ONTOCOM cost estimation model

Data collection for model calibration

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ONTOCOM background information

In case you have any questions please contact Igor Popov.

Questions marked with a * are required.

 
STI Innsbruck

INTRODUCTION

ONTOCOM is a cost estimation model for the area of Ontology Engineering developed at the Free University of Berlin in collaboration with the Institute AIFB (University of Karlsruhe - TH). ONTOCOM is currently being advanced at STI Innsbruck . It aims at predicting the costs arising in typical classes of ontology engineering processes such as ontology building, ontology reuse or ontology maintenance.

The accuracy of the cost predictions of Ontology Engineering tasks calculated by means of ONTOCOM can be improved by the calibration of the model. This necessitates the collection of real-world ontology engineering project data. In STI Innsbruck we are accomplishing the calibration of the model for the evaluation of the efforts incurred for the creation of some ontologies and this survey serves for the collection of the required data.

ABOUT THIS SURVEY

Developed in the tradition of Software Engineering, ONTOCOM uses a parametric prediction equation which contains product-, personnel and project management-related effort multipliers. The effort multipliers are used to adjust the nominal effort to reflect the particularities of the ontology and of the underlying engineering process. They are rated accordingly with values from Very Low to Very High, depending on their (positive or negative) impact on the nominal development effort.

The survey, consisting of 39 questions, is divided into 4 parts:

  • introductory questions (Questions 1 to 14)
  • product-related questions (Questions 15 to 32)
  • personnel-related questions (Questions 33 to 36)
  • project-related questions (Questions 37 to 39)
For most of the questions you are required to specify the value of a certain effort multiplier, i.e. to position your answer according to a five-step rating scale. If a particular activity induces an increase of the nominal ontology development effort, then it should be rated with values such as High and Very High. In contrast, if it causes a decrease of the nominal costs, then it should be rated with values such as Low and Very Low. Finally, if the corresponding activity does not influence the nominal costs it should be rated with Nominal. THIS APPLIES IN PARTICULAR TO ACTIVITIES WHICH DO NOT APPLY TO YOUR PROJECT SETTING. For each effort multiplier, we suggest decision criteria which could be taken into consideration when assigning the corresponding ratings.

 
*1. Provide the name of the ontology:
 
2. Provide the namespace of the ontology (if available):
 
*3. Please provide a short description of the domain and purpose of the ontology:
 
*4. How many entities does the ontology (approximately) contain?

Please sum the number of concepts, properties, relations, axioms and fixed instances
NOTE: Include also the number of entities of the reused ontologies
 
*5. How many concepts does the ontology (approximately) contain?

 
*6. How many properties does the ontology (approximately) contain?

 
*7. How many axioms does the ontology (approximately) contain?

As a guideline:
RDF(S) ontologies do not contain axioms.
OWL Restrictions or equivalence expressions count as one axiom.
The same applies for rules.
 
*8. How many fixed instances does the ontology (approximately) contain?

Fixed instances in our understanding are completed concept instantiations which never or rarely change in the ontology life time, such as country lists or continent lists.
 
*9. What language did you use for the implementation of the ontology?
 
10. What ontology engineering methodology did you use (if any)?
 
*11. How many person months did you spend in building the ontology?

Please sum the time spent by each participant involved in building the ontology (not to be confused with the duration of the application building process)
Please consider the time to collect initial requirements, the time to build the ontology, the time to test and refine the ontology, and the time to document the process
 
12. What was the average size of the ontology engineering team?
 
13. If you would like further information about the results of the survey please provide your email address below:
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