data-management system for detailed areal interpretive data

Cover of: data-management system for detailed areal interpretive data | Carmelo F. Ferrigno

Published by U.S. Dept. of the Interior, Geological Survey, Books and Open-File Reports [distributor] in Denver, Colo .

Written in English

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  • Information storage and retrieval systems -- Groundwater flow -- Mathematical models.,
  • Groundwater flow -- Mathematical models -- Information services.

Edition Notes

Book details

Statementby Carmelo F. Ferrigno.
SeriesU.S. Geological Survey water-resources investigations report -- 86-4091, Water-resources investigations report -- 86-4091.
ContributionsGeological Survey (U.S.)
The Physical Object
Paginationv, 103 p. :
Number of Pages103
ID Numbers
Open LibraryOL22409089M

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Data-management system for detailed areal interpretive data. Denver, Colo.: U.S. Dept. of the Interior, Geological Survey: Books and Open-File Reports [distributor], (OCoLC) A DATA-MANAGEMENT SYSTEM FOR DETAILED AREAL INTERPRETIVE DATA By Carmelo F. Ferrigno ABSTRACT A data storage and retrieval system has been developed to organize and preserve areal interpretive data.

This system can be used by any study where there is a need to store areal interpretive data that generally is presented in map : C.F. Ferrigno. A data storage and retrieval system has been developed to organize and preserve areal interpretive data. This system can be used by any study where there is a need to store areal interpretive data that generally is presented in map form.

This system provides the capability to grid areal interpretive data for input to groundwater flow models at any spacing and orientation. Get this from a library. A data-management system for areal interpretive data for the High Plains in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming.

[Richard R Luckey; Carmelo F Ferrigno; Geological Survey (U.S.)]. The study is designed under an interpretive paradigm, which took the form of a multiple-case study and the analysis of a considerable amount of primary and secondary qualitative data. This enabled the researchers to interact closely with the participants and to explore issues in : Hany Elbardan, Ahmed Othman Rashwan Kholeif.

data dictionary or data directory, which ca ontains metadata i.e. data about data. This file is consulted before actual data are read or modified in the data base system.

"Data analysis is the process of bringing order, structure and meaning to the mass of collected data. It is a messy, ambiguous, time-consuming, creative, and fascinating process.

It does not proceed in a linear fashion; it is not neat. Qualitative data analysis is a search for general statements about relationships among categories of data.".

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lation of the research problem, followed by a discussion of issues in qualitative data collection and sampling. We will then go on to present common strategies of data analysis, before concluding by summarising principles of good practice in descriptive– interpretive qualitative research and providing suggestions for further reading and learning.

to it, the process of qualitative data analysis is even described by some as involving as much “art” as science— as a “dance,” in the words of William Miller and Benjamin Crabtree (b) (Exhibit ): Interpretation is a complex and dynamic craft, with as much creative artistry as technical exacti.

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