In this presentation we introduce SAMOD, a.k.a. Simplified Agile Methodology for Ontology Development, a novel agile methodology for the development of ontologies by means of small steps of an iterative workflow that focuses on creating well-developed and documented models starting from exemplar domain descriptions.

1. A Simplified Agile Methodology for
Ontology Development
Silvio Peroni
13th OWL: Experiences and Directions Workshop and 5th
OWL Reasoner Evaluation Workshop
Bologna, Italy, November 20, 2016
Paper: https://w3id.org/people/essepuntato/papers/samod-owled2016.html

2. Inspiration and desiderata
• Desiderata (or long story short)
– Methodology for developing relatively small-/medium-size ontologies quickly
– Advantages of agile methodologies (from Software Engineering)
✦ adaptive planning
✦ evolutionary development
✦ early delivery
✦ continuous improvement
✦ rapid and flexible response to change
– No pair programming: from personal experience, the development of small
ontologies usually involves only one ontology engineer
– Precise definition of different kinds of tests that the model must pass at each stage of
the development, and that can be used for documenting the model as well
• Source of inspiration
– Software Engineering: test-driven development
– Ontology Engineering: other existing agile methodologies, in particular Extreme
Design (XD) – disclosure: I have been a user of this methodology since its
introduction

3. SAMOD
• SAMOD, i.e., Simplified Agile Methodology for Ontology Development, a novel
agile methodology for the development of ontologies
• Small steps of an iterative process that focuses on creating well-developed and
documented models through using significative exemplars of data so as to
produce ontologies that are always ready-to-be-used and easily-understandable by
humans (i.e. the possible customers) without spending a lot of effort
• Why we should use data
– Avoid inconsistencies: a common mistake when developing a model is to make a TBox
(i.e., only classes and properties) that is consistent if considered alone and that becomes
inconsistent when we define an ABox (i.e., individuals and relations between them) for it
– Self-explanatory and easy-understandable models: using data as part of the ontology
development, ontology engineers and developers are obliged to think about the possible
ways users will understand and use the ontology they are developing
– Examples of usage: producing data within the development process means to have a
bunch of exemplars that describe the usage of the model and allows users to apply a
learn-by-example approach in understanding the model and during their initial skill
acquisition phase

4. Basic terms
• Current model: a preliminary/final version of the
ontology under-development/developed
• Modelet: a stand-alone model describing a particular
domain – a modelet does not include entities from other
models and it is not included in other models (it is a
monolithic artefact)
• Test case: a bag containing
– [done by ontology engineer + domain expert] motivating
scenario, informal competency questions, glossary of terms
– [done by ontology engineer] a modelet/current model,
implementation of the examples in the motivating scenario,
implementation of the informal competency questions

5. Material collected with
domain experts
Motivating scenario
Informal
competency
question
Glossary of terms

6. Kinds of tests
• Model test: it aims at checking the validity of the model
against formal (via reasoners) and rhetorical (does it
implement the motivating scenario? does it use appropriate
language?) requirements
• Data test: it aims at checking the validity of the model with the
implemented examples against formal (via reasoners) and
rhetorical requirements (are the examples fully implemented?)
• Query test: it aims at checking the validity of teach SPARQL
query against formal (does each SPARQL query run correctly
on the examples implemented?) and rhetorical requirements
(does the result returned by running the SPARQL query return
the expected values?)

7. The process
SAMOD is an agile methodology for the development of ontologies by means of small steps of an iterative process that
focuses on creating well-developed and documented models through using significative exemplar of data
y
milestone
nGo to the previous
milestone
n
n
y
is there any
further scenario?
did it pass model,
data, query tests?
did it pass model,
data, query tests?
did it pass model,
data, query tests?
end of process
n
if we need to extend
the model in the future
Collect requirements and
develop a modelet
Ontology Engineers (OEs) collect all the information about
a specific domain, with the help of Domain Experts (DEs),
build a modelet formalising the domain in consideration,
and then create a new test case
milestone y
Merge the modelet with
the current final model
OEs merge the modelet of the new test case with the current model
produced by the end of the last process iteration (first
iteration: modelet becomes current model)
Refactor the
current final model
milestone
y
OEs refactor (important: reuse existing knowledge)
the current model, focussing on the last part added in
the previous step

8. From modelets
to the final model
First iteration: modelet
Second iteration: modelet
Final model after
two iterations

9. Experiments
• 9 Computer Science and Law people
– 1 professor
– 2 post-docs
– 6 Ph.D. students
• Task: to use SAMOD (one iteration only) for modelling a
particular motivating scenario provided as exercise
– SAMOD, as well as the main basics in Ontology Engineering, OWL,
and Semantic Web technologies, were introduced to the subjects
during four lectures of four hours each
• Three questionnaires
– Previous experience in Ontology Engineering and OWL
– System Usability Scale (SUS)
– Experience in using SAMOD for completing the task

10. Results
• SUS score: 67.25 (in a 0 to 100 range)
– Usability score: 65.6
– Learnability score: 73.75
• Other insights
– SAMOD evaluated positively by 7 subjects (“useful”, “natural”, “effective”, “consistent”)
– Criticisms by 5 subjects: needs of more knowledge about Semantic Web technologies and Ontology Engineering
– Tests for assessing the ontology developed after a certain step: 3 positive comments vs. 1 negative one
– Scenarios and examples: 3 positive comments
– Implementation of competency questions in form of SPARQL queries: 2 positive comments

11. Conclusions
• SAMOD, an agile methodology for the
development of small-size ontologies
– Each iteration has three steps
• Experiments showed a good level of usability
and learnability
• Future developments
– Involve a larger set of users for testing it
– Develop supporting tools for accompanying and
facilitating users in each step of the methodology

12. Silvio Peroni
silvio.peroni@unibo.it - @essepuntato
Digital And Semantic Publishing Laboratory
Department of Computer Science and Engineering
Alma Mater Studiorum – Università di Bologna
Bologna, Italy
dasplab.cs.unibo.it – www.unibo.it
Thank you for your attention