A Systemic Framework for Improving Clients\u27 Understanding of Software Requirements

This research proposes a systemic framework for the understanding of client requirements in Information System development that is particularly relevant for project contexts characterized by diversity of stakeholder values and significant complexity. In spite of the strong research tradition associated with Soft Systems Methodology and the growing interest in the Work System Method, the level of use of those by practitioners is not high as such situations require harnessing the strengths of more than one methodology. The paper explores the selection of techniques from three systems methodologies and mixing them to be applied in the process of requirements understanding by clients. The mixing of methods from various methodologies is justified through the principles of Critical Systems Practice and the process of their use is guided by Action Design Research. The contribution of the paper for the field of Information Systems is in the proposal of a more powerful framework for promoting organizational learning about software requirements understanding by clients

A new Systemic Taxonomy of Cyber Criminal activity

Cybercrime commonly refers to a broad range of different criminal activities that involve computers and information systems, either as primary tools or as primary targets. Cybercrime Science combines the methodology of Crime Science with the technology of Information Security. The few existing taxonomies of Cybercrime provide only general insights into the benefits of information structures; they are neither complete nor elaborated in a systemic manner to provide a proper framework guided by real system-principles. The main problem with such taxonomies is the inability to dynamically upgrade, which is why there is no timely cybersecurity actions. The current and past approaches were based mainly on the technical nature of cyberattacks and such approaches classified the impact of the activities from a criminological perspective. In this article, we present a systemic taxonomy of Cybercrime, based on definitions of the field items and the related data specifications. We develop a new method for estimating the fractal dimension of networks to explore a new taxonomy of Cybercrime activity. This method can serve to dynamically upgrade taxonomy and thus accelerate the prevention of cybercrime

Statistical signatures for adverse events in molecular life sciences

The ongoing evolution of computational sciences is helping to address the growing data analytical needs in applications. For instance, in biosciences, recent advances in measurement technologies have resulted in large amounts of data with domain-specific properties that are challenging to analyze with traditional statistical methods. An example of such a domain is microbiomics, the study of microbial communities, which in humans, have been reported to be associated with health and diseases. Despite advances in the field, further research is needed, as there is still a lack of understanding of how microbiome data should be processed and of the universal ecological properties of these complex systems. The objective of this thesis is to advance the field of microbiome data science by considering methods for predicting future outcomes based on current information. This is achieved through developing time series methods for complex systems and applying established statistical models in large population cohorts. The thesis consists of two complementary parts. The first part consists of analyses of two prospective human gut microbiome data sets, and contains the first ever microbiome-based survival analysis. The second part is focused on the stability properties of dynamical systems. It shows that the Bayesian statistical framework can be used to improve accuracy in inferring stability features, such as systemic resilience and early warning signals for catastrophic state transitions. The results of this thesis contribute to the best practices of human microbiomerelated data science and demonstrate the advantages of the Bayesian framework in detecting adverse events in limited time series. Although the work was motivated by timely questions in microbiomics, the developed tools are generic and applicable in various contexts

Systemic Risk in a Unifying Framework for Cascading Processes on Networks

We introduce a general framework for models of cascade and contagion processes on networks, to identify their commonalities and differences. In particular, models of social and financial cascades, as well as the fiber bundle model, the voter model, and models of epidemic spreading are recovered as special cases. To unify their description, we define the net fragility of a node, which is the difference between its fragility and the threshold that determines its failure. Nodes fail if their net fragility grows above zero and their failure increases the fragility of neighbouring nodes, thus possibly triggering a cascade. In this framework, we identify three classes depending on the way the fragility of a node is increased by the failure of a neighbour. At the microscopic level, we illustrate with specific examples how the failure spreading pattern varies with the node triggering the cascade, depending on its position in the network and its degree. At the macroscopic level, systemic risk is measured as the final fraction of failed nodes, $X^\ast$, and for each of the three classes we derive a recursive equation to compute its value. The phase diagram of $X^\ast$ as a function of the initial conditions, thus allows for a prediction of the systemic risk as well as a comparison of the three different model classes. We could identify which model class lead to a first-order phase transition in systemic risk, i.e. situations where small changes in the initial conditions may lead to a global failure. Eventually, we generalize our framework to encompass stochastic contagion models. This indicates the potential for further generalizations.Comment: 43 pages, 16 multipart figure

Developing professional recognition of systems thinking in practice: an interim report

The interim report on developing a competency framework for systems thinking in practice (STiP) provides a step towards possibly developing professional recognition of STiP. The report provides feedback to initial co-respondents involved with phase 1 of this wider inquiry, and provides a platform to a wider audience for initiating a second phase of the inquiry. The phase 1 study had the following objectives: 1. To scope relevant examples of work aimed at giving professional recognition to systems thinking 2. To capture some perspectives on the challenges and opportunities facing the task of giving profession recognition to systems thinking. Phase 2 of the wider inquiry aims to firstly consolidate the findings from phase 1 but also to focus more on moves towards collaborative modelling of a STiP competency framework. The research is carried out by members of the Applied Systems Thinking in Practice (ASTiP) Group at The Open University (UK) with funding from OU eSTEeM (OU Centre for STEM Pedagogy). The research team for phase 1 comprised of Rupesh Shah (Associate Lecturer), who carried out the core research activities, in collaboration with Martin Reynolds (Senior Lecturer) who is overseeing both phases of the wider inquiry, including support for reporting on research outcomes. The findings reported in sections 4, 5 and 6 remain largely unrefined and in sketch (bullet) form at this interim stage of reporting. The interim report comprises a brief background to the wider inquiry before outlining the approach taken to the phase 1 study. The findings are reported in relation to each of the two study objectives. Three themes arising from the study as identified by Rupesh are then discussed. Finally, some concluding ideas are presented for taking forward the outcomes from this study towards a second phase of the inquiry

Governance for sustainability: learning from VSM practice

Purpose – While there is some agreement on the usefulness of systems and complexity approaches to tackle the sustainability challenges facing the organisations and governments in the twenty-first century, less is clear regarding the way such approaches can inspire new ways of governance for sustainability. The purpose of this paper is to progress ongoing research using the Viable System Model (VSM) as a meta-language to facilitate long-term sustainability in business, communities and societies, using the “Methodology to support self-transformation”, by focusing on ways of learning about governance for sustainability. Design/methodology/approach – It summarises core self-governance challenges for long-term sustainability, and the organisational capabilities required to face them, at the “Framework for Assessing Sustainable Governance”. This tool is then used to analyse capabilities for governance for sustainability at three real situations where the mentioned Methodology inspired bottom up processes of self-organisation. It analyses the transformations decided from each organisation, in terms of capabilities for sustainable governance, using the suggested Framework. Findings – Core technical lessons learned from using the framework are discussed, include the usefulness of using a unified language and tool when studying governance for sustainability in differing types and scales of case study organisations. Research limitations/implications – As with other exploratory research, it reckons the convenience for further development and testing of the proposed tools to improve their reliability and robustness. Practical implications – A final conclusion suggests that the suggested tools offer a useful heuristic path to learn about governance for sustainability, from a VSM perspective; the learning from each organisational self-transformation regarding governance for sustainability is insightful for policy and strategy design and evaluation; in particular the possibility of comparing situations from different scales and types of organisations. Originality/value – There is very little coherence in the governance literature and the field of governance for sustainability is an emerging field. This piece of exploratory research is valuable as it presents an effective tool to learn about governance for sustainability, based in the “Methodology for Self-Transformation”; and offers reflexions on applications of the methodology and the tool, that contribute to clarify the meaning of governance for sustainability in practice, in organisations from different scales and types

Team 3: Exploring the relationship of systems research to systems literacy

In this paper, the Systems Research Team (SRT) details the activities and outcomes of the 2016 IFSR Conversation in Linz, Austria. The 2016 SRT includes: Mary Edson (team leader), Pam Buckle Henning, Tim Ferris, Andreas Hieronymi, Ray Ison, Gary Metcalf, George Mobus, Nam Nguyen, David Rousseau, and Shankar Sankaran, with guest team member, Peter Tuddenham, anchoring the endeavor in Systems Literacy. While the 2014 SRT’s focus was answering the question, “What distinguishes Systems Research from other types of research?” an internal focus intended to provide grounding for researchers new to the Systems Sciences, the 2016 SRT’s focus is on reaching out to a broader community in order to provide a foundation for Systems Literacy. The team’s Conversation revolved around the question, “How can Systems Research be in service to Systems Literacy?” The team’s discussions were directed into two essential aspects, separate and integrated, of this question. First, Systems Research serves Systems Literacy by providing a credible foundation for the principles and practices of Systems Science and Systems Thinking in both systematic and systemic modes. Second, Systems Research provides a neutral frame for development of ethical applications of those principles and practices. The SRT recognizes the exigency in providing foundational principles that can be effectively adopted and disseminated through Systems Literacy. The team’s narrative begins with an understanding the urgency for application of Systems Sciences and Systems Thinking to critical issues. Systems research, as with other types of research, is typically a slow generation of results; however, the body of knowledge gained through this process can be confidently used to address complexity in timely ways. The criticality of the need for salient approaches to complexity is shown in a graphic representation of some possible trajectories of applying or not applying these Systems principles in practice. The choice of how we respond to these issues relates to a process model that can be applied. Through understanding the relationship of the process model to the trajectory, the team directed its focus to developing a MindMap (Eppler, 2006) of eight essential aspects or features of how Systems Research can support Systems Literacy. These include: Systems Science knowledge base, roles and personas, maturity models, role profile, ontology/vocabulary, perspective/framing choice, frameworks, and political ecology. Each of these eight has its own process of unpacking, which was demonstrated to the Conversation participants by delving more deeply into the aspect of knowledge base. The eight relate to unpacking the Systems landscape in a coherent but loosely coupled investment portfolio (economic, social, and relational) for building systemic sensibility in such a way as to be dis/aggregated for different audiences. The week’s work culminated in a plan for “Looking Ahead,” which outlines the intentions of the SRT to continue its activities in support of Systems Literacy in the upcoming months. An example of this continued work is a workshop, “Toward Systems Literacy, the Role of Systems Research,” that was conducted at the 60th Meeting of the International Society for the Systems Sciences in Boulder, July 25, 2016

Systemic intervention for computer-supported collaborative learning

This paper presents a systemic intervention approach as a means to overcome the methodological challenges involved in research into computer-supported collaborative learning applied to the promotion of mathematical problem-solving (CSCL-MPS) skills in schools. These challenges include how to develop an integrated analysis of several aspects of the learning process; and how to reflect on learning purposes, the context of application and participants' identities. The focus of systemic intervention is on processes for thinking through whose views and what issues and values should be considered pertinent in an analysis. Systemic intervention also advocates mixing methods from different traditions to address the purposes of multiple stakeholders. Consequently, a design for CSCL-MPS research is presented that includes several methods. This methodological design is used to analyse and reflect upon both a CSCL-MPS project with Colombian schools, and the identities of the participants in that project

Co-guarantor attributes: a systemic approach to evaluating expert support

The paper suggests features of a generic framework which can assist in highlighting good practice as well as revealing shortcomings in expert support for management decision-making. Following the earlier writings of Habermas, I argue that expertise might be identified and considered as a set of �co-guarantor attributes� based upon knowledge constitutive interests. Co-guarantor attributes can be used as a benchmark for evaluation, where affirmative features of expert support can be identified as well as the incidence of �false guarantor� attributes which might be significant in perpetuating costly and unsuccessful intervention