The Prometheus Description Model: an examination of the taxonomic description-building process and its representation

A model for representing taxonomic descriptive data is presented. The model has been developed in response to the growing requirement for the global exchange of descriptive data. Meaningful exchange of data requires that data be represented in a form that can be consistently parsed and interpreted, requiring a common data model and the constrained and explicitly defined use of descriptive terms. The model presented here is divided into two parts that address both of these issues. A new data model for the representation and storage of taxonomic descriptive data is proposed that builds on and extends the best features of current descriptive data models and formats. An ontology-based model for defining and constraining the use of descriptive terms is also presented. The model is based on an analysis of current taxonomic working practices and the processes involved in generating a description. The model takes a specimen-oriented approach allowing descriptive data to be represented through a range of levels of abstraction from actual measurements of structures on a specimen to abstract descriptions of the features expected to be found on a specimen that is a member of a particular taxon. A comparison and discussion of the important aspects of the new model relative to existing models is presented

The Prometheus Taxonomic Model: a practical approach to representing multiple classification.

A model for representing taxonomic data in a flexible and dynamic system capable of handling and comparing multiple simultaneous classifications is presented. The Prometheus Taxonomic Model takes as its basis the idea that a taxon can be circumscribed by the specimens or taxa of a lower rank which are said to belong to it. In this model alternative taxon concepts are therefore represented in terms of differing circumscriptions. This provides a more objective way of expressing taxonomic concepts than purely descriptive circumscriptions have been published. Using specimens as the fundamental elements of taxon circumscription also allows for the automatic naming of taxa based upon the distribution and priority of types within each circumscription, and by application of the International Code of Botanical Nomenclature. This approach effectively separates the process of naming taxa (nomenclature) from that of classification, and therefore enables the system to store multiple classifications. The derivation of the model, how it compares with other models, and the implications for the construction of global data sets and taxonomic working practice are discussed

Research directions in data wrangling: Visualizations and transformations for usable and credible data

In spite of advances in technologies for working with data, analysts still spend an inordinate amount of time diagnosing data quality issues and manipulating data into a usable form. This process of ‘data wrangling’ often constitutes the most tedious and time-consuming aspect of analysis. Though data cleaning and integration arelongstanding issues in the database community, relatively little research has explored how interactive visualization can advance the state of the art. In this article, we review the challenges and opportunities associated with addressing data quality issues. We argue that analysts might more effectively wrangle data through new interactive systems that integrate data verification, transformation, and visualization. We identify a number of outstanding research questions, including how appropriate visual encodings can facilitate apprehension of missing data, discrepant values, and uncertainty; how interactive visualizations might facilitate data transform specification; and how recorded provenance and social interaction might enable wider reuse, verification, and modification of data transformations

DRIVE: An Environment for the Organised Construction of User-Interfaces to

©Copyright in this paper belongs to the author(s) Published in collaboration with th

bclasses: A construct and method for modelling co-operative object behaviour

Current object-oriented (OO) modelling techniques emphasise the static aspects of data objects. Dynamics in general and collaborations between objects in particular tend to be poorly supported and are often treated separately. A full understanding of an object is hindered if we cannot easily grasp what it can do as well as what it is. We require a way of expressing collaborations. Our approach abstracts collaborations and suggests a method of integrating these abstractions into mainstream OO data definition languages (DDLs) thereby adding new modelling primitives. We argue that these are closer to real-world views of objects and are therefore more useful than the modelling contrivances in current use. We demonstrate how these primitives may be translated into DDLs which are easily mapped onto OO programming languages

Role models for choice of academic discipline at university

Role models are considered important in career development (Hackett and Betz, 1981), but the range of role models adopted in making academic and vocational decisions is not well researched (Nauta and Kokaly, 2001), although there is some evidence of the impact of role models, such as in changes in attitudes to non-traditional careers (Evans and Whigham, 1995). This study analyses the role models identified by a large cohort of students studying first-year courses at the University of Queensland. A questionnaire was completed in class by 1075 students across six faculties, in which they identified role models for their choice of academic program and indicated whether the role model was of the same sex, and whether it was a positive or negative role model. The number and types of roles models identified for each discipline of study is presented. Analysis of the data indicates that both males and females identify more role models of the same sex than of the opposite sex, except for women entering male-dominated fields of engineering and information technology. Women have more positive role models than men for career choices

The influence of role models on students' entrepreneurial intentions

The Smart State initiative requires both improved education and training, particularly in technical fields, plus entrepreneurship to commercialise new ideas. In this study, we propose an entrepreneurial intentions model as a guide to examine the educational choices and entrepreneurial intentions of first-year University students, focusing on the effect of role models. A survey of over 1000 first-year University students revealed that the most enterprising students were choosing to study in the disciplines of information technology and business, economics and law, or selecting dual degree programs that include business. The role models most often identified for their choice of field of study were parents, followed by teachers and peers, with females identifying more role models than males. For entrepreneurship, students' role models were parents and peers, followed by famous persons and teachers. Males and females identified similar numbers of role models, but males found starting a business more desirable and more feasible, and reported higher entrepreneurial intention. The implications of these findings for Smart State policy are discussed

Situational factors and entrepreneurial intentions

Entrepreneurship can provide a satisfying and rewarding working life, providing a flexible lifestyle and considerable business autonomy. It is becoming an increasingly important career option for school and university graduates. At a national level, entrepreneurial activity contributes to prosperity and economic growth {Hindle, 2000 #316}. Economies are more robust if there are people who can combine technical knowledge with business acumen, and thereby also compete in a world market. Understanding the factors that influence and shape individuals’ intentions of starting a business is critical if programs and policies are to be developed to encourage entrepreneurial behaviour