“bl - 
from this examplei For- a factual data base -- e.g. on. me- 
tals properties - this work has to be done in advance. So 
pairs of values of alloy designation and heat conductivity 
must be extracted from the documents for data input. But 
this may be not sufficient for the following reason: 
In a document the whole context for which a value is valid 
can be reported in free text form. In a factual data base 
the documentation of the context must be provided for in 
the data base structure. The heat conductivity e.g. de- 
pends on the temperature and the chemical composition (fi- 
gure 1), and an individual value may be influenced by the 
measuring procedure. 
From this the question arises what is the correct value of 
the heat conductivity of say pure copper (how pure? There 
is no absolutely pure MLS Different values will be 
found in the literature. Shall all values be documented or 
one validated value only. Who is responsible for the vali- 
dation? 
And what about an alloy designated by its name? Such an 
alloy has an allowed range for its chemical composition. 
Therefore samples of the "same" alloy with a different 
chemical composition must have different values of the 
heat conductivity in addition to measuring uncertainties. 
The result of all these questions is that in the design 
phase of a factual data base a thorough analysis has to 
be performed and some decisions have to be made according 
to the purpose of the planned information system: 
- Which types of objects and which properties of them 
shall be containd in the data base? 
- Which influencing factors on a property have to be 
documented? 
- Shall the data base contain raw data or validated 
data? 
- If validiation: Which type of value is needed for 
each property ("true" value, upper and/or lower 
limit, mean value); how is it performed; how is 
it adapted to future developments? 
- Is there a need for further processing of retrieved 
data and which kind of processing? 
If a comparison is drawn with literature data bases the 
following is valid in general for factual data bases: 
- The scope is relatively narrow. 
- The input is relatively expensive. 
- The output is more specific to certain tasks. 
- The system can easier be extended to new types of 
objects or to new methods of data evaluation. 
Dahte 2