Interactive visualisation tools for supporting taxonomists working practice.

The necessity for scientists and others to use consistent terminology has recently beenregarded as fundamental to advancing scientific research, particularly where data fromdisparate sources must be shared, compared or integrated. One area where there aresignificant difficulties with the quality of collected data is the field of taxonomicdescription. Taxonomic description lies at the heart of the classification of organismsand communication of ideas of biodiversity. As part of their working practice,taxonomists need to gather descriptive data about a number of specimens on aconsistent basis for individual projects. Collecting semantically well-defined structureddata could improve the clarity and comparability of such data. No tools howevercurrently exist to allow taxonomists to do so within their working practice.Ontologies are increasingly used to describe and define complex domain data. As a partof related research an ontology of descriptive terminology for controlling the storageand use of flowering plant description data was developed.This work has applied and extended model-based user interface developmentenvironments to utilise such an ontology for the automatic generation of appropriatedata entry interfaces that support semantically well defined and structured descriptivedata. The approach taken maps the ontology to a system domain model, which ataxonomist can then specialise using their domain expertise, for their data entry needs asrequired for individual projects. Based on this specialised domain knowledge, thesystem automatically generates appropriate data entry interfaces that capture dataconsistent with the original ontology. Compared with traditional model-based userautomatic interface development environments, this approach also has the potential toreduce the labour requirements for the expert developer.The approach has also been successfully tested to generate data entry interfaces basedon an XML schema for the exchange of biodiversity datasets

Interactive visualisation tools for supporting taxonomists working practice.

The necessity for scientists and others to use consistent terminology has recently beenregarded as fundamental to advancing scientific research, particularly where data fromdisparate sources must be shared, compared or integrated. One area where there aresignificant difficulties with the quality of collected data is the field of taxonomicdescription. Taxonomic description lies at the heart of the classification of organismsand communication of ideas of biodiversity. As part of their working practice,taxonomists need to gather descriptive data about a number of specimens on aconsistent basis for individual projects. Collecting semantically well-defined structureddata could improve the clarity and comparability of such data. No tools howevercurrently exist to allow taxonomists to do so within their working practice.Ontologies are increasingly used to describe and define complex domain data. As a partof related research an ontology of descriptive terminology for controlling the storageand use of flowering plant description data was developed.This work has applied and extended model-based user interface developmentenvironments to utilise such an ontology for the automatic generation of appropriatedata entry interfaces that support semantically well defined and structured descriptivedata. The approach taken maps the ontology to a system domain model, which ataxonomist can then specialise using their domain expertise, for their data entry needs asrequired for individual projects. Based on this specialised domain knowledge, thesystem automatically generates appropriate data entry interfaces that capture dataconsistent with the original ontology. Compared with traditional model-based userautomatic interface development environments, this approach also has the potential toreduce the labour requirements for the expert developer.The approach has also been successfully tested to generate data entry interfaces basedon an XML schema for the exchange of biodiversity datasets

Interoperability between heterogeneous and distributed biodiversity data sources in structured data networks

The extensive capturing of biodiversity data and storing them in heterogeneous information systems that are accessible on the internet across the globe has created many interoperability problems. One is that the data providers are independent of others and they can run systems which were developed on different platforms at different times using different software products to respond to different needs of information. A second arises from the data modelling used to convert the real world data into a computerised data structure which is not conditioned by a universal standard. Most importantly the need for interoperation between these disparate data sources is to get accurate and useful information for further analysis and decision making. The software representation of a universal or a single data definition structure for depicting a biodiversity entity is ideal. But this is not necessarily possible when integrating data from independently developed systems. The different perspectives of the real-world entity when being modelled by independent teams will result in the use of different terminologies, definition and representation of attributes and operations for the same real-world entity. The research in this thesis is concerned with designing and developing an interoperable flexible framework that allows data integration between various distributed and heterogeneous biodiversity data sources that adopt XML standards for data communication. In particular the problems of scope and representational heterogeneity among the various XML data schemas are addressed. To demonstrate this research a prototype system called BUFFIE (Biodiversity Users‘ Flexible Framework for Interoperability Experiments) was designed using a hybrid of Object-oriented and Functional design principles. This system accepts the query information from the user in a web form, and designs an XML query. This request query is enriched and is made more specific to data providers using the data provider information stored in a repository. These requests are sent to the different heterogeneous data resources across the internet using HTTP protocol. The responses received are in varied XML formats which are integrated using knowledge mapping rules defined in XSLT & XML. The XML mappings are derived from a biodiversity domain knowledgebase defined for schema mappings of different data exchange protocols. The integrated results are presented to users or client programs to do further analysis. The main results of this thesis are: (1) A framework model that allows interoperation between the heterogeneous data source systems. (2) Enriched querying improves the accuracy of responses by finding the correct information existing among autonomous, distributed and heterogeneous data resources. (3) A methodology that provides a foundation for extensibility as any new network data standards in XML can be added to the existing protocols. The presented approach shows that (1) semi automated mapping and integration of datasets from the heterogeneous and autonomous data providers is feasible. (2) Query enriching and integrating the data allows the querying and harvesting of useful data from various data providers for helpful analysis.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Interoperability between heterogeneous and distributed biodiversity data sources in structured data networks

The extensive capturing of biodiversity data and storing them in heterogeneous information systems that are accessible on the internet across the globe has created many interoperability problems. One is that the data providers are independent of others and they can run systems which were developed on different platforms at different times using different software products to respond to different needs of information. A second arises from the data modelling used to convert the real world data into a computerised data structure which is not conditioned by a universal standard. Most importantly the need for interoperation between these disparate data sources is to get accurate and useful information for further analysis and decision making. The software representation of a universal or a single data definition structure for depicting a biodiversity entity is ideal. But this is not necessarily possible when integrating data from independently developed systems. The different perspectives of the real-world entity when being modelled by independent teams will result in the use of different terminologies, definition and representation of attributes and operations for the same real-world entity. The research in this thesis is concerned with designing and developing an interoperable flexible framework that allows data integration between various distributed and heterogeneous biodiversity data sources that adopt XML standards for data communication. In particular the problems of scope and representational heterogeneity among the various XML data schemas are addressed. To demonstrate this research a prototype system called BUFFIE (Biodiversity Users‘ Flexible Framework for Interoperability Experiments) was designed using a hybrid of Object-oriented and Functional design principles. This system accepts the query information from the user in a web form, and designs an XML query. This request query is enriched and is made more specific to data providers using the data provider information stored in a repository. These requests are sent to the different heterogeneous data resources across the internet using HTTP protocol. The responses received are in varied XML formats which are integrated using knowledge mapping rules defined in XSLT & XML. The XML mappings are derived from a biodiversity domain knowledgebase defined for schema mappings of different data exchange protocols. The integrated results are presented to users or client programs to do further analysis. The main results of this thesis are: (1) A framework model that allows interoperation between the heterogeneous data source systems. (2) Enriched querying improves the accuracy of responses by finding the correct information existing among autonomous, distributed and heterogeneous data resources. (3) A methodology that provides a foundation for extensibility as any new network data standards in XML can be added to the existing protocols. The presented approach shows that (1) semi automated mapping and integration of datasets from the heterogeneous and autonomous data providers is feasible. (2) Query enriching and integrating the data allows the querying and harvesting of useful data from various data providers for helpful analysis

A Knowledge Based Educational (KBEd) framework for enhancing practical skills in engineering distance learners through an augmented reality environment

The technology advancement has changed distance learning teaching and learning approaches, for example, virtual laboratories are increasingly used to deliver engineering courses. These advancements enhance the distance learners practical experience of engineering courses. While most of these efforts emphasise the importance of the technology, few have sought to understand the techniques for capturing, modelling and automating the on-campus laboratory tutors’ knowledge. The lack of automation of tutors’ knowledge has also affected the practical learning outcomes of engineering distance learners. Hence, there is a need to explore further on how to integrate the tutor's knowledge, which is necessary for imparting and assessing practical skills through current technological advances in distance learning. One approach to address this concern is through the use of Knowledge Based Engineering (KBE) principles. These KBE principles facilitate the utilisation of standardised methods for capturing, modelling and embedding experts’ knowledge into engineering design applications for the automation of product design. Hence, utilising such principles could facilitate, automating engineering laboratory tutors’ knowledge for teaching and assessing practical skills. However, there is limited research in the application of KBE principles in the educational domain. Therefore, this research explores the use of KBE principles to automate instructional design in engineering distance learning technologies. As a result, a Knowledge Based Educational (KBEd) framework that facilitates the capturing, modelling and automating on-campus tutors’ knowledge and introduces it to distance learning and teaching approaches. This study used a four-stage experimental approach, which involved rapid prototyping method to design and develop the proposed KBEd framework to a functional prototype. The developed prototype was further refined through internal and external expert group using face validity methods such as questionnaire, observation and discussion. The refined prototype was then evaluated through welding task use-case. The use cases were assessed by first year engineering undergraduate students with no prior experience of welding from Birmingham City University. The participants were randomly separated into two groups (N = 46). One group learned and practised basic welding in the proposed KBEd system, while the other learned and practised in the conventional on-campus environment. A concurrent validity assessment was used in determining the usefulness of the proposed system in learning hands-on practical engineering skills through proposed KBEd system. The results of the evaluation indicate that students who trained with the proposed KBEd system successfully gained the practical skills equivalent to those in the real laboratory environment. Although there was little performance variation between the two groups, it was rooted in the limitations of the system’s hardware. The learning outcomes achieved also demonstrated the successful application of KBE principles in capturing, modelling and transforming the knowledge from the real tutor to the AI tutor for automating the teaching and assessing of the practical skills for distance learners. Further the data analysis has shown the potential of KBEd to be extendable to other taught distance-learning courses involving practical skills