4 edition of Research data management in the ecological sciences found in the catalog.
by Published for the Belle W. Baruch Institute for Marine Biology and Coastal Research by the University of South Carolina Press in Columbia, S.C
Written in English
|Statement||edited by William K. Michener.|
|Series||The Belle W. Baruch library in marine science ;, no. 16|
|Contributions||Michener, William K., Belle W. Baruch Institute for Marine Biology and Coastal Research.|
|LC Classifications||QH541.15.E45 R47 1986|
|The Physical Object|
|Pagination||xiii, 426 p. :|
|Number of Pages||426|
|LC Control Number||85026557|
Objective The purpose of this study is to describe the volume, topics, and methodological nature of the existing research literature on research data management in academic institutions. Materials and methods We conducted a scoping review by searching forty literature databases encompassing a broad range of disciplines from inception to April The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing.
The Bonanza Creek LTER is a member of the U.S. LTER Network which is supported by the National Science Foundation (DEB) and by the USDA Forest Service, Pacific Northwest Research Station (RJVA-PNWJV).Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the . The LTER Data Portal offers a coordinated view of LTER data sets and is published by the Environmental Data Initiative (EDI), an environmental data repository that grew out of the information management systems and practices of the LTER other environmental science research programs — especially those funded through NSF’s Division of Environmental Biology — also .
First, unlike other text books, this book is not just about “research methods” (empirical data collection and analysis) but about the entire “research process” from start to end. Research method is only one phase in that research process, and possibly the easiest and most structured one. Website cá nhân giáo viên - cán bộ CNV -Trường Đại Học.
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The central thesis of the book is that high quality data management systems are critical for addressing future environmental challenges, requiring a new approach to how we conduct ecological research, one that views data as a resource and promotes stewardship, recycling and sharing of data.4/5(1).
Research data management in the ecological sciences. Columbia, S.C.: Published for the Belle W. Baruch Institute for Marine Biology and Coastal Research by the University of South Carolina Press, (OCoLC) Material Type: Conference publication, Government publication, State or province government publication: Document Type: Book.
Data and Information Management in the Ecological Sciences: A Resource Guide Edited by William K. Michener, John H. Porter, and Susan G.
Stafford This publication should be cited as: Michener, W.K., J.H. Porter, and S.G. Stafford. Data and information management in the ecological sciences: a.
A Guide to Data Management in Ecology and Evolution 21 Good data management is fundamental to research excellence. It produces high-quality research data that are accessible to.
This book provides a practical introduction to analysing ecological data using real data sets collected as part of postgraduate ecological studies or research projects.
The first part of the book gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modelling techniques), multivariate analysis, time series analysis (e.g.
common trends) and spatial. Data Sciences in Ecology and the Environment Many of the greatest challenges we face today come from understanding and interacting with the natural world: from global climate change to the sudden collapse of fisheries and forests, from the spread of disease and invasive species to the unknown wealth of medical, cultural, and technological value.
This book is about combining models with data to answer ecological ques-tions. Pursuing this worthwhile goal will lead to topics ranging from basic statistics, to the cutting edge of modern statistics, to the nuts and bolts of computer programming, to the philosophy of science.
Remember as we go. Environmental and Ecological Statistics broadly covers theory and methods, case studies and applications, environmental change and statistical ecology, environmental health statistics and stochastics, and related areas.
The book Introduction to Environmental Sciences by R. Khoiyangbam and Navindu Gupta is very timely and well-conceived publication; it covers almost all important areas of the vast subject. The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices.
The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator applications as well as for theoretical, modelling and quantitative approaches such as index development.
The book Fundamentals of Research methodology and Data collection aims at providing necessary steps and guidelines to researchers and postgraduates who are. The term "species interaction" has both positive and negative impact on ecological research.
It underlies many fundamental ecological ideas but obscures the importance of individual heterogeneity in community dynamics. This article provokes debate on the validity of the term for the future development of ecology. Environmental Data Science — Natural Resources.
By Lillian Pierson. You can use data science to model natural resources in their raw form. This type of environmental data science generally involves some advanced statistical modeling to better understand natural resources.
You model the resources in the raw — water, air, and land conditions as they occur in nature — to better understand the natural. Written specifically for social science-based research into the environment, this book covers the best-practice research methods most commonly used to study the environment and its connections to societal and economic activities and objectives.
Over five key parts, Kanazawa introduces quantitative and qualitative approaches, mixed methods, and. This book gives a clear understanding of the data science and the algorithms which are used. Every algorithm is clearly explained. There are many concepts that all are covered like Neural Networks, Social Network Analysis, Decision Trees and Random Forests, Clustering and also many more.
It has become increasingly accepted that important digital data must be retained and shared in order to preserve and promote knowledge, advance research in and across all disciplines of scholarly endeavor, and maximize the return on investment of public funds.
To meet this challenge, colleges and universities are adding data services to existing infrastructures by drawing on the expertise of.
: Environmental Assessment on Energy and Sustainability by Data Envelopment Analysis (Wiley Series in Operations Research and Management Science) (): Sueyoshi, Toshiyuki, Goto, Mika: Books. At Springer Nature we want to enable all of our authors and journals to publish the best research, which includes achieving community best practices in the sharing and archiving of research data - Springer Nature Research Data Support enables researchers to do this quickly and securely.
The requirements of ecological information management are not extraordinary compared to other data-intensive endeavors, but the potentially contradictory demands of research, archival, analysis and collaboration can overwhelm an inappropriately designed computing infrastructure.
Marine Environmental Research publishes original research papers on chemical, physical, and biological interactions in the oceans and coastal journal serves as a forum for new information on biology, chemistry, and toxicology and syntheses that advance understanding of marine environmental processes.
Submission of multidisciplinary studies is encouraged. Elsevier | An Information Analytics Business | Empowering.Data management is the most important things in research - discover how researchers plan, Find out why it’s time to think about adding ‘book author’ to your CV.
28 m. Research in health and medical sciences is always inevitably carried out with the intention to bring some benefit to the public.This book provides a practical introduction to analysing ecological data using real data sets collected as part of postgraduate ecological studies or research projects.
The first part of the book gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modelling techniques), multivariate.