Controlled Vocabulary Working Group Virtual Water Cooler Session April 6-7, 2009 Moderator: John Porter rm.action?confKey=jhp7e.

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Presentation transcript:

Controlled Vocabulary Working Group Virtual Water Cooler Session April 6-7, 2009 Moderator: John Porter rm.action?confKey=jhp7e rm.action?confKey=jhp7e1

Goals for this VTC ► Brief review of activities ► Get feedback on “LTER Data Keywords” draft list ► Discuss process for managing keyword list ► Next steps? – Taxonomys, Tools etc. ► What should we do at the ASM meeting? 2

Carbon Dataset 1 Carbon Dataset 2 Carbon Dataset 3 Disjointed keywords make it hard to locate similar datasets 3

Carbon Dataset 1 Carbon Dataset 2 Carbon Dataset 3 Overlapping keywords make it easier to locate similar datasets Note that the purpose of keywords and a controlled vocabulary is not to provide the best possible description of a particular dataset, but to provide a mechanism for appropriate groupings of datasets 4

The Problem ► Inconsistent, disjunct and sparse keywords negatively impact data discovery 72.2% of all keywords are used at only a single LTER site 90% of all keywords are used at 4 or fewer LTER sites 5

Goals for the Controlled Vocabulary Group ► Aid the discovery of data by researchers  Consistent, broadly applied keywords  Develop “browseable” structures (taxonomys, thesauri, ontologies) ► Aid in the creation of high-quality metadata ► Make it easier for LTER data to interoperate with other data systems 6

Past Activities ► Research  A variety of studies regarding which words are used where ► Improvement of existing systems  Metacat drop down list now features the most common existing keywords ► Discussion of possible tools to:  Aid in Keywording  Aid in searching 7

Draft List ► Creation of a draft list of ~650 words for an LTER-wide controlled vocabulary  Words must be used at two or more sites, OR  Words must be used at one or more sites and also be found in either NBII, GCMD, the KNB/Metacat browse list or recent metacat searches  Excluded were species names and names of geographic locations which probably belong in separate lists 8

Draft List ► Words on the candidate list were edited to create “Preferred forms” that comply with NISO-Z NISO-Z  Nouns are plural if you would count them, singular if they are an amount  Removal of hyphenated words when possible  Creation of a “synonym ring” linking extant forms with preferred forms (~150 terms) 9

A Logical Next Step ► The draft list needs to be formalized in a database that includes (NISO Z39.19 sections & ):  term  source(s) consulted for terms and entry terms.  scope note  USED FOR references – to indicate which synonyms, near synonyms, and other expressions are covered by the term.  nondisplayable variations, e.g., common spelling errors  broader terms  narrower terms  related terms  locally established relationships  category or classification number  history note, including minimally the date added, as well as the record of changes, if any Some elements support development of hierarchical taxonomys and thesauri 10

Issues ► Who should make decisions regarding the content of the list (11.3 in NISO Z39.19)? ► How should site-specific terms be handled?  Include in list, but use Scope or Category elements to distinguish ► What steps are needed to create a hierarchical polytaxonomy or thesaurus? 11

Discussion Topics ► Get feedback on the draft list ► How (who) should manage the keyword list? ► Next steps? – Taxonomys, Tools etc. ► What should we do at the ASM meeting to move the process forward? 12

Day 1 – Discussion Points ► Generally pleased with the list. Issues:  Site-specific words  Human dimensions largely absent  Locations  Homographs ► Next Steps:  Give sites a chance to propose addition, deletion or substitution of terms in the list, and/or additions to the synonym ring  Vote on changes 13

Day 1 – Discussion Points ► What to do at ASM meeting?  Session presenting different approaches ► Lists through ontologies  Session: New Tools for Locating Data ► Spec out tools for keywording and searching  Session “How to find and use data” 14