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SURVEY 
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INDEX_1 
R0AD_17 PT 921 .. . PT 1004 
INDEX_2 
WELL_2 3 
PLAN 24 PT 5197 . . . PT 5203 
INDEX_3 
R0AD_17 PT_1004 . . . PT_1029 
PLAN_92 
INDEX_4 
R0AD_17 PT_1029 . . . PT_1102 
PLAN 24 PT 5203 . . . PT 5197 
sets. Restricted access (such as read-only access) 
for certain classes of users, oi different "user 
views", can be provided by means of different 
subschemas. And, on the VAX-11 DBMS in particular, 
retrieval efficiency can be optimized by means of a 
storage schema, which provides details on such 
things as indices, and attempts to store related 
items on the same page of disk storage. 
5.2 Infological Model 
The infological model is related to human concepts 
and real world representation. In other words the 
data are organized in terms of representing reality 
the way humans perceive it. The most common 
infological model is a hierarchical tree structure 
which would break the data into levels as shown in 
Figure 4. This type of model is feasible to 
implement in a database but it does have some 
limitations. If there are a large number of classes 
near the root of the tree it is difficult to 
navigate around the data to establish and utilize 
the various relationships. This type of model also 
has a problem with data redundancy, which arises 
from the need for each entity to have its own 
non-unique attributes. This results in 
nonstandardized entity/attribute records, where a 
geology polygon would require fewer record fields 
than the same polygon representing surface cover. 
Figure 3. Spatial indexing 
define connections between different record types. 
These connections are defined by means of DBTG 
(Database Task Group) sets. 
The relational approach offers the advantage of 
flexibility, since there are no pre-defined link 
ages. Any query that can be formulated in the query 
language can be accomplished. For this reason, 
relational DBMSs, such as ARC/INFO (Dangermond and 
Freedman, 1984), are popular for LRIS design. The 
network approach, on the other hand, offers the 
potential advantage of greater efficiency of those 
queries for which suitable linkages have been 
pre-defined. Of course, when suitable DBTG sets 
have not been pre-defined, a query may either be 
impossible or very inefficient to answer. In a 
network database one is said to "navigate" through 
the database, and in such a database system it is 
necessary to structure the record types and DBTG 
sets in such a way tnat frequently occurring queries 
can be satisfied by relatively simple navigation 
through the database. 
As a general rule, the inclusion of more DBTG sets 
improves retrieval speed, but may make the speed of 
updating, both insertion of new records and changing 
values in existing records, slower, because more 
pointers and indexes must be changed. In the 
current project much of the data is not volatile; 
much of it will change rarely, if ever. Even those 
data that do change will not need to be updated in 
"real-time". Consequently, the design of the 
database is oriented toward efficient retrieval at 
the cost of slower updates. 
GEOLOGY 
SURFICIAL BEDROCK 
ALLUVIUM COLLUVIUM AEOLIAN SEDIMENTARY METAMORPHIC IGNEOUS 
Figure 4. Hierarchical infological model 
With these limitations in mind, a different 
infological model has been designed. This model 
also takes into account the nature of the network 
database model, which allows definition of backwards 
and forwards file pointers. This infological model 
utilizes paradigm files to reduce redundancy and to 
allow easier navigation and establishment of rela 
tionships. A paradigm file contains a set of 
standardized entity attribute records as shown in 
Table 2. 
Table 2. 
Geologic bedrock paradigm 
file. 
Geologic 
Geologic 
Formation 
Rock 
Structure 
code 
age 
name 
type 
D 
Devonian 
undiff 
Dbf 
Devonian 
Banff 
Dbw 
Devonian 
Bow 
J 
Jurassic 
undiff 
Jcl 
Jurassic 
Coleman 
This prototype LRIS will use the VAX-11 DBMS, 
which is a "CODASYL compliant" network data base 
management system, and which runs under the VMS 
operating system on a DEC VAX-11/750. A good 
Fortran interface, and the retrieval efficiencies 
that are possible with a network database system are 
among the reasons for choosing it. As with all 
CODASYL network DBMS's, a database is defined by 
defining a schema, which contains, among other 
things, definitions of the record types and the DBTG 
These paradigm files are very stable, allowing easy 
updating and multiple entry to and from various 
different entities. Thus, it is possible to 
standardize the basic entity attribute record 
structure by utilizing the pointers to these files 
as shown in Figure 5. This reduces data redundancy 
in many cases and provides a framework for the 
definition of the relationships between the various 
data.