An objective, niche-based approach to indicator species selection

1. Species-based indices are frequently employed as surrogates for wider biodiversity health and measures of environmental condition. Species selection is crucial in determining an indicators metric value and hence the validity of the interpretation of ecosystem condition and function it provides, yet an objective process to identify appropriate indicator species is frequently lacking. 2. An effective indicator needs to (i) be representative, reflecting the status of wider biodiversity; (ii) be reactive, acting as early-warning systems for detrimental changes in environmental conditions; (iii) respond to change in a predictable way. We present an objective, niche-based approach for species' selection, founded on a coarse categorisation of species' niche space and key resource requirements, which ensures the resultant indicator has these key attributes. 3. We use UK farmland birds as a case study to demonstrate this approach, identifying an optimal indicator set containing 12 species. In contrast to the 19 species included in the farmland bird index (FBI), a key UK biodiversity indicator that contributes to one of the UK Government's headline indicators of sustainability, the niche space occupied by these species fully encompasses that occupied by the wider community of 62 species. 4. We demonstrate that the response of these 12 species to land-use change is a strong correlate to that of the wider farmland bird community. Furthermore, the temporal dynamics of the index based on their population trends closely matches the population dynamics of the wider community. However, in both analyses, the magnitude of the change in our indicator was significantly greater, allowing this indicator to act as an early-warning system. 5. Ecological indicators are embedded in environmental management, sustainable development and biodiversity conservation policy and practice where they act as metrics against which progress towards national, regional and global targets can be measured. Adopting this niche-based approach for objective selection of indicator species will facilitate the development of sensitive and representative indices for a range of taxonomic groups, habitats and spatial scales.

Towards a semiotic approach to practice-oriented knowledge transfer

With the rapid growth of information and technology, knowledge is a valuable asset in organisation which has become significant as a strategic resource. Many studies have focused on managing knowledge in organisations. In particular, knowledge transfer has become a significant issue concerned with the movement of knowledge across organisational boundaries. It enables the exploitation and application of existing knowledge for other organisations, reducing the time of creating knowledge, and minimising the cost of organisational learning. One way to capture knowledge in a transferrable form is through practice. In this paper, we discuss how organisations can transfer knowledge through practice effectively and propose a model for a semiotic approach to practice-oriented knowledge transfer. In this model, practice is treated as a sign that represents knowledge, and its localisation is analysed as a semiotic process.

P-Prism: a computationally efficient approach to scaling up classification rule induction

Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unseen data. Alternative algorithms have been developed such as the Prism algorithm. Prism constructs modular rules which produce qualitatively better rules than rules induced by TDIDT. However, along with the increasing size of databases, many existing rule learning algorithms have proved to be computational expensive on large datasets. To tackle the problem of scalability, parallel classification rule induction algorithms have been introduced. As TDIDT is the most popular classifier, even though there are strongly competitive alternative algorithms, most parallel approaches to inducing classification rules are based on TDIDT. In this paper we describe work on a distributed classifier that induces classification rules in a parallel manner based on Prism.

Towards a computationally efficient approach to modular classification rule induction

Induction of classification rules is one of the most important technologies in data mining. Most of the work in this field has concentrated on the Top Down Induction of Decision Trees (TDIDT) approach. However, alternative approaches have been developed such as the Prism algorithm for inducing modular rules. Prism often produces qualitatively better rules than TDIDT but suffers from higher computational requirements. We investigate approaches that have been developed to minimize the computational requirements of TDIDT, in order to find analogous approaches that could reduce the computational requirements of Prism.

A spatio-temporal structure-based approach to drought characterisation

Drought characterisation is an intrinsically spatio-temporal problem. A limitation of previous approaches to characterisation is that they discard much of the spatio-temporal information by reducing events to a lower-order subspace. To address this, an explicit 3-dimensional (longitude, latitude, time) structure-based method is described in which drought events are defined by a spatially and temporarily coherent set of points displaying standardised precipitation below a given threshold. Geometric methods can then be used to measure similarity between individual drought structures. Groupings of these similarities provide an alternative to traditional methods for extracting recurrent space-time signals from geophysical data. The explicit consideration of structure encourages the construction of summary statistics which relate to the event geometry. Example measures considered are the event volume, centroid, and aspect ratio. The utility of a 3-dimensional approach is demonstrated by application to the analysis of European droughts (15 °W to 35°E, and 35 °N to 70°N) for the period 1901–2006. Large-scale structure is found to be abundant with 75 events identified lasting for more than 3 months and spanning at least 0.5 × 106 km2. Near-complete dissimilarity is seen between the individual drought structures, and little or no regularity is found in the time evolution of even the most spatially similar drought events. The spatial distribution of the event centroids and the time evolution of the geographic cross-sectional areas strongly suggest that large area, sustained droughts result from the combination of multiple small area (∼106 km2) short duration (∼3 months) events. The small events are not found to occur independently in space. This leads to the hypothesis that local water feedbacks play an important role in the aggregation process.

A mathematical approach to chemical equilibrium theory for gaseous systems—I: theory

Equilibrium theory occupies an important position in chemistry and it is traditionally based on thermodynamics. A novel mathematical approach to chemical equilibrium theory for gaseous systems at constant temperature and pressure is developed. Six theorems are presented logically which illustrate the power of mathematics to explain chemical observations and these are combined logically to create a coherent system. This mathematical treatment provides more insight into chemical equilibrium and creates more tools that can be used to investigate complex situations. Although some of the issues covered have previously been given in the literature, new mathematical representations are provided. Compared to traditional treatments, the new approach relies on straightforward mathematics and less on thermodynamics, thus, giving a new and complementary perspective on equilibrium theory. It provides a new theoretical basis for a thorough and deep presentation of traditional chemical equilibrium. This work demonstrates that new research in a traditional field such as equilibrium theory, generally thought to have been completed many years ago, can still offer new insights and that more efficient ways to present the contents can be established. The work presented here can be considered appropriate as part of a mathematical chemistry course at University level.

Semiotic approach to a practice-oriented knowledge transfer

Knowledge is a valuable asset in organisations that has become significant as a strategic resource in the information age. Many studies have focused on managing knowledge in organisations. In particular, knowledge transfer has become a significant issue concerned with the movement of knowledge across organisational boundaries. One way to capture knowledge in a transferrable form is through practice. In this paper, we discuss how organisations can transfer knowledge through practice effectively and propose a model for a semiotic approach to practice-oriented knowledge transfer. In this model, practice is treated as a sign that represents knowledge, and its localisation is analysed as a semiotic process.

A conceptual framework for aligning business and information systems from organisational learning perspective

The three decades of on-going executives’ concerns of how to achieve successful alignment between business and information technology shows the complexity of such a vital process. Most of the challenges of alignment are related to knowledge and organisational change and several researchers have introduced a number of mechanisms to address some of these challenges. However, these mechanisms pay less attention to multi-level effects, which results in a limited un-derstanding of alignment across levels. Therefore, we reviewed these challenges from a multi-level learning perspective and found that business and IT alignment is related to the balance of exploitation and exploration strategies with the intellec-tual content of individual, group and organisational levels.

Accounting information systems as institutional carriers: a case study of regulatory compliance in UK asset management houses

Previously, governments have responded to the impacts of economic failures and consequently have developed more regulations to protect employees, customers, shareholders and the economic wellbeing of the state. Our research addresses how Accounting Information Systems (AIS) may act as carriers for institutionalised practices associated with maintaining regulatory compliance within the context of UK Asset Management Houses. The AIS was found to be a strong conduit for institutionalized compliance related practices, utilising symbolic systems, relational systems, routines and artefacts to carry approaches relating to regulative, normative and cultural-cognitive strands of institutionalism. Thus, AIS are integral to the development and dissipation of best practice for the management of regulatory compliance. As institutional elements are clearly present we argue that AIS and regulatory compliance provide a rich context to further institutionalism. Since AIS may act as conduits for regulatory approaches, both systems adopters and clients may benefit from actively seeking to codify and abstract best practices into AIS. However, the application of generic institutionalized approaches, which may be applied across similar organizations, must be tempered with each firm’s business environment and associated regulatory exposure. A balance should be sought between approaches specific enough to be useful but generic enough to be universally applied.

Assessing pragmatic interoperability of information systems from a semiotic perspective

Most of studies on interoperability of systems integration focus on technical and semantic levels, but hardly extend investigations on pragmatic level. Our past work has addressed pragmatic interoperability, which is concerned with the relationship between signs and the potential behaviour and intention of responsible agents. We also define the pragmatic interoperability as a level concerning with the aggregation and optimisation of various business processes for achieving intended purposes of different information systems. This paper, as the extension of our previous research, is to propose an assessment method for measuring pragmatic interoperability of information systems. We firstly propose interoperability analysis framework, which is based on the concept of semiosis. We then develop pragmatic interoperability assessment process from two dimensions including six aspects (informal, formal, technical, substantive, communication, and control). We finally illustrate the assessment process in an example.

Evaluation frameworks for information systems integration: from a semiotic lens

Information systems integration aims at the interaction, information exchange and interoperability between information systems, devices and units. Research efforts have contributed in evaluation of information systems integration on the development of evaluation frameworks. To improve the usability and measurability of evaluation, a review of existing evaluation frameworks including their evolution and classifications of different interoperability levels is conducted. The theory of organisational semiotics is used for a comparative analysis of the frameworks and future work.

An ontological approach to personalized medical knowledge recommendation

Knowledge recommendation has become a promising method in supporting the clinicians decisions and improving the quality of medical services in the constantly changing clinical environment. However, current medical knowledge management systems cannot understand users requirements accurately and realize personalized recommendation. Therefore this paper proposes an ontological approach based on semiotic principles to personalized medical knowledge recommendations. In particular, healthcare domain knowledge is conceptualized and an ontology-based user profile is built. Furthermore, the personalized recommendation mechanism is illustrated.

Institutional pressures on financial services firms: the role of information systems in regulatory compliance

The financial crisis of 2008 led to new international regulatory controls for the governance, risk and compliance of financial services firms. Information systems play a critical role here as political, functional and social pressures may lead to the deinstitutionalization of existing structures, processes and practices. This research examines how an investment management system is introduced by a leading IT vendor across eight client sites in the post-crisis era. Using institutional theory, it examines changes in working practices occurring at the environmental and organizational levels and the ways in which technological interventions are used to apply disciplinary effects in order to prevent inappropriate behaviors. The results extend the constructs of deinstitutionalization and identify empirical predictors for the deinstitutionalization of compliance and trading practices within financial organizations.

The development of a data-driven application benchmarking approach to performance modelling

Performance modelling is a useful tool in the lifeycle of high performance scientific software, such as weather and climate models, especially as a means of ensuring efficient use of available computing resources. In particular, sufficiently accurate performance prediction could reduce the effort and experimental computer time required when porting and optimising a climate model to a new machine. In this paper, traditional techniques are used to predict the computation time of a simple shallow water model which is illustrative of the computation (and communication) involved in climate models. These models are compared with real execution data gathered on AMD Opteron-based systems, including several phases of the U.K. academic community HPC resource, HECToR. Some success is had in relating source code to achieved performance for the K10 series of Opterons, but the method is found to be inadequate for the next-generation Interlagos processor. The experience leads to the investigation of a data-driven application benchmarking approach to performance modelling. Results for an early version of the approach are presented using the shallow model as an example.

Beneath a learning management system: understanding the human information interaction in information systems

Studies on learning management systems have largely been technical in nature with an emphasis on the evaluation of the human computer interaction (HCI) processes in using the LMS. This paper reports a study that evaluates the information interaction processes on an eLearning course used in teaching an applied Statistics course. The eLearning course is used as a synonym for information systems. The study explores issues of missing context in stored information in information systems. Using the semiotic framework as a guide, the researchers evaluated an existing eLearning course with the view to proposing a model for designing improved eLearning courses for future eLearning programmes. In this exploratory study, a survey questionnaire is used to collect data from 160 participants on an eLearning course in Statistics in Applied Climatology. The views of the participants are analysed with a focus on only the human information interaction issues. Using the semiotic framework as a guide, syntactic, semantic, pragmatic and social context gaps or problems were identified. The information interactions problems identified include ambiguous instructions, inadequate information, lack of sound, interface design problems among others. These problems affected the quality of new knowledge created by the participants. The researchers thus highlighted the challenges of missing information context when data is stored in an information system. The study concludes by proposing a human information interaction model for improving the information interaction quality issues in the design of eLearning course on learning management platforms and those other information systems.