PROCESS IN DATA SYSTEMS

1. PROCESS IN DATA SYSTEMS

2. Non spatial Finance Library Communication Transportation Spatial earth coordinates DATA STRUCTURES

3. NON SPATIAL Management Information System Decision Support System Office Otomation System Artificial Inteligent System SPATIAL Environmental Info Systems Infrastructural Info Systems Cadastral Info Systems Social-economic Info Systems DATA STRUCTURES

4. GIS DATA STRUCTURES • traditional computer file structures that allow for the storing, ordering and searching of pieces of data • higher level of organisation in the computer called data base structures allow more complex methods of managing data • GIS: graphic data structure, multiple graphic data layers and their databases

5. SPATIAL DATA • POINTS • LINES • AREAS can be represented by their respective symbols • SURFACES most often represented either by point elevationsor other computer structures,

7. POINT FEATURES • Trees, houses, road intersections, and many more. • Each feature is said to be discrete in that it can occupy only a given point in space at any time. • These objects are assumed to have no spatial dimension. Each can be referenced by its locational coordinates

8. LINEAR (LINE) FEATURES • They are conceptualized as occupying only a single dimension in our coordinate space. • Roads, rivers, regional boundaries, fences, hedgerows, or any kind of object that is fundamentally long and very skinny. • Other lines such as political boundaries, have no width dimension to be concerned about. In fact they are not physical entities at all, but rather, a construct of political convention and agreement.

9. LINEAR (LINE) FEATURES • They allow us to measure their spatial extent by simply finding out how long they are. • Two points, a beginning and an ending point. • The more complex the line, the more points we will need to indicate exactly where it is located.

10. AREAS • Objects observed closely enough to be clearly seen to occupy both length and width are called areas. • Two-dimensional objects include the area occupied by a yard, the areal extent of a city, and an area as large as a continent.

11. SURFACES • Adding the dimension of height to our area features allows us to observe and record the existence of surfaces. • Surfaces occur all around us as natural features. Hills, valleys, ridges, cliffs. • Continuous data

12. SPATIAL MEASUREMENT LEVELS • Objects themselves are called entities (coordinates) • Spatial features or entities also have additional information besides spatial information • The additional non-spatial information that helps us describe the objects we observe in space comprises the feature’s attributes

14. GEOGRAPHIC DATA MEASUREMENTS • Range from simply naming objects, to give ourselves something to call them, to precise measurements that allow us to directly compare the qualities of different objects. • Nominal Scale: Named data, no comparison

15. GEOGRAPHIC DATA MEASUREMENTS • Ordinal Scale: From best to worst. The spectrum is based entirely on what we intended to use the information for. • Interval scale: Numbers are assigned to the items measured. • Ratio scale: Most useful, level of data measurement. Allows us to make a direct comparison between two spatial variables.

16. SPATIAL LOCATION AND REFERENCES • Absolute location: It will give us definitive, measurable, fixed point in space.But we must have a reference system against which to evaluate such a location. • Spherical grid system, places two sets of imaginary lines around the earth

17. SPATIAL LOCATION AND REFERENCES • Parallels The angular distance-latitude • Meridians The angular distance-longitude

18. RASTER raster grid cells resolution dots or pixel coverage grid, compact storing of raster data VECTOR X and Y coordinates representative of dimensionality simple network topology Polygon direct translation of the graphic topologically coded network and polygon GRAPHIC DATA

19. NON GRAPHIC DATA • SIMPLE LIST • Simplest file structure is called simple list. • Our names, addresses like creating a separate index card for each name (unordered) • Searching is very inefficient (Suppose your database contains 200000 records)

20. ORDERED SEQUENTIAL FILES • The sequence of alphabetical characters. • Names and addresses in ordered files.

21. INDEXED FILES • It can be developed as direct files or inverted files • Key attribute say a number sequence or alphabetic sequence. Search was based on the key attributes ‘yellow pages’ • Attributes are the primary search criteria and the entities rely on them for selection. We call this an indexed inverted file structure

22. DATABASE • A collection of multiple files is called database. The complexity of working with database system requires a more elaborate structure for management called data base management system. • Hierarchical data structures • network system • relational database structure

23. HIERARCHICAL DATA STRUCTURE • Parent-to child branching • classifying plants and animals • A major advantages of this system is that it is easy to search because the structure is so well defined and easy to expand

24. NETWORK SYSTEMS • This structure allows users to move from data item to data item through a series of pointers • network systems are generally considered to be an improvement over hierarchical structures for GIS work because they are less rigid and can handle many to many reletionships

25. RELATIONAL DATABASE MANAGEMENT SYSTEM • The data are stored as ordered records or rows of attribute values called tuples • Tubles are grouped with data rows in aform collectively called relations • primary key • relational join • graphic representation of entities and attributes