This paper outlines the design process that is used to create Topic Maps Ontologies for space experiments in a wide range of scientific disciplines. This design process is implemented in three iterations, one for creating initial Topic Maps Ontologies and two for further refinement. The paper focuses on the first iteration that consists of nine workshops with various providers of space experiment data, each active in a different scientific domain. Furthermore, we report our findings in holding these workshops.
18. Results 01/18/10 Task Tool Result Enumeration (identifying terms) Microsoft Excel Word List Categorization (grouping terms) CMapTools Concept Map Organization (modelling taxonomical relationships) CMapTools Concept Map Organization (modelling ontological relationships) CMapTools Concept Map Organization (transforming into Topic Maps Notation, including Scopes, Roles, Occurrences) Microsoft PowerPoint Ontology in simplified GTM notation
19. Results – Fluid Science 01/18/10 Eckmann number I of characteristic number X educational AT unary AT: of experiment X electric pole TT AT: "hardware" "composed-of" "electric pole" X electrical conductivity I of physical property electrical power TT of current. AT: "experiment" "uses" "electrical power" X electromagnetic force TT subtype of body force X energy TT variable/parameter (cfr.velocity, temperature) engine TT AT: "hardware"/"facility" "composed-of" "engine" X environmental temperature I of boundary condition X equation TT AT: "mathematical model" "is-made-up-of" "equation"; AT:"mathematical model" "is-made-up-of" "boundary condition" ESA I of space agency X evaporation I of physical phenomenon X experiment TT instances are FASES, … AT: "experiment" "is-performed-in" "exp. Facility". AT: "experiment" "studies" "physical phenomenon" X experiment output TT AT: "experiment" "produces" "experiment output" X experiment result TT AT: "experiment" "produces" "experiment result" X experiment setup TT AT: "experiment" "describes" "experiment setup" X
7 scientific disciplines: Material Science Fluid Science Cell Biology Plant Biology Solar Physics Physiology Technology
And lots of experience at SpaceApps
The original Ontology Creation Workflow as designed by L.M. Garshol.
Changes made to the Ontology Creation Workflow as designed by L.M. Garshol: Move End-user phase into Analysis phase Remove Interaction Design phase Also (not shown): Perform Draft phase during Ontology Workshop Used simplified GTM for notation.
The updated Ontology Creation Workflow as used in ULISSE.
9 workshops over 2,5 months 27 scientists/engineers involved
3-day session Day 1: Present Topic Maps, Learn about the domain Day 2: Dump Domain Knowledge Day 3: Structure Domain Knowledge
Make sure you understand Topic Maps Technology Story : Workshop @ CNES, lots of tricky questions
Give lots of examples Use examples that “work” Do not expect domain experts to just accept that Topic Maps is the right solution.
For ULISSE: mostly scientist/engineers Different kinds of domain experts will have different backgrounds that you can take into account
Switch to examples of the domain as quickly as possible. Let domain experts talk. You can make suggestions and keep them on course, but once they get going, do not interfere. Afterwards, summarize what they said when you note it down to make sure you understood it correctly. Use tools they already know (typically, Microsoft Office).
First we told everything in one presentation. Afterwards we first focus on Topics and Associations when structuring domain knowledge, and we gradually brought in Occurrence Types, Role Types and Scopes.
Scared and nervous myself before each workshop. Trust your preparations. Trust yourself. You will make wrong suggestions.
For them it might even be worse, but they don’t always know in advance. Domain experts are confronted with their own knowledge of the domain. Story : Some domain experts likened it with being a student again.
Part of the word list for Fluid Science
Part of the concept map for Physiology Experiments
Part of the General Space Experiments Ontology.
Be prepared to make suggestions that turn out wrong a lot.