Write a short note on conceptual modeling of data warehouses

First, the domain of w3cgeo: Point is defined as a sub-class of w3cgeo:

Write a short note on conceptual modeling of data warehouses

The red arrow indicates 'disjoint classes'. First, the domain of w3cgeo: While one could interpret these properties as mapping to a geometryas GeoRSS Simple does, there isn't conclusive evidence that this is what was intended. Point is defined as a sub-class of w3cgeo: As a result, we have inconsistency in how w3cgeo: SpatialThing may be interpreted.

Geometry ; Because foaf: Person is defined as a sub-class of w3cgeo: SpatialThingsome other people find it natural to equate w3cgeo: Feature So in summary, it's safer to say that our Spatial Thing equates to geosparql: Featureand that it is not the same as w3cgeo: However, in some applications it is more useful to describe the variation of property values in space and time.

Such descriptions are formalized as coverages. Users of spatial information may employ both viewpoints. So what is a coverage? As defined by [ ISO ] it is simply a data structure that maps points in space and time to property values.

For example, an aerial photograph can be thought of as a coverage that maps positions on the ground to colors.

A river gauge maps points in time to flow values. A weather forecast maps points in space and time to values of temperature, wind speed, humidity and so forth. One way to think of a coverage is as a mathematical function, where data values are a function of coordinates in space and time.

You can see from the above paragraph that non-gridded data like a river gauge measurement can also be modelled as coverages. Nevertheless, you will often find a bias toward gridded data in discussions and software that concern coverages. Although the definition above presents a coverage as a data structure, conceptually it still has spatial extent.

write a short note on conceptual modeling of data warehouses

For example, the distribution of rainfall measured by a weather radar can be thought of as a coverage — the spatial extent is defined by the limit of the weather radar's range.

Similarly, we might say in the hydrology example, where a river gauge measures flow values at regular sampling times, the spatial extent would be the monitoring point where the river gauge is positioned. We say that a coverage is really just a special type of Spatial Thing with some particular properties.

Spatial Things and coverages may be related in several ways: As the property value of a Spatial Thing whose value varies within the extent of that Spatial Thing; for example, the varying strength of mobile-network coverage throughout the UK. The values of a common property for a distributed set of Spatial Things provide a discrete sampling of a coverage; for example, the measurement of soil moisture based at a set of sampling stations can be compiled to show the spatial variation of soil moisture across the region where the sampling stations are located.

A coverage can be defined using three main pieces of information: The domain of the coverage is the set of points in space and time for which we have data values.


For example, in a river gauge measurement, the domain is the set of times at which the flow was measured. In a satellite image, the domain is the set of pixels. In a weather forecast, the domain is a set of grid cells. The range of the coverage is the set of measured, simulated or observed data values.

A single coverage may record values for lots of different quantities; for example, a weather forecast predicts values for many things temperature, humidity etc. So the range of a coverage often consists of several lists of data values, one for each measured variable.

Each element within each list corresponds with one of the elements of the domain e. The range metadata describes the range of the coverage, to help users to understand what the data values mean.

This may include links to definitions of variables, units of measure and other bits of useful information. Usually, the most complex piece of information in the coverage is the definition of the domain. This can vary quite widely from coverage type to coverage type, as the list above shows.Metadata is "data [information] that provides information about other data".


Many distinct types of metadata exist, among these descriptive metadata, structural metadata, administrative metadata, reference metadata and statistical metadata. Descriptive metadata describes a resource for purposes such as discovery and identification.

* Some lab experiments must be performed using any circuit simulation software e.g. PSPICE. BACHELOR OF TECHNOLOGY (Computer Science & Engineering).

3. Methodology.


In order to find out the requirements for the deliverables of the Working Group, use cases were collected. For the purpose of the Working Group, a use case is a story that describes challenges with respect to spatial data on the Web for existing or envisaged information systems.

The rise of contact and commerce between many human-colonized worlds or many worlds of alien intelligences that have come to trust and do business with one another. The Bachelor of Science in Data Science and Analytics is based in the Department of Electrical Engineering and Computer Science in the Case School of Engineering..

Applied Data Science Minor. An undergraduate minor in applied data science is administered in the Materials Science and Engineering Department.. A complete list of DSCI courses may be found on the courses tab of the Data .

DISCLAIMER: I am not a rocket scientist, merely an amateur that has read a lot of books. Any and all of the information on these pages may be incorrect or inaccurate. But since I have yet to find a website like this written by a real live rocket scientist, I had to write it myself, as unqualified as I am.

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