linkages among them and exploring possible synergies. The seminar was organised in the framework of the AIDCCD project (Active Exchange of Experiences on Indicators and Development of Perspective in the Context of UNCCD), aiming at developing and co-ordinating exchange of experience across the world among institutions involved in the implementation of the UNCCD regional Annexes

Predicting Software Revision Outcomes on Github Using Structural Holes Theory

Many software repositories are hosted publicly online via social platforms. Online users contribute to the software projects not only by providing feedback and suggestions, but also by submitting revisions to improve the software quality. This study takes a close look at revisions and examines the impact of social media networks on the revision outcome. A novel approach with a mix of different research methods (e.g., ego-centric social network analysis, structural holes theory and survival analysis) is used to build a comprehensible model to predict the revision outcome. The predictive performance is validated using real life datasets obtained from GitHub, the social coding website, which contains 32,962 pull requests to submit revisions, 20,399 distinctive software project repositories, and a social network of 234,322 users. Good predictive performance has been achieved with an average AUC of 0.84. The results suggest that a repository host's position in the ego network plays an important role in determining the duration before a revision is accepted. Specifically, hosts that are positioned in between densely connected social groups are likely to respond more quickly to accept the revisions. The study demonstrates that online social networks are vital to software development and advances the understanding of collaboration in software development research. The proposed method can be applied to support decision making in software development to forecast revision duration. The result also has several implications for managing project collaboration using social media