Difference between revisions of "Umea 2013 Wiki WorkshopA"

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(Exercise: produce your own question for the Umea FAQ)
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==Exercise: produce your own question for the Umea FAQ==
 
==Exercise: produce your own question for the Umea FAQ==
 
# Discover the wiki content  
 
# Discover the wiki content  
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# Copy the query in your wiki page
 
# Copy the query in your wiki page
 
# Add some explanations / comments (why this query, for whom is it relevant, what about the results, why relevant?) > see the  [http://upload.wikimedia.org/wikipedia/commons/f/fb/Welcome2WP_English_Flap_081810.pdf  wikimarkup quick reference] or a [http://en.wikipedia.org/wiki/Help:Wiki_markup more detailed help]
 
# Add some explanations / comments (why this query, for whom is it relevant, what about the results, why relevant?) > see the  [http://upload.wikimedia.org/wikipedia/commons/f/fb/Welcome2WP_English_Flap_081810.pdf  wikimarkup quick reference] or a [http://en.wikipedia.org/wiki/Help:Wiki_markup more detailed help]
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== Wiki basic concepts ==
 
== Wiki basic concepts ==

Revision as of 09:53, 25 April 2013

Exercise: produce your own question for the Umea FAQ

  1. Discover the wiki content
    1. DSS descriptions, Case Studies and Lessons Learned documentation
    2. Check for the properties likely to be useful for querying
  2. Formulate your question > see below the wiki basic concepts and examples of questions
  3. Create a wiki page about your question > see the following example Question: Which DSSs were developed by large team of people
  4. Produce the semantic query > semantic search
  5. Copy the query in your wiki page
  6. Add some explanations / comments (why this query, for whom is it relevant, what about the results, why relevant?) > see the wikimarkup quick reference or a more detailed help


Wiki basic concepts

Wiki page

> Basic unit of a wiki, shared knowledge about a concept

> Content:

  • Text + resources (e.g., images)
  • Formatting > highlight important aspects (bold), list of items, table
  • Structure > organise the content of a wiki page in sections; e.g.: =header of main level=
  • Hyperlink > link to other wiki pages or outside of the wiki; e.g.: =[[main page]] [[http://www.forestdss.org]]=

Category

> Classification of wiki pages

> Markup: [[Category:category name]]

> Example: [[Category:DSS]] ... means: the wiki page belongs to the category DSS

Protperty

> Formalisation of some specific aspects of the content of a wiki page (basically single words or combinations thereof)

> Markup: [[property name::value]]

> Example: [[has country::Sweden]] ... means: the wiki page is characterised by the fact that it is related to Sweden

Semantic search

> semantic queries to select wiki pages

> Tool: semantic search wiki page

Example with category: [[Category:DSS]]

Result: all DSSs, respectively a list of all wiki pages with the category „DSS“

Example with property: [[has country::Sweden]]

Result: all wiki pages related to Sweden, respectively a list of all wiki pages with the property „has country“ and the value „Sweden“ for this property

Example with category and property: [[Category:DSS]] [[has country::Sweden]]

Result: all DSSs related to Sweden, respectively a list of all wiki pages with the category „DSS“, as well as the property „has country“ and the value „Sweden“

Example with subqueries > semantic sub-queries to search across interconnected wiki pages [[property 1.property 2::value of property 2]]

Automatic search procedure:

  1. Select all wiki pages with property 2 and the target value(s) of property 2
  2. Select all wiki pages with property 1 and at least a selected wiki page of step 1 as value of property 1

Precondition: value type of property 1 is wiki page

Example: [[has country.has forest area::>1000000 ha]]

Result: All wiki pages related to a country whose forest area is larger than 1’000’000 ha, respectively all wiki pages with the property „has country“ with a value that points to a wiki page, which has the property “has forest area” and a value for this property that is higher than 1’000’000 ha.

Some examples of questions

Which DSSs were developed by a team of at least 5 people?

Query: [[Category:DSS]][[Has DSS development.Has development team size::>5]]

Results: AFFOREST-sDSS, CONES, EFIMOD, EMDS, ETÇAP, EcologicalSiteClassification, LEaRNForME, PYL, ProgettoBosco, SIPAFIT, ToSIA

Embed code {{#ask:[[Category:DSS]][[Has DSS development.Has development team size::>5]] |format=list |limit=20 |offset=0 }}


Which DSSs support the process of evaluating options?

Query: [[Category:DSS]][[Has support for social participation.Has participatory planning task::Evaluating options]]

Results: CONES, ClimChAlp, DSD, EFIMOD, EMDS, FORFUN, Heureka, MyTestDSS, PEB, PLANFLOR, PYL, SiWaWa, WIS.2, YAFO


Which DSSs support the process of evaluating options at forest and strategic level?

Query: [[Category:DSS]][[Has support for social participation.Has participatory planning task::Evaluating options]][[Has temporal scale::Long term (strategic)]][[Has spatial scale::Forest level]]

Results: EFIMOD, EMDS, Heureka, PEB, PLANFLOR, WIS.2, YAFO


List of questions elaborated during the workshop

Overview on the dedicated category page Category:Umea 2013 Question

Query: [[Category:Umea 2013 Question]]

Results: DSS for ecosystem services, Question: DSS Commercial Product, Question: DSS with forest indicators, Question: For which kind of use cases DSS are used for, Question: Question: Which DSSs use Stochastic programming, Question: Which DSS has strategic temporal scale, Question: Which DSSs have spatial context, Question: Which DSSs have technical documentation, Question: Which DSSs support multiple objectives, Question: Which DSSs support the process of evaluating options, Question: Which DSSs were developed by Sweden, Question: Which DSSs were developed by large team of people, Question: Which DSSs were developed in Italy, Question: Which LessonsLearned has spatial scale of stand level, Question: Which cases are currently active, Which kinds of DSS focus on landscape quality, Which lessons are about knowledge management