e-collaboration and knowledge sharing based on text notes
DESCRIPTION
e-Collaboration and Knowledge Sharing based on Text Notes. EMBET System Institute of Informatics, SAS Michal Laclavik. Overview. Applications Motivation, history Experience Management Approach EMBET Architecture Ontology GUI Examples. Application of the system. - PowerPoint PPT PresentationTRANSCRIPT
e-Collaboration and Knowledge Sharing based on Text Notes
EMBET SystemInstitute of Informatics, SAS
Michal Laclavik
Overview
Applications Motivation, history Experience Management Approach EMBET Architecture Ontology GUI Examples
Application of the system
Collaboration among users Knowledge Sharing Recommendation
Representation of Experience or Knowledge Text Notes
Motivation, History
In Pellucid IST Project Active Hint approach AH = action on resource(s) in context + explanation Many AHs in Pellucid:
See Text Note in this context because is useful
Text Notes Natural way for people If we are able to detect context of note - note can help
others better then other formalized knowledge People like to enter notes or memos to remind something
to themselves or others
Experience Management Approach
Problem p Problem Space (P) In EMS Case-Lesson pairs (c, l)
Case Space (C) lesson space (L).
maps problem space to case space c = f(p)
General vs. EMBET Approach
General EM Approach Characterize a problem Transform the problem from the space P to the space C. Choose from the cases the most "useful" lesson from the case-lesson
pairs stored in the database Apply that lesson.
EMBET EM Approach User context detection from environment which describes problem P Our Model is described by ontology and Notes are stored with
associated context, which describes space C Notes represent learned lesson L which is associated with space C
(note context). The note context is matched with a user problem described by the detected user context. The user context is wider than the note context and as a result all applicable notes are matched and returned.
Applying the lesson is left to the user be reading appropriate notes.
User enter a Note
Pattern DetectionAnnotation of
Note with context
Compare current user context
and Note context
Displaying Context List
User approve and submit
Context of note
Notes are displayed to user in
detected user context
Vote on Note,updating Relevance
Knowledge Cycle
Architecture
XML messages
JSPPages
HTML Output
JSTL
XSLT Style Sheets CSS
UAA GUI
RDFOWL
XML messages
KnowledgeNotes
FeedbackOn
knowledge
UpdateKnowledge
ContextUpdate
UAA Core
KnowledgeNotes
Detection
ContextDetection
StoreKnowledge
GOM
Ontology
System GUI
Example Note:
the ALADIN model is not appropriate for weather forecast in late fall because it gives results which differ approx. 50% from reality
Dealing with a problem of Floods □
Running model for Meteorology □
Running Service type ALADIN ■
Running Service Instance for ALADIN located in Slovakia
□
In late fall (October – November) ■
Other (specify) □
Examples In High Tatra mountain 40% of snow can sublimate Precipitation measuring tools are not used during the winter,
consider this in models computing floods especially in spring because you will have not proper precipitation data
In area of East Slovakia most of the floods are caused by flash rains in spring
Intensity of flash rains can be discovered by vertical balloon measurement – quite expensive, find correct intensity of measurement when needed
context: location, time, model You are not able to predict weather for 1km2 because grid
size is 3x3km context: model, input data, output data
Examples
Water levels for Slovakia can be found at http://www.povodia.sk/ context: input data, location
Notes comparing modeled output data with historical real data or historical model output data context: model, output data, historical data, real data
Notes for performance prediction, monitoring or other – notification from K- Wf Grid system (WP2, WP3, KAA)
Thank you !
Institute of Informatics, SASMichal Laclavik