1 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008 Interface Model Elicitation from Textual Scenarios Christophe Lemaigre, Josefina Guerrero, Jean Vanderdonckt Université catholique de Louvain (UCL) Louvain School of Management (LSM) Information Systems Unit (ISYS) Place des Doyens, 1 – B-1348 Louvain-la-Neuve (Belgium) http://www.isys.ucl.ac.be/
19
Embed
Interface Model Elicitation from Textual Scenarios
During the stage of system requirements gathering, model elicitation is aimed at identifying in textual scenarios model elements that are relevant for building a first version of models that will be further exploited in a model-driven engineering method. When multiple elements should be identified from multiple interrelated conceptual models, the complexity increases. Three method levels are successively examined to conduct model elicitation from textual scenarios for the purpose of conducting model-driven engineering of user interfaces: manual classi-fication, dictionary-based classification, and nearly natural language understanding based on semantic tagging and chunk extraction. A model elicitation tool implementing these three levels is described and exemplified on a real-world case study for designing user interfaces to workflow information systems. The model elicitation process discussed in the case study involves several models: user, task, domain, organization, resources, and job.
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
1 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Interface Model Elicitationfrom Textual Scenarios
Christophe Lemaigre, Josefina Guerrero, Jean Vanderdonckt
Université catholique de Louvain (UCL)Louvain School of Management (LSM)
Information Systems Unit (ISYS)Place des Doyens, 1 – B-1348 Louvain-la-Neuve (Belgium)
http://www.isys.ucl.ac.be/
2 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Introduction and motivations
• Model Elicitation– Consists of
• The identification of model elements• From Textual scenario
– First step of a model-driven engineering process– Selection of several models : user, task, domain, organization,
resource and job• Characterizing the concepts used in the development life cycle
of user interfaces for Worfklow Information Systems
3 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
The underlying ontology
• Reduced view
– Task : piece of work (same resource, location, time period)– Organizational unit : physical location, equipped with resources – User stereotype : human being
Organizational Unit Job Task1..* 1..* 1..* 1..*
Task Resource
User Stereotype Material Immaterial
Process Workflow1..*1..*
*0..1 0..1 * 0..1 *
1..*
1..*
1..* 1..*
isOrganizedInto ► isOrderedIn ►
1..* 1..*
Object Method
Manipulates ►
Invokes ►
*
* * *
4 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
5 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Related work
• Some other tools use model elicitation at some level – U-Tel, ConcurTaskTress, T2T, Garland et al. Brasser &
vanderLinden• Shortcomings :
– Focused on a single model– No attribute elicitation– Result that can hardly be exploited
6 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Methodology and tool support
• We developped an elicitation methodology based on three levels– Manual classification– Dictionary-based classification– Semantic understanding
• And implemented the first and second one in a tool, made of– A text edition part, with syntactic coloration– Trees in which model elements are dispatched
7 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Tool support
• Model Elicitation Tool
8 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Level 1: manual classification
• Definition :– Program user does the elicitation job– Without the help of an automated process
• Method :– Selection of a piece of text from the scenario– Choose the appropriate model and object type
9 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Level 1: manual classification
• Tool : elicitation of a task
1 2
3
10 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Level 1: manual classification
• Advantages : – Accurate result– Easier to implement than automated elicitation– No need of classification datas
• Inconvenients : – Fastidious for the user– Time costly
11 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Level 2: dictionary-based classification
• Definition :– Underlies on a set of predefined terms that will be automatically
extracted and identified as model objects– Two kinds of dictionaries :
• Generic dictionary, which is domain-independant • Specific dictionary, linked with a definite domain
• Method :– Improved pattern-matching process :
• Based on the recognition of phrases• That are associated with their model definition• Plural forms and conjugation are taken into account (e.g. to
provide // providing)
12 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Level 2: dictionary-based classification
• Tool : elicitation of jobs using a dictionary
13 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Level 2: dictionary-based classification
• Advantages : – Processing speed– No human intervention needed
• Inconvenients : – Lack of precision, some elements being poorely classified due to
the fact it is context-independant– No relations between elements (e.g. hierarchy)
14 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Level 3: toward semantic understanding
• Definition :– Try to approximate natural language understanding
• Method :– Using syntactic tagging, semantic tagging and chunk parsing.– Detection of
• Concepts such as task types or attribute types• Relationships between model elements
– No tool support currently
15 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Level 3: toward semantic understanding
• Concrete example– “An accountant receives taxes complaints, but he is also in
charge of receipts perception”– Model elements :
• Task : receive taxes complaints• Task : charge of receipts perception• Job : accountant• Relation “performed by” between those tasks an the job • Temporal operator : concurrency for the tasks, used by default
16 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Level 3: toward semantic understanding
• Advantages : – Expressivity, being able to deduce relationships between model
elements– Automatic treatement
• Inconvenients : – Difficult to implement– Natural language understanding is a field of informatics research
that needs a lot of work and improvement
17 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
After model elicitation
• Once elicitation job is done, some treatments can be performed– Use of syntactical coloration allowing the user to check its work– Verification of the compliance with some desirable quality
properties– UsiXML export, allowing to use tools like IdealXML or FlowiXML to
edit models and derivate user interfaces
18 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Conclusion and future work
• Methodology and tool support– Combination of three complementary methods– Allowing elicitation of elements from several models and relations
between those elements– Oriented towards user-interfaces generation for workflow
information systems– Implemented in a tool, using Usi-XML standard to export its result
• Future works :– Advanced visualisation (e.g carrousel)– Take into account inter-model relationships– Refine the third level towards a more natural language
understanding
19 HCIS’2008 – Milan, September 8-9th, 2008, during IFIP World Congress 2008
Thank you very much for your attention
For more information and downloading,http://www.isys.ucl.ac.be/bchi
http://www.usixml.orgUser Interface eXtensible Markup Language
http://www.similar.ccEuropean network on Multimodal UIs