Extended Wiki Scenario (was Re: Review of Use-Case Document)

Thanks Harry for your feedback on the wiki scenario.
The online version of the file seems to be locked so here is
an extract of the scenario including the "history of Michel the lecturer".

Fabien.


Use case #2 - Wikis and e-learning: The Technical University of Marcilly 
decided to use wikis to foster knowledge exchanges between lecturers and 
students.
The Technical University of Marcilly (TMU) decided to use wikis to 
foster knowledge exchanges between lecturers and students. They tested 
several wikis over the years and they want to experiment with novel ways 
of structuring the wiki to improve navigation and retrieval. They also 
want to make it easier to reuse learning objects in different contexts. 
Ideally TMU wants the information structuring the wiki to be:

   1. easy to add, edit, enrich and this should be done at the same time 
a user edits a page to avoid multiplying interfaces and manipulations.
   2. explicit and understandable to machines so that the wiki engine 
can rely on it to propose related pages, to perform precise search, to 
generate browsing interfaces, to build dynamic indexes based on 
customized queries and to provide customized sorting and filtering for them.
   3. accessible to other applications to allow integration with other 
information systems, links or migration to other wiki engines, extension 
of its functionalities, etc.

In this context TMU uses metadata embedded in the wikipages to:

    * store the results of social tagging on the pages: tags suggested 
by users are inserted in the page itself and may reuse data from the 
page (e.g. the authors name) or annotate specific portions of the page 
(e.g. type a paragraph as a definition, categorize an image);
    * generate navigation widgets: lists of forward and back links to 
navigate the wiki, lists of similar pages, list of all pages tagged with 
a specific topic, view of the clusters of pages, etc.
    * enrich them with schemata to restructure the wiki (declare 
equivalent tags, broader/narrower tags, add synonymous labels to 
existing tags, etc.) and enrich the navigation with these links;
    * include queries on these metadata in the wikipages to dynamically 
generate tailored indexes for the different departments, the different 
years, the different topics, etc.
    * import learning objects edited in classical word processing 
application by using the styles of the different sections to extract 
annotations for each section and recompose new documents (e.g. transform 
a handout into a web site for practical sessions).

Let us consider the case of Michel, a lecturer in engines and 
thermodynamics. He used the wiki to publish the handouts of his course. 
He initially tagged each handout with the main concepts it introduces 
(e.g. "RenewableEnergies", "Ethanol", "Diesel"). In addition, Michel 
automatically typed each section of the document using predefined styles 
(e.g. definitions, formula, example, etc.). The next practical session 
will involve knowledge on classical Diesel engines and Ethanol-based 
engines. In order to generate a mnemonic card for this session Michel 
runs a query to extract definitions and formulas of the courses tagged 
with "Diesel" or "Ethanol". He also uses these tags to generate dynamic 
"see also" sections at the end of his sections suggesting other sections 
to read.
Students edit the online handouts, to add pointers, to insert comments 
on part they found difficult to understand, to recall pieces of previous 
courses useful for understanding a new course, etc. Students also tagged 
the pages with their own tags to organize their reading and bookmark 
important parts for them; they use tags to create transversal thematic 
tracks (e.g. "LiquidFlow"), to give feedback on the content (e.g. 
"Difficult"), to prioritize reading (e.g. "NiceToKnow", "Vital"). These 
tags allow them to have transversal navigation and reorganize the 
content depending on the task they are doing (e.g. preparing an exam, 
writing a report, running an experiment). These tags are also used by 
Michel to evaluate the understanding and the shortcomings of his course.
Finally the mass of the course material and tags is such that it needs 
to be reorganized. Using the tag editor Michel groups "Ethanol" and 
"Methanol" as sub tags of a new tag he calls "Alcohol". Doing so the 
pages tagged with "Ethanol" or "Methanol" are grouped and accessible 
through "Alcohol". He repeats this with other tags (e.g. "Alcohol" and 
"Hydrogen" becomes sub- tags of "NewEngineEnergy"). This reorganizes the 
wiki seamlessly e.g. suggestion of navigation in the pages automatically 
propose narrower, broader and brother tags thus when viewing a page 
tagged with "Ethanol", the system suggest other pages tagged with 
"Methanol". Later when a student posts his report on an engine using 
"CopraOil", his new tag can be placed under the existing one 
"NewEngineEnergy"; he or anyone else can do it and the result will 
immediately benefit the whole community of the users. Using these tags 
and their organization, thematic indexes are dynamically generated for 
the materials of the course and automatically updated.

 From the technical stand point, TMU designed a wiki that stores its 
pages directly in XHTML and RDF annotations are used to represent the 
wiki structure and annotate the wikipages and the objects it contains 
(images, uploaded files, etc.). The RDF structure allows refactoring the 
wiki structure by editing the RDF annotations and the RDFS schemas they 
are based on. RDF annotations are embedded in the wiki pages themselves 
using the RDFa and microformats. Some of the learning objects can be 
saved in XML formats and an XSLT stylesheet exploits the styles used for 
the session to tag the different parts (e.g. definition, exercise, 
example) and these annotation can then be used to generate new views on 
this resource (e.g. list of definition, hypertext support for practical 
sessions, etc.).

Using RDFa and GRDDL in wikis
The embedded RDF is extracted using a GRDDL XSLT stylesheets available 
online to provide semantic annotations directly to the application that 
needs to extract the embedded metadata:

    * if someone sends a wiki page to someone else the annotations 
follow it and can be processed by applications of the recipient;
    * if another application crawls (e.g. the crawler of a search 
engine) the wiki site it can extract the metadata and reuse them just by 
applying the same GRDDL transformation;
    * if a new community of practice of TMU (e.g. the accountants) wants 
a dedicated index of its working document, it can be embedding the 
corresponding SPARQL query in a wikipage: the search engine fed with the 
GRDDL results solves this query and the result is rendered by an XSLT 
stylesheet and embedded in the page;
    * if the wiki engine is to be changed, the migration transformations 
can exploit the embedded metadata;
    * if a division wants to setup access rules to some documents, they 
can be based on these metadata merged with others (e.g. only lecturer 
can access document tagged as "tests").
    * if some users are interested in being informed on any new 
information on a topic (e.g. chemists want to be informed on any new 
norm for the environment) they can use notification systems monitoring 
the wiki by querying its metadata (e.g. recurrent SPARQL queries on 
pages tagged with "environment")


-- 
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Received on Tuesday, 29 August 2006 14:42:59 UTC