A Web-Based Tool for Analysing Normative Documents in English

Our goal is to use formal methods to analyse normative documents written in English, such as privacy policies and service-level agreements. This requires the combination of a number of different elements, including information extraction from natural language, formal languages for model representation, and an interface for property specification and verification. We have worked on a collection of components for this task: a natural language extraction tool, a suitable formalism for representing such documents, an interface for building models in this formalism, and methods for answering queries asked of a given model. In this work, each of these concerns is brought together in a web-based tool, providing a single interface for analysing normative texts in English. Through the use of a running example, we describe each component and demonstrate the workflow established by our tool

Ontological Engineering: What are Ontologies and How Can We Build Them?

Ontologies are formal, explicit specifications of shared conceptualizations. There is much literature on what they are, how they can be engineered and where they can be used inside applications. All these literature can be grouped under the term “Ontological Engineering,” which is defined as the set of activities that concern the ontology development process, the ontology lifecycle, the principles, methods and methodologies for building ontologies, and the tool suites and languages that support them. In this chapter we provide an overview of Ontological Engineering, describing the current trends, issues and problem

Thermal conditions of buildings: mathematical modeling by power circuit theory

The object of this study is to produce a mathematical model for heat conditions in a building, expressed as a complex power circuit. The building is characterized as a power circuit, complete with a detailed description of those components responsible for heat loss, using formal methods to make circuit calculations. Representing a building as a power circuit provides a powerful mathematical modelling tool for assessing heat processes (heat conditions) in separate rooms and in the building in a whole

Decision trees in epidemiological research

Background: In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods. Main text: We review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART) technique and the newer Conditional Inference tree (CTree) technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees. Conclusions: Decision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation

A goal-based approach to policy refinement

As the interest in using policy-based approaches for systems management grows, it is becoming increasingly important to develop methods for performing analysis and refinement of policy specifications. Although this is an area that researchers have devoted some attention to, none of the proposed solutions address the issue of deriving implementable policies from high-level goals. A key part of the solution to this problem is having the ability to identify the operations, available on the underlying system, which can achieve a given goal. This paper presents an approach by which a formal representation of a system, based on the Event Calculus, can be used in conjunction with abductive reasoning techniques to derive the sequence of operations that will allow a given system to achieve a desired goal. Additionally it outlines how this technique might be used for providing tool support and partial automation for policy refinement. Building on previous work on using formal techniques for policy analysis, the approach presented here applies a transformation of both policy and system behaviour specifications into a formal notation that is based on Event Calculus. Finally, it shows how the overall process could be used in conjunction with UML modelling and illustrates this by means of an example. 1

Lessons from implementing INFFER with regional catchment management organisations

Investment in natural resource management (NRM) by regional organisations in Australia has been widely criticised for failing to achieve substantial environmental outcomes. The Investment Framework for Environmental Resources (INFFER) is a tool for developing and prioritising projects to address environmental issues such as water quality and biodiversity decline, environmental pest impacts and land degradation. It aims to achieve the most valuable environmental outcomes with the available resources. During 2008 and 2009 INFFER has been implemented with a number of catchment management organisations (CMOs) throughout Australia. In this paper, we report on lessons from and implications of this experience. Data on implementation were collected in formal and informal ways from staff of organisations that were using INFFER and state agencies, including: an on-line survey, benchmarking questions at training workshops, a formal on-going monitoring and evaluation process tracking the use of INFFER by CMOs, and comments made in correspondence and informal feedback to the INFFER team. In this paper we describe issues that arise when implementing INFFER with regions and organisations, and how the INFFER team has attempted to address these. Key issues include a desire to consider the community as an asset and emphasise capacity building, a rejection of the need for targeted investment, and various difficulties associated with specific aspects of the Framework. Existing institutional arrangements, and the legacy of past institutional arrangements, remain serious barriers to the adoption of methods to improve environmental outcomes from NRM investment. A lack of rigour in investment planning has become accepted as the norm, and resistance to processes to improve rigour is common. However, many CMOs want to achieve better environmental outcomes with their limited funds, and we report on our efforts to work with them to achieve this by using INFFER.Research and Development/Tech Change/Emerging Technologies,

Teacher Evaluation: The Change We Wish to See; Improving the Formal Observation Process to Improve Student Learning

Teacher evaluation is a formal construct for improving instruction and student learning. Formal observations are a central component of that process. This change model explores the option of a videotaped observation model as an alternative to the current Illinois state-mandated in-person formal observation to increase teacher ownership, promote reflective practice and improve instructional practices. The evaluation process is a vehicle that promotes collaboration among building leaders and staff. The Illinois shift to a professional practice model provides a construct for a culture and climate that encourages reflection and promotes professional growth (Danielson, 2011; Darling-Hammond, 2013; Jay, 2003; Stuhlman, Hamre, Downer, & Pianta, n.d.). In examining practices related to evaluation and the formal observation, the idea is to build systems empowering teachers and focused on collaboration to promote reflection and professional growth (Myung & Martinez, 2013). The premise of the change model is to realize the context, culture, conditions and competencies that will reflect an effective system with a focus on student learning (Wagner & Kegan, 2006). Qualitative research methods were used to gain a deeper understanding of the teacher and administrator perceived value of the formal observation. Analyzing data from surveys and semi-structured interviews regarding the observation experience, the findings suggest that there is an opportunity to examine alternate structures for the formal observation to increase its value as a tool for professional growth. A further case study of the change model was conducted with three teachers and three administrators. Given responses to the case study coupled with the survey and interview data, I found there is merit to exploring how the videotaped alternative may contribute to an improved teacher evaluation process

An open extensible tool environment for Event-B

Abstract. We consider modelling indispensable for the development of complex systems. Modelling must be carried out in a formal notation to reason and make meaningful conjectures about a model. But formal modelling of complex systems is a difficult task. Even when theorem provers improve further and get more powerful, modelling will remain difficult. The reason for this that modelling is an exploratory activity that requires ingenuity in order to arrive at a meaningful model. We are aware that automated theorem provers can discharge most of the onerous trivial proof obligations that appear when modelling systems. In this article we present a modelling tool that seamlessly integrates modelling and proving similar to what is offered today in modern integrated development environments for programming. The tool is extensible and configurable so that it can be adapted more easily to different application domains and development methods.