Databases, design, and organisation

        A data definition language

        A data dictionary

        A data entry module

        A data update module

        A report generator

        A query language

 

Data definition language (DDL):

DDL is the language used to describe the contents of the database (Modarres, 1998). DDL is the part of the DBMS that is allows the user to set up a new database, to specify how many attributes there will be what types and lengths or numerical ranges of each attribute will be and how much of the user is allowed to do (Clarke, 1997).

It is used to describe, for example, attribute names (field names), data types, location in the database, etc.

This establishes the data dictionary, a catalog of all of the attributes with their legal values and ranges.

The most management function is data entry, and since most entry of attribute data

Monotonous and may be by transcription from paper records, the DBMS's data-entry system should be able to enforce the ranges and limit entered into the data dictionary by definition language.

All data entry is subject to error, and first step after entry should be verification, and after that updated to reflect change.

Then the DBMS can be used to perform functions such as sorting, reordering, subsetting, and searching; to do so requires the use of query language, the part that allows the user to interact with the data to perform those tasks(Clarke, 1997).

Data manipulation and query language: Normally a fourth-generation language (4GL) is supported by a DBMS to form commands for input, edit, analysis, output, reformatting, etc. Some degree of standardisation has been achieved with SQL (Structured Query Language) (Modarres, 1998).

DBMS queries are sorting, renumbering, subsetting, and searching.

The query language is the user interface for searching.

GIS DATABASE

INTRODUCTION

The real world is too complex for our immediate and direct understanding. We create "models" of reality that are intended to have some similarity with selected aspects of the real world. Data bases are created from these "models" as a fundamental step in coming to know the nature and status of that reality (Modarres, 1998). 

The Geographical Information System (GIS) has two distinct utilisation capabilities - the first pertaining to querying and obtaining information and the second pertaining to in tegrated analytical modelling. However, both these capabilities depend upon the core of the GIS - the database that has been organised. Many a GIS utilisation have been limited because of improper database organisation. The importance of the GIS database stems from the fact that the data elements of the database are closely interrelated and thus need to be structured for easy integration and retrieval. The GIS database has also to cater to the different needs of applications. In general, a proper database organisation needs to ensure the following [Healey, 1991; NCGIA, 1990]:

        flexibility in the design to adapt to the needs of different users.

        a controlled and standardised approach to data input and updation.

        a system of validation checks to maintain the integrity and consistency of the data elements.

        a level of security for minimising damage to the data.

        minimising redundancy in data storage.

While the above is a general consideration for database organisation, in a GIS domain the considerations are pertinent with the different types and nature of data that need to be organised and stored.

 

What is a database?

Database: is a large collection of data in a computer system, organized so that it can be expanded, updated, and retrieved rapidly for various uses. It could be a file or a set of files (Ronli, 1999). File: is a collection of organized records of information. A record has usually a record number and record content. The file has a name give by the system or user (Ronli, 1999).

 

A database is a collection of information related to a particular subject or purpose, such as tracking customer orders or maintaining a music collection (microsoft, 1997).

 

Database: is self-describing collection of integrated records (Kroenke, 1995)

Database is self-describing: It contains, in addition to the user's source data, a description of its structure. This description is called a data dictionary (or data directory or metadata). It is the data dictionary that makes program/data independence possible.

A database is a collection of integrated records: Bits are aggregated into bytes or characters; characters are aggregated into fields; fields are aggregated into records; and records into files. Bits - characters - fields - records -files

Others are metadata, indexes that are used to represent relationship among the data and also to improve the performance of database application, the database often contains data about the applications that uses the database. The structure of data entry form, or a report, is sometimes part of the database, which is called application metadata. Thus, database contains four types of data: files of the user's data, indexes, and application metadata.

Files + metadata + indexes + application = Database.

 

A spatial data base is a collection of spatially referenced data that acts as a model of reality. 

Spatial database: stores GEOREFERENCED data. For example, wells with their locations, bank account holders with addresses, and property taxes with boundaries

 

 

INTRODUCTION TO DATABASE PROCESSING

A successful GIS begins with a database, so it important to first take a look at database

In GIS, the database is important as its creation will often account for up to three-quarters of the time and effort involved in developing a geographic information system. (Kenneth et al, 1996).

It is important, however, to view these GIS databases as more than simple stores of information. The database is used to abstract very specific sorts of information about reality and organize it in a way that will prove useful. The database should be viewed as a representation or model of the world developed for a very specific application (Kenneth et al, 1996). There are very many things involved in the design of a database.

 

GIS has become more powerful as database products has be more powerful and database technology more accessible (Kroenke, 1995). This has been so because

        The personal computer DBMS have become more powerful and easier to use, and their price has decreased substantially. Products such as Microsoft's access not only provide the power to a true relational DBMS on a PC, but also include facilities for developing GUI-based forms, reports, and menus.

        The new modelling methodologies and tools, especially those based on the object-oriented thinking, have become available. studies show that semantic object modelling( say with SALSA) to be far superior to the old techniques, such as the entity-relationship modelling (say with IEF) approach: able to create better models, faster, and with greater satisfaction

        There has the emergence of client server processing in general and especially client server database processing in particular. This enables companies to download main frame to a server database on a PC, making ease for personal to access to database.

 

THE DATA IN DATABASE

Broadly categorised, the basic data for the GIS database has two components:

a) Spatial data - consisting of maps and which have been pr-pared either by field surveys or by the interpretation of Remote-ly Sensed (RS) data. Some examples of the maps are the soil survey map,geological map, landuse map from RS data, village map etc. Much of these maps are available in analog form and it is of late that some map information is available directly in digital format. Thus, the incorporation of these maps into a GIS depends upon whether it is in analog or digital format - each of which has to be handled differently.

b) Non-spatial data - attributes as complementary to the spatial data and describe what is at a point, along a line or in a polygon and as socio-economic characteristics from census and other sources. The attributes of a soil category could be the depth of soil, texture, erosion, drainage etc and for a geological category could be the rock type, its age, major composition etc. The socio-economic characteristics could be the demographic data, occupation data for a village or traffic volume data for roads in a city etc. The non-spatial data is mainly available in tabular records in analog form and need to be converted into digital format for incorporation in GIS. However, the 1991 census data is now available in digital mode and thus direct incorporation to GIS database is possible.

 

Data input In database

There are very many methods of data entry in database, these include use of advancing technologies, such as scanning, feature recognition, raster-to-vector conversion, and image processing, along with traditional digitizing and key entry methods (Kroenke, 1995).

Digitizing on a tablet captures map data by tracing lines from a map by hand, using a cursor and an electronically-sensitive tablet. The result is a string of points with (x, y) values.

Scanning places a map on a glass plate, and passes a light beam over it measuring the reflected light intensity. The result is a grid of pixels. Image size and resolution are important to scanning. Small features on the map can drop out if the pixels are too big.

Attribute data can be thought of as being contained in a flat file. This is a table of attributes by records, with entries called values.

 

How data is represented in database

Kenneth et al, 1996).

It is important to realize that this non-spatial data can be filed away in several different forms depending on how it needs to be used and accessed. Perhaps the simplist method is the flat file or spreadsheet, where each geographic feature is matched to one row of data

 

Flat Files and Spreadsheets

A flat file or spreadsheet is a simple method for storing data. All records in this data base have the same number of "fields". Individual records have different data in each field with one field serving as a key to locate a particular record (Kenneth et al, 1996). For a person, or a tract of land there could be hundreds of fields associated with the record. When the number of fields becomes lengthy a flat file is cumbersome to search. Also the key field is usually determined by the programmer and searching by other determinants may be difficult for the user. Although this type of database is simple in its structure, expanding the number of fields usually entails reprogramming. Additionally, adding new records is time consuming, particularly when there are numerous fields. Other methods offer more flexibility and responsiveness in GIS.

 

Hierarchical Files

Hierarchical files store data in more than one type of record. This method is usually described as a "parent-child, one-to-many" relationship (Kenneth et al, 1996). One field is key to all records, but data in one record does not have to be repeated in another. This system allows records with similar attributes to be associated together. The records are linked to each other by a key field in a hierarchy of files. Each record, except for the master record, has a higher level record file linked by a key field "pointer". In other words, one record may lead to another and so on in a relatively descending pattern. An advantage is that when the relationship is clearly defined, and queries follow a standard routine, a very efficient data structure results. The database is arranged according to its use and needs. Access to different records is readily available, or easy to deny to a user by not furnishing that particular file of the database. One of the disadvantages is one must access the master record, with the key field determinant, in order to link "downward" to other records.

 

 

Relational Files

Relational files connect different files or tables (relations) without using internal pointers or keys. Instead a common link of data is used to join or associate records. The link is not hierchical (Kenneth et al, 1996). A "matrices of tables" is used to store the information. As long as the tables have a common link they may be combined by the user to form new inquires and data output. This is the most flexible system and is particularly suited to SQL (structured query language). Queries are not limited by a hierarchy of files, but instead are based on relationships from one type of record to another that the user establishes. Because of its flexibility this system is the most popular database model for GIS. They remain the dominant form of DBMS today (Clarke, 1997).

They are simple, and user's standpoint is an extension of the flat file model. The major difference is that a database can consist of several flat files, and each can contain different attributes associated with a record.

 

 

 

Flat, Hierarchical, and Relational Files Compared

Structure	Advantages	Disadvantages
Flat Files	        Fast data retrieval         Simple structure and easy to program	        Difficult to process multiple values of a data item         Adding new data categories requires reprogramming         Slow data retrieval without the key
Hierarchical Files	        Adding and deleting records is easy         Fast data retrieval through higher level records         Multiple associations with like records in different files	        Pointer path restricts access         Each association requires repetitive data in other records         Pointers require large amount of computer storage
Relational Files	        Easy access and minimal technical training for users, as data is kept in different files.         Flexibility for unforeseen inquiries as it allows to assemble any combination of attributes and records as long as they are linked by a key attribute.         Easy modification and addition of new relationships, data, and records         Physical storage of data can change without affecting relationships between records	        New relations can require considerable processing         Sequential access is slow         Method of storage an disks impacts processing time         Easy to make logical mistakes due to flexibility of relationships between records

 

Now, let us consider a couple of examples of matching applications to database structures.

 Exploratory research--flat files are easy to organize, space is not particular problem

 Government agencies--hierarchical systems are particularly attractive

 Planning and development--relational might be justified for flexibility

 

 

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