From Conflict to Concord: Copyeditors, Composition, and Technology

The traditional rhetorical model suggests that the composition process progresses from writer, to text, to audience, but copyeditors must be added to the equation as writers create texts for the purpose of publication. To better understand the copyeditor's role in the publication process and within authors' writing and revision processes, this study examined how thirty copyeditors describe their roles; how they feel about their interactions with authors; and how they feel about the role of technology in the writing process and how they have adapted to technology. Overall, copyeditors were confident in their ability to copyedit using technology. In revising/editing, copyeditors are responsible for grammar, punctuation, and style; additionally, however, this study posits that they are also responsible for engaging in a collaborative revision process with the author. They must be recognized as both readers and writers and thus have the ability to affect a writer's revision and writing processes

Hoverlay : a peer-to-peer system for on demand sharing of capacity across network applications

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Hoverlay : a peer-to-peer system for on demand sharing of capacity across network applications

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Semi-automated Ontology Generation for Biocuration and Semantic Search

Background: In the life sciences, the amount of literature and experimental data grows at a tremendous rate. In order to effectively access and integrate these data, biomedical ontologies – controlled, hierarchical vocabularies – are being developed. Creating and maintaining such ontologies is a difficult, labour-intensive, manual process. Many computational methods which can support ontology construction have been proposed in the past. However, good, validated systems are largely missing. Motivation: The biocuration community plays a central role in the development of ontologies. Any method that can support their efforts has the potential to have a huge impact in the life sciences. Recently, a number of semantic search engines were created that make use of biomedical ontologies for document retrieval. To transfer the technology to other knowledge domains, suitable ontologies need to be created. One area where ontologies may prove particularly useful is the search for alternative methods to animal testing, an area where comprehensive search is of special interest to determine the availability or unavailability of alternative methods. Results: The Dresden Ontology Generator for Directed Acyclic Graphs (DOG4DAG) developed in this thesis is a system which supports the creation and extension of ontologies by semi-automatically generating terms, definitions, and parent-child relations from text in PubMed, the web, and PDF repositories. The system is seamlessly integrated into OBO-Edit and Protégé, two widely used ontology editors in the life sciences. DOG4DAG generates terms by identifying statistically significant noun-phrases in text. For definitions and parent-child relations it employs pattern-based web searches. Each generation step has been systematically evaluated using manually validated benchmarks. The term generation leads to high quality terms also found in manually created ontologies. Definitions can be retrieved for up to 78% of terms, child ancestor relations for up to 54%. No other validated system exists that achieves comparable results. To improve the search for information on alternative methods to animal testing an ontology has been developed that contains 17,151 terms of which 10% were newly created and 90% were re-used from existing resources. This ontology is the core of Go3R, the first semantic search engine in this field. When a user performs a search query with Go3R, the search engine expands this request using the structure and terminology of the ontology. The machine classification employed in Go3R is capable of distinguishing documents related to alternative methods from those which are not with an F-measure of 90% on a manual benchmark. Approximately 200,000 of the 19 million documents listed in PubMed were identified as relevant, either because a specific term was contained or due to the automatic classification. The Go3R search engine is available on-line under www.Go3R.org

Supporting Nutrition for Australian Childcare (SNAC): The development, implementation and evaluation of an online nutrition education intervention

The provision of a nutritious diet in a child’s early years can have an immense effect on their future health and wellbeing. Due to the increasing number of children attending child care, this setting is strategically placed for teaching children important food literacy skills and establishing positive eating habits, which remain through to adulthood. However, food served in child care facilities is often not of the best nutritional quality (Zuercher, Grace, & Kranz, 2011) and there is lack of positive role modelling among staff. Both of these factors pose obstacles to a health-promoting environment for the children who attend. The nutritional needs of young children are well known. This research sought to identify the child care specific nutrition education resources currently available, and to understand the broader needs of Australian child care staff that would enable them to provide a healthy eating environment. The findings of this research phase informed the design and development of a website to increase child care staff nutrition knowledge and confidence in providing a healthy eating environment, facilitating ongoing continuous improvement in their professional development. Discussion boards to promote a sense of community and provide ‘information wrapped in support’ were a key website feature. Qualitative interviews were conducted with child care facility staff and key industry stakeholders. Although positive attitudes towards promoting healthy eating were demonstrated, data revealed that recommended nutrition resources were not well known or utilised by the childcare sector and staff reported a lack of confidence and workplace support. Guided by the Spiral Technology Action Research model (H. Skinner, Maley, & Norman, 2006), a health promotion project management tool, these findings informed the development of the website, “Supporting Nutrition in Australian Childcare” (SNAC), containing a range of resources, recipes, discussion boards and links. Use of the website, staff nutrition knowledge, attitudes, confidence and sense of community were evaluated using a qualitative, netnographic approach, through conversation threads, interviews and observations. Quantitative data collection methods including pre- and post-intervention surveys and web analytics were utilised to triangulate these findings. Despite the “netnographic slog”, that is, the persistence and continued attempts to recruit educators and encourage them to engage with the website, findings suggest that the SNAC website was well utilised and valued by more than 1200 SNAC members, attracting over 90,000 page views and 600 posts/comments. Educators valued the ‘information wrapped in support’ offered by the website, and a sense of community developed, particularly around shared emotional connection. Educators reported positive attitudes and high self-efficacy towards providing a healthy eating environment. However, evaluation results demonstrated disparity between reported knowledge and behaviours, such as high self-efficacy, and those observed, such as poor quality menu plans. This research has shown the need for changes in public health policy to reprioritise a healthy eating environment in Australian childcare facilities; changes that foreground optimal nutrition in the early years as vital for future health and wellbeing. However, given that high-level policy change is often difficult and time consuming, the demonstrated disparity between reported and observed knowledge and behaviours highlights the need for shorter term strategies that address the support so badly needed, to ensure the long-term sustainability of these changes

Semi-automated Ontology Generation for Biocuration and Semantic Search

Background: In the life sciences, the amount of literature and experimental data grows at a tremendous rate. In order to effectively access and integrate these data, biomedical ontologies – controlled, hierarchical vocabularies – are being developed. Creating and maintaining such ontologies is a difficult, labour-intensive, manual process. Many computational methods which can support ontology construction have been proposed in the past. However, good, validated systems are largely missing. Motivation: The biocuration community plays a central role in the development of ontologies. Any method that can support their efforts has the potential to have a huge impact in the life sciences. Recently, a number of semantic search engines were created that make use of biomedical ontologies for document retrieval. To transfer the technology to other knowledge domains, suitable ontologies need to be created. One area where ontologies may prove particularly useful is the search for alternative methods to animal testing, an area where comprehensive search is of special interest to determine the availability or unavailability of alternative methods. Results: The Dresden Ontology Generator for Directed Acyclic Graphs (DOG4DAG) developed in this thesis is a system which supports the creation and extension of ontologies by semi-automatically generating terms, definitions, and parent-child relations from text in PubMed, the web, and PDF repositories. The system is seamlessly integrated into OBO-Edit and Protégé, two widely used ontology editors in the life sciences. DOG4DAG generates terms by identifying statistically significant noun-phrases in text. For definitions and parent-child relations it employs pattern-based web searches. Each generation step has been systematically evaluated using manually validated benchmarks. The term generation leads to high quality terms also found in manually created ontologies. Definitions can be retrieved for up to 78% of terms, child ancestor relations for up to 54%. No other validated system exists that achieves comparable results. To improve the search for information on alternative methods to animal testing an ontology has been developed that contains 17,151 terms of which 10% were newly created and 90% were re-used from existing resources. This ontology is the core of Go3R, the first semantic search engine in this field. When a user performs a search query with Go3R, the search engine expands this request using the structure and terminology of the ontology. The machine classification employed in Go3R is capable of distinguishing documents related to alternative methods from those which are not with an F-measure of 90% on a manual benchmark. Approximately 200,000 of the 19 million documents listed in PubMed were identified as relevant, either because a specific term was contained or due to the automatic classification. The Go3R search engine is available on-line under www.Go3R.org

The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed

Simple identification tools in FishBase

Simple identification tools for fish species were included in the FishBase information system from its inception. Early tools made use of the relational model and characters like fin ray meristics. Soon pictures and drawings were added as a further help, similar to a field guide. Later came the computerization of existing dichotomous keys, again in combination with pictures and other information, and the ability to restrict possible species by country, area, or taxonomic group. Today, www.FishBase.org offers four different ways to identify species. This paper describes these tools with their advantages and disadvantages, and suggests various options for further development. It explores the possibility of a holistic and integrated computeraided strategy

A Knowledge Mining Approach for Effective Customer Relationship Management

The problem of existing customer relationship management (CRM) system is not lack of information but the ability to differentiate useful information from chatter or even disinformation and also maximize the richness of these heterogeneous information sources. This paper describes an improved text mining approach for automatically extracting association rules from collections of textual documents. It discovers association rules from keyword features extracted from the documents. The main contributions of the technique are that, in selecting the most discriminative keywords for use in association rules generation, the system combines syntactic and semantic relevance into its Information Retrieval Scheme which is integrated with XML technology. Experiments carried out revealed that the extracted association rules contain important features which form a worthy platform for making effective decisions as regards customer relationship management. The performance of the improved text mining approach is compared with existing system that uses the GARW algorithm to reveal a significant reduction in the large itemsets, leading to reduction in rules generated to more interesting ones due to the semantic analysis component being introduced. Also, it has brought about reduction of the execution time, compared to the GARW algorithm.</p