Conceptual framework for the mapping of management process with information technology in a business process.
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ABSTRACT:
SUBMITTER: Rajarathinam V
PROVIDER: S-EPMC4377516 | biostudies-other | 2015
REPOSITORIES: biostudies-other
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Project description:Although ontogenetic changes in body shape and its associated allometry has been studied for over a century, essentially nothing is known about their underlying genetic and developmental mechanisms. One of the reasons for this ignorance is the unavailability of a conceptual framework to formulate the experimental design for data collection and statistical models for data analyses. We developed a framework model for unraveling the genetic machinery for ontogenetic changes of allometry. The model incorporates the mathematical aspects of ontogenetic growth and allometry into a maximum likelihood framework for quantitative trait locus (QTL) mapping. As a quantitative platform, the model allows for the testing of a number of biologically meaningful hypotheses to explore the pleiotropic basis of the QTL that regulate ontogeny and allometry. Simulation studies and real data analysis of a live example in soybean have been performed to investigate the statistical behavior of the model and validate its practical utilization. The statistical model proposed will help to study the genetic architecture of complex phenotypes and, therefore, gain better insights into the mechanistic regulation for developmental patterns and processes in organisms.
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Project description:The increasing availability of digitized biodiversity data worldwide, provided by an increasing number of institutions and researchers, and the growing use of those data for a variety of purposes have raised concerns related to the "fitness for use" of such data and the impact of data quality (DQ) on the outcomes of analyses, reports, and decisions. A consistent approach to assess and manage data quality is currently critical for biodiversity data users. However, achieving this goal has been particularly challenging because of idiosyncrasies inherent in the concept of quality. DQ assessment and management cannot be performed if we have not clearly established the quality needs from a data user's standpoint. This paper defines a formal conceptual framework to support the biodiversity informatics community allowing for the description of the meaning of "fitness for use" from a data user's perspective in a common and standardized manner. This proposed framework defines nine concepts organized into three classes: DQ Needs, DQ Solutions and DQ Report. The framework is intended to formalize human thinking into well-defined components to make it possible to share and reuse concepts of DQ needs, solutions and reports in a common way among user communities. With this framework, we establish a common ground for the collaborative development of solutions for DQ assessment and management based on data fitness for use principles. To validate the framework, we present a proof of concept based on a case study at the Museum of Comparative Zoology of Harvard University. In future work, we will use the framework to engage the biodiversity informatics community to formalize and share DQ profiles related to DQ needs across the community.
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Project description:Today's health care environment encourages health care consumers to take an active role in managing their health. As digital natives, young educated adults do much of their health information management through the Internet and consider it a valid source of health advice. However, the quality of information on health websites is highly variable and dynamic. Little is known about the understandings and perceptions that young educated adults have garnered on the quality of information on health websites used for health care-related purposes.To fill this gap, the aim of this study was to develop a conceptual framework of health website information quality with quality dimensions (ie, criteria) and associated quality drivers (ie, attributes) specified in the context of young educated adults' use of health websites for health care-related purposes. This aim was achieved by (1) identifying information quality dimensions of health websites from the perspective of young educated adults; (2) identifying the importance ratings of these quality dimensions; and (3) constructing a framework of health website information quality with quality dimensions and associated drivers specified in the context of young educated adults' use of health websites for health care-related purposes.The study employed both qualitative and quantitative methods. Methods included semistructured group interviews and an individual quality assessment exercise grounded in visiting various websites and responding to Likert scale questions regarding the importance ratings of information quality dimensions and open-ended questions with specifying website quality drivers. Study participants included junior and senior undergraduate and graduate students in business, allied health, and public health majors. Qualitative, open-coding procedures were used to develop the conceptual framework reflecting the participants' means of assessing information quality on health websites.Five dimensions of information quality for health websites were identified: Completeness of information, Understandability of information, Relevance of information, Depth of information, and Accuracy of information. Completeness of information and Understandability of information were rated as the two most important quality dimensions by the study participants. Results indicated that these five information quality dimensions for health websites were supported by the following main driver themes: Content, Design, Links, Consumer resources, Search functionality, Supporting references, User focus, Content FAQ, Open access, Policy statements, and Site performance.This study contributes to the literature by developing a health website information quality conceptual framework with quality dimensions and associated drivers specified for a young educated adult population. The detailed quality drivers supporting the corresponding quality dimensions provide a rich picture of young educated adults' perceptions on health website information quality. This framework can be used to guide the development of health websites, as well as the foundation for a means to evaluate health information from existing health websites with young educated adults as the target audience.
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