Data Management Policies and Issues with Life Science Data

Data management and sharing are relatively new concepts in the health and life sciences fields. This presentation will cover some basic policies as well as the impediments to data sharing unique to health and life sciences data.

Guidelines for Linked Data generation and publication: an example in building energy consumption

Linked Data is the key paradigm of the Semantic Web, a new generation of the World Wide Web that promises to bring meaning (semantics) to data. A large number of both public and private organizations have published their data following the Linked Data principles, or have done so with data from other organizations. To this extent, since the generation and publication of Linked Data are intensive engineering processes that require high attention in order to achieve high quality, and since experience has shown that existing general guidelines are not always sufficient to be applied to every domain, this paper presents a set of guidelines for generating and publishing Linked Data in the context of energy consumption in buildings (one aspect of Building Information Models). These guidelines offer a comprehensive description of the tasks to perform, including a list of steps, tools that help in achieving the task, various alternatives for performing the task, and best practices and recommendations. Furthermore, this paper presents a complete example on the generation and publication of Linked Data about energy consumption in buildings, following the presented guidelines, in which the energy consumption data of council sites (e.g., buildings and lights) belonging to the Leeds City Council jurisdiction have been generated and published as Linked Data.

Environmental data : major effort is needed to improve NOAA's data management and archiving : report to the Chairman, Committee on Commerce, Science and Transportation, U.S. Senate /

"B-241021"--P. l.

MARC uses and users : papers presented at the 1970 Clinic on Library Applications of Data Processing conducted by the University of Illinois Graduate School of Library Science, April 26-29, 1970 /

Includes bibliographical references and index.

Foreign direct investment in the United States : an update : review and analysis of current developments : a report submitted to the Committee on Energy and Commerce, the Committee on Ways and Means, and the Committee on Foreign Affairs of the House of Representatives, to the Committee on Finance, the Committee on Commerce, Science and Transportation, and the Committee on Foreign Relations of the Senate, and to the Joint Economic Committee of the Congress in response to section 3(a) of the Foreign Direct Investment and International Financial Data Improvements Act of 1990.

"January 1995."

Osiris III; an integrated collection of computer programs for the management and analysis of social science data.

v. 1. System and program description.--v. 2. Error Messages.--v. 3. Summary of control cards.--v. 4. Sample jobs.--v. 5. Formulas and statistical references.--v. 6. Primer.

An intensive survey of the Kaskaskia River Basin : data summary, summer 1996 and 1997 /

"IEPA/BOW/00-001"--Cover.

An intensive survey of the Vermilion River Basin (Wabash River drainage) 1997 : data collection methods and summary /

"The Illinois Environmental Protection Agency monitors surface waters (i.e. lakes and streams) through a variety of programs. The most extensive is the Ambient Water Quality Monitoring Network (AWQMN) which consists of 203 stream stations statewide sampled on a 6 week cycle since October 1977." -- p. 1.

An intensive survey of the Cache River Basin, data summary : summer 1999 /

"IEPA/BOW/02-021."--Cover.

Individuals and families in transition : understanding change through longitudinal data : papers presented at the Social Science Research Council conference in Annapolis, Maryland, March 16-18, 1988 /

Mode of access: Internet.

Methods for Categorical Longitudinal Survey Data: Understanding Employment Status of Australian Women

Many variables that are of interest in social science research are nominal variables with two or more categories, such as employment status, occupation, political preference, or self-reported health status. With longitudinal survey data it is possible to analyse the transitions of individuals between different employment states or occupations (for example). In the statistical literature, models for analysing categorical dependent variables with repeated observations belong to the family of models known as generalized linear mixed models (GLMMs). The specific GLMM for a dependent variable with three or more categories is the multinomial logit random effects model. For these models, the marginal distribution of the response does not have a closed form solution and hence numerical integration must be used to obtain maximum likelihood estimates for the model parameters. Techniques for implementing the numerical integration are available but are computationally intensive requiring a large amount of computer processing time that increases with the number of clusters (or individuals) in the data and are not always readily accessible to the practitioner in standard software. For the purposes of analysing categorical response data from a longitudinal social survey, there is clearly a need to evaluate the existing procedures for estimating multinomial logit random effects model in terms of accuracy, efficiency and computing time. The computational time will have significant implications as to the preferred approach by researchers. In this paper we evaluate statistical software procedures that utilise adaptive Gaussian quadrature and MCMC methods, with specific application to modeling employment status of women using a GLMM, over three waves of the HILDA survey.

Data envelopment analysis model for the appraisal and relative performance evaluation of nurses at an intensive care unit

The appraisal and relative performance evaluation of nurses are very important and beneficial for both nurses and employers in an era of clinical governance, increased accountability and high standards of health care services. They enhance and consolidate the knowledge and practical skills of nurses by identification of training and career development plans as well as improvement in health care quality services, increase in job satisfaction and use of cost-effective resources. In this paper, a data envelopment analysis (DEA) model is proposed for the appraisal and relative performance evaluation of nurses. The model is validated on thirty-two nurses working at an Intensive Care Unit (ICU) at one of the most recognized hospitals in Lebanon. The DEA was able to classify nurses into efficient and inefficient ones. The set of efficient nurses was used to establish an internal best practice benchmark to project career development plans for improving the performance of other inefficient nurses. The DEA result confirmed the ranking of some nurses and highlighted injustice in other cases that were produced by the currently practiced appraisal system. Further, the DEA model is shown to be an effective talent management and motivational tool as it can provide clear managerial plans related to promoting, training and development activities from the perspective of nurses, hence increasing their satisfaction, motivation and acceptance of appraisal results. Due to such features, the model is currently being considered for implementation at ICU. Finally, the ratio of the number DEA units to the number of input/output measures is revisited with new suggested values on its upper and lower limits depending on the type of DEA models and the desired number of efficient units from a managerial perspective.