By Praveen Kumar, Mike Folk, Momcilo Markus, Jay C. Alameda
Sleek hydrology is extra interdisciplinary than ever. striking quantities and types of details pour in from GIS and distant sensing structures each day, and this data has to be gathered, interpreted, and shared successfully. Hydroinformatics: information Integrative ways in Computation, research, and Modeling introduces the instruments, methods, and procedure issues essential to take complete benefit of the ample hydrological info to be had this day. Linking hydrological technology with desktop engineering, networking, and database technological know-how, this e-book lays a pedagogical starting place within the recommendations underlying advancements in hydroinformatics. It starts with an creation to facts illustration via Unified Modeling Language (UML), via electronic libraries, metadata, the fundamentals of information types, and Modelshed, a brand new hydrological facts version. construction in this platform, the e-book discusses integrating and dealing with various info in huge datasets, information communique matters corresponding to XML and Grid computing, the fundamental ideas of knowledge processing and research together with characteristic extraction and spatial registration, and glossy equipment of sentimental computing reminiscent of neural networks and genetic algorithms. this present day, hydrological info are more and more wealthy, complicated, and multidimensional. offering a radical compendium of suggestions and methodologies, Hydroinformatics: info Integrative methods in Computation, research, and Modeling is the 1st connection with offer the instruments essential to confront those demanding situations effectively.
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Additional info for Hydroinformatics: data integrative approaches in computation, analysis, and modeling
Vector vs. scalar data. These descriptions actually apply to the logical data structures used to represent the data and not the manner in which they are stored physically. Some refer to this type of consideration as relating to the structure or semantics of the data but there is no universal agreement on this classiﬁcation since it is highly subjective and context dependent. In order to simplify our subsequent discussion and refrain from having to provide too many caveats and asides, we will focus on the ﬁle-oriented aspects of the problem and generally assume “data” to mean data ﬁles of all types.
Standard lists of geographic placenames) and other authoritative data. 3 Functions Needed for the Publication of Scientiﬁc Data In order to support the concepts of the previous sections, we have identiﬁed and described a set of basic functions for the publication of scientiﬁc data (REF). 3. Many modern systems contain at least a subset of these functions but the ensuing discussion of the HIS incorporates them all so we will refer back to this table throughout the exposition of the HIS design.
1 A Scholarly Model for Data Publication Using Digital Libraries . . . . . . 2 The Problem of Multisource Data . . . . . . . . . . . . . . . . . . . . . . . . 1 Types of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Importance of and Considerations for Reproducibility of Results . . . . . . . . . . . . . . . . . . . . . . . . .
Hydroinformatics: data integrative approaches in computation, analysis, and modeling by Praveen Kumar, Mike Folk, Momcilo Markus, Jay C. Alameda