Modelling with stakeholders within a development project

This paper brings forth the experiences and lessons of implementing a participatory modelling process, the Companion Modelling (ComMod) approach, to a natural resource management system in the province of Palawan, Philippines. In this study, we explore the added value of using ComMod in a research and development project, and then we describe the actual modelling process, which includes the use of multiple methods for its evaluation, namely, workshop evaluation exercises, criteria & indicators for the project and the ComMod evaluation protocol. We use the lessons of this evaluation to assess the organisational learning and discuss the role of the modelling process within the development project.     

Engaging construction stakeholders with sustainability through a knowledge harvesting platform

With the new regulations and policies related to climate change, the construction industry has been put under pressure to increase the sustainability of its practices. Many organisations are now adapting their practices to meet government legislative targets (e.g. reducing carbon emissions) and consider the environmental, social and economic performance of buildings. In addition, the sustainable construction is also a rapidly changing field, with technological advances, changes in legislation and increasingly educated clients driving the industry to constantly adapt to remain competitive. This represents a key problem for construction professionals as they must continually be aware of new information, best practices, technologies and changing legislation (at a local, national and international level) which are often disseminated from different organisations/individuals through dispersed media.     

Understanding project sociology by modeling stakeholders

We have been collaborating on ways to improve how we involve stakeholders in projects. Here, we summarize the approach we've been taking to discover the right stakeholders and maintain their involvement. All the projects that we work on seem to have one thing in common: developers are concerned about the difficulty of involving the right stakeholders to discover, specify, and test requirements. We ran the stakeholder concerns survey to better understand what people mean when they say, "We have a problem with our stakeholders." We asked each participant to choose one stakeholder concern that causes the biggest problem in his or her environment. The objective was to discover which concerns are the most frequent and where we should focus our improvement efforts. Missing stakeholders result in missing requirements and escalating project costs. Once we've analyzed our project using a combination of onion models and stakeholder analysis templates, our project sociology modes become a tool for monitoring the continuing involvement of the appropriate stakeholders and dealing with changes.     

Modelling multiple inheritance with colimits

A categorical semantics of multiple inheritance is presented, in which the inheritance relations between program entities are represented as commutative diagrams in a suitable category, and multiple inheritance is then modelled with colimits of such diagrams. It is shown that the informal semantics of multiple inheritance used in existing object-oriented programming languages conforms to, or is consistent with, this model.     

Structural Modelling with Sparse Kernels

A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A number of new concepts and algorithms have been introduced by researchers to address this problem. They focus primarily on determining which inputs are relevant in predicting the output. This work describes a transparent, advanced non-linear modelling approach that enables the constructed predictive models to be visualised, allowing model validation and assisting in interpretation. The technique combines the representational advantage of a sparse ANOVA decomposition, with the good generalisation ability of a kernel machine. It achieves this by employing two forms of regularisation: a 1-norm based structural regulariser to enforce transparency, and a 2-norm based regulariser to control smoothness. The resulting model structure can be visualised showing the overall effects of different inputs, their interactions, and the strength of the interactions. The robustness of the technique is illustrated using a range of both artifical and real world datasets. The performance is compared to other modelling techniques, and it is shown to exhibit competitive generalisation performance together with improved interpretability.     

Modeling stakeholders for information systems design processes

In the software engineering area, stakeholders play a significant role in requirements elicitation and validation. Moreover, all the project management is integrally affected by stakeholders’ perspectives and their participation. This effect is strengthened when projects involve several organizations. Thus, a clear and explicit representation of the stakeholders and their attributes is required in order to achieve their effective management. The integration of this representation with other models capturing the knowledge of engineering design processes can be of great utility in software development projects. In this sense, this article describes the construction of an integrated model for representing stakeholders in information systems design processes. This proposal considers diverse attributes related to stakeholders and gives information for performing quantitative calculations about their interest and influence over the project. Thus, more inclusive experiences of the information systems development can be supported, even more if contexts with the participation of several organizations are considered.     

Large-scale group decision making with multiple stakeholders based on probabilistic linguistic preference relation

A large number of stakeholders take part in the process of decision making, namely, large-scale group decision making (LGDM) problems. Every stakeholder utilises a linguistic preference relation (LPR) to represent her/his preference information for alternatives. Then, a probabilistic LPR (PLPR) is established to represent the group preference. However, some stakeholders may only provide partial preference information about the alternatives. Thus, a PLPR with incomplete probabilities can be used to manage LGDM problems in complex environments. Based on the defined expected multiplicative consistency of PLPR, a probability computation model is established by mathematical programming to derive the missing probabilities of PLPR. In addition, an iterative algorithm to improve the consistency is proposed to obtain the PLPR with satisfactory consistency. Finally, a real-world investment decision-making problem with multiple stakeholders is solved to demonstrate the effectiveness of the proposed method.     

Improving the detection of requirements discordances among stakeholders

This paper introduces a technique to identify requirements discordances among stakeholders. This technique is validated in experiments. An extended version of the goal-oriented requirements elicitation method, named attributed goal-oriented analysis (AGORA), and its supporting tool are used. Two types of requirements discordances among stakeholders are defined: the first arises from the different interpretations by the stakeholders and the second is the result of different evaluations of preferences. Discordances are detected by the preference matrices in AGORA. Each preference matrix represents both preferences of each stakeholder and the estimated preferences of other stakeholders. A supporting tool for the AGORA method was developed. This tool is a groupware that seamlessly combines face-to-face meetings for goal elicitation and distributed individual sessions for scoring preference values. The experimental results showed that the proposed classification of discordances was sound and that the occurrences of the requirements discordances could be detected by preference matrices.     

Modelling Asynchrony with a Synchronous Model

The I/O automaton paradigm of Lynch and Tuttle models asynchrony through an interleaving parallel composition. The recognition that such interleaving models in fact can be viewed as special cases of synchronous parallel composition has been very limited. Let be any set of finite-state I/O automata drawing actions from a fixed finite set containing a subset . In this article we establish a translation T : to a class of -automata closed under a synchronous parallel composition, for which T is monotonic with respect to implementation relative to , and linear with respect to composition. Thus, for A¹, ..., A, B¹, ..., B and A = A¹ ... A, B = B¹ ... B, if is the set of actions common to both A and B, then A implements B (in the sense of I/O automata) if and only if the -automaton language containment (T(A¹) ... T(A)) (T(B¹) ... T(B)) obtains, where denotes the interleaving parallel composition on and denotes the synchronous parallel composition on . For the class , we use the L-process model of -automata. This result enables one to verify systems specified by I/O automata through model-checkers such as COSPAN or SMV, that operate on models with synchronous parallel composition. The translation technique generalizes to other interleaving models, although in each case, the translation map must match the specific model.     

Research stakeholders identification using an mobile agent's framework

In the business process of reengineering, one of the main problems consists in the organizational reintegration of the employee. New instruments for the automatic identification of stakeholders among existing staff evaluation are needed. It is difficult to identify a stakeholder, especially if we refer to science stakeholders, and the proper evaluation of a researcher's value and position at international level is needed. There are large contradictions concerning the validity of various types of indexing services and other techniques used to classify the researchers. This paper proposes the use of corporate Human Resource Management (HRM) specific instruments when it comes to the researcher as informational stakeholder identification. The main idea behind the method is to use some form of information retrieval techniques over a set of research papers which contain, mostly, the same key words and to extract the hierarchy of the researchers involved/referenced over that set. A distributed approach was used due to its inherent scalability. The use of an inference engine was also deemed necessary due to the complexity of the problem. The system may be used in the automatic assessment of research performance in public or private institutions. It can be easily modified to support complex sets of rules depending on each user's needs in personnel evaluation. The main research field of this papers concerns distributed artificial intelligence.     

Modelling relational statistics with Bayes Nets

Class-level models capture relational statistics over object attributes and their connecting links, answering questions such as “what is the percentage of friendship pairs where both friends are women?” Class-level relationships are important in themselves, and they support applications like policy making, strategic planning, and query optimization. We represent class statistics using Parametrized Bayes Nets (PBNs), a first-order logic extension of Bayes nets. Queries about classes require a new semantics for PBNs, as the standard grounding semantics is only appropriate for answering queries about specific ground facts. We propose a novel random selection semantics for PBNs, which does not make reference to a ground model, and supports class-level queries. The parameters for this semantics can be learned using the recent pseudo-likelihood measure (Schulte in SIAM SDM, pp. 462–473, 2011) as the objective function. This objective function is maximized by taking the empirical frequencies in the relational data as the parameter settings. We render the computation of these empirical frequencies tractable in the presence of negated relations by the inverse Möbius transform. Evaluation of our method on four benchmark datasets shows that maximum pseudo-likelihood provides fast and accurate estimates at different sample sizes.     

Modelling programmed frameshifting with frameshift machines

The translation of a messenger RNA into a functional protein is one of the most fundamental molecular processes in a cell. Groups of three ribonucleotides, called codons, uniquely specify amino acids to be used in the construction of a protein. When the translation process skips a number of bases it is possible for the reading frame of the RNA to be shifted. By making use of multiple reading frames, organisms and viruses are able to encode multiple proteins in a single gene. We propose here a formal model of these frameshifting events and investigate its basic mathematical properties and their relevance to biological systems. In addition, multiple time-efficient algorithms are created for use in the study of frameshifting. Some of these algorithms are created to work in general, for any type of frameshifting which could be found in organisms, while others are optimized for known specialized types of frameshifting.     

Modelling parallel databases with process algebra

With the current interest in using parallel computers as database servers to provide a scaleable parallel application which satisfies a real commercial need, there is a corresponding interest in performance prediction of parallel database systems. Both analytical and simulation approaches have been used and reported in the literature. This paper reports on an investigation into how a stochastic extension to classical process algebra (performance evaluation process algebra, PEPA) may be used for this purpose. This paradigm has a small but powerful set of elements which offers great flexibility for performance modelling. The paper describes how the approach has been adapted to handle database models, including the development of a technique, the decompositional approach, to handle the state-space explosion of parallel database models. It concludes with a comparison between the results obtained using this approach and those obtained using a different analytical approach.     

Security practitioners in context: Their activities and interactions with other stakeholders within organizations

This study investigates the context of interactions of information technology (IT) security practitioners, based on a qualitative analysis of 30 interviews and participatory observation. We identify nine different activities that require interactions between security practitioners and other stakeholders, and describe in detail two of these activities that may serve as useful references for security-tool usability scenarios. We propose a model of the factors contributing to the complexity of interactions between security practitioners and other stakeholders, and discuss how this complexity is a potential source of security issues that increase the risk level within organizations. Our analysis also reveals that the tools used by our participants to perform their security tasks provide insufficient support for the complex, collaborative interactions that their duties involve. We offer several recommendations for addressing this complexity and improving IT security tools.     

Cybercrime: Understanding and addressing the concerns of stakeholders

Cybercrime and cybercriminal activities continue to impact communities as the steady growth of electronic information systems enables more online business. The collective views of sixty-six computer users and organizations, that have an exposure to cybercrime, were analyzed using concept analysis and mapping techniques in order to identify the major issues and areas of concern, and provide useful advice. The findings of the study show that a range of computing stakeholders have genuine concerns about the frequency of information security breaches and malware incursions (including the emergence of dangerous security and detection avoiding malware), the need for e-security awareness and education, the roles played by law and law enforcement, and the installation of current security software and systems. While not necessarily criminal in nature, some stakeholders also expressed deep concerns over the use of computers for cyberbullying, particularly where younger and school aged users are involved. The government’s future directions and recommendations for the technical and administrative management of cybercriminal activity were generally observed to be consistent with stakeholder concerns, with some users also taking practical steps to reduce cybercrime risks.     

Modelling concurrency with comtraces and generalized comtraces

Comtraces (combined traces) are extensions of Mazurkiewicz traces that can model the “not later than” relationship. In this paper, we first introduce the novel notion of generalized comtraces, extensions of comtraces that can additionally model the “non-simultaneously” relationship. Then we study some basic algebraic properties and canonical representations of comtraces and generalized comtraces. Finally we analyze the relationship between generalized comtraces and generalized stratified order structures. The major technical contribution of this paper is a proof showing that generalized comtraces can be represented by generalized stratified order structures.     

Modelling large dynamical systems with industrial specifications

For a linear single-input, single-output time-invariant system, techniques for constructing a low-order model and modelling an approximate high-order model with industrial specifications are presented.

First, a second-order model with a phase-advance factor is established. Next, a. third-order model constructed with industrial specifications is illustrated. Finally, a method to construct an approximate high-order model from a low-order one via continued fraction technique is presented.