=Paper=
{{Paper
|id=None
|storemode=property
|title=Collaborative Editing and Linking of Astronomy Vocabularies Using Semantic Mediawiki
|pdfUrl=https://ceur-ws.org/Vol-632/paper06.pdf
|volume=Vol-632
|dblpUrl=https://dblp.org/rec/conf/semwiki/ChalmersGOG10
}}
==Collaborative Editing and Linking of Astronomy Vocabularies Using Semantic Mediawiki ==
https://ceur-ws.org/Vol-632/paper06.pdf
Collaborative Editing and Linking of Astronomy
Vocabularies Using Semantic Mediawiki
Stuart Chalmers1 , Norman Gray2 , Iadh Ounis1 , and Alasdair Gray3
1
Computing Science, University of Glasgow, Glasgow, UK
2
Physics and Astronomy, University of Glasgow, Glasgow, UK
3
School of Computer Science, Manchester University, Manchester, UK
Abstract. The International Virtual Observatory Alliance (IVOA) com-
prises 17 Virtual Observatory (VO) projects and facilitates the creation,
coordination and collaboration of standards promoting the use and re-
use of astronomical data archives. The Semantics working group in the
IVOA has repurposed five existing vocabularies (modelled using SKOS),
capturing concepts within specific areas of astronomy expertise and ap-
plications. A major task however, is to promote the uptake of these se-
mantic representations within the Astronomy community, and further, to
let astronomers model (and in turn create links from) their own custom
vocabularies to use these existing definitions. In this paper we show how
Semantic Mediawiki (SMW) can be used to support expert interaction
in the lifecycle of vocabulary creation, linking, and maintenance.
1 Introduction
Astronomy as a discipline incorporates a broad range of topics and data analysis
across the wavelength spectrum, from gamma-rays to radio waves, and a wide
range of expertise from professional researchers to amateurs. Because of the
collaborative nature of astronomy working groups and projects, and a culture
where sharing data is the norm, there is a well-established need for consensus
definitions describing data (mostly image and object catalogue data). To this
end a number of standardised vocabularies have emerged, which are mostly, at
present, focused on the search for and retrieval of resources, primarily data and
journal articles.
Thus, multiple independent controlled vocabularies have evolved to meet the
various terminological needs of these different sub-communities (Table 1). The
most widely-known of these is the keyword list maintained jointly by the three
main astronomy journals A&A, ApJ and MNRAS (these keywords are used to
tag journal articles, so that most astronomers have a familiarity with this set),
and the largest is a thesaurus developed by the International Astronomical Union
(IAU) (with the IVOA starting work on an update, the IVOAT). Newer than
both are the AVM vocabulary – a recent effort intended for use when tagging
astronomy outreach images – and the UCD list, in increasingly wide use as a set
of standardised database column headings4 . For further discussion see [1].
4
http://www.ivoa.net/Documents/latest/Vocabularies.html
Vocabulary Original Purpose Number of
Publisher Concepts
Journal Keywords Journal Tagging articles to aid retrieval 311
publishers
Astronomy Visualization various Tagging images for dissemination 208
Metadata (avm)
The IAU Thesaurus (iaut) iau Library cataloguing 2551
The ivoa Thesaurus (ivoat) ivoa Update of the IAU Thesaurus 2890
Universal Content Descriptors ivoa Labelling data repository 473
(ucd) column headings
Table 1. Astronomy vocabularies
While the IVOA vocabularies have provided a basis for standardisation of
experimental terminology, there remain a few problems:
– There are no standardised tools or methodology for creating custom exper-
imental descriptions based on these vocabularies.
– Users may be familiar with specific IVOA vocabularies relating to their sub-
discipline, but not others, meaning that their description cannot describe
their data as fully as a searching colleague might require.
– Searching of user-defined vocabularies and data is limited to terminology in
the IVOA vocabular(ies) used to define them. For instance, a user vocabu-
lary described using the IVOAT thesaurus has no relation to searches using
keywords from the IAUT thesaurus.
Recent work in the Explicator project5 has laid the foundations for a solution
to these problems, by representing the main IVOA vocabularies in SKOS, and ex-
ploiting SKOS relationships to help domain experts articulate cross-vocabulary
links [2].
2 Current Vocabulary Building Tools
The Explicator project has developed a number of tools for the creation and
use of SKOS astronomy vocabularies. The main entry point for searching and
exploring terminology is the Web Vocabulary Explorer6 , built upon the Terrier
Information Retrieval Platform [3] and providing an AJAX frontend for search-
ing and browsing the astronomy vocabularies by entering a simple search string
to find matching concepts. Fig. 1 (left) shows the search results for “star”. The
use of Terrier is important, in order to provide useful ranking of results: this
vocabulary contains a large number of labels with common strings, so a naive
search for “star” produces more than 600 concepts which have that string some-
where in their label, with the key concept ‘Star’ appearing uselessly far down
the list. Using Terrier’s ranking support, however, the appropriate concepts from
5
http://explicator.dcs.gla.ac.uk
6
http://explicator.dcs.gla.ac.uk/WebVocabularyExplorer
the three searched vocabularies appear at the beginning of this list. The explorer
allows users to expand results and view details of concepts, such as alternate la-
bels, available definitions and semantic relationships. Related concepts, both
within a vocabulary and across vocabularies, can be explored by following links
to broader, narrower, related, and equivalent concepts. Searches can be config-
ured by selecting sets of vocabularies and mappings. This service is also available
via XML-RPC, so that it can be embedded within other applications.
Fig. 1. The Web Vocabulary Explorer interface (left), and the inline search query and
its use in the AOIM Galaxy definition (right)
To create links between the main vocabularies in Table 1 we have a Java
mapping application providing a GUI interface to declare mappings between
vocabularies that can then be integrated into the Web Vocabulary Explorer.
The five vocabularies listed here were pre-existing ones, though not published as
SKOS, and so were converted from their original formats as part of the process of
developing [4]. The tool also allows the inclusion of automatically created RDF
representations of databases, created using the D2RQ database to RDF mapping
tool7 . The other important source of ontology information within the VO is the
IVOA’s resource registry8 , which curates resource metadata using a standardised
set of XML Schemas, which we have also converted to RDF Schemas using XSLT
transformations.
Part of the point of the tool’s search functionality is to help users find relevant
concepts in multiple vocabularies, and to support them in articulating inter-
vocabulary mappings. However we do not aim to do any automatic vocabulary
alignment.
3 Semantic Mediawiki in the Vocabulary Lifecycle
While the astronomy community is in general technically adept, the immediate
payoff from adopting the tools described in section 2 and converting to SKOS
7
http://www4.wiwiss.fu-berlin.de/bizer/d2rq/
8
http://rofr.ivoa.net
representations is not obvious (or apparent) enough to users to make this an at-
tractive option (this is a general problem, also discussed in [5]). What is needed
is a cohesive, familiar and easily understandable interface that integrates these
tools in a way that allows the creation of SKOS-based experiment descriptions
and vocabularies (based on and utilising current IVOA standard vocabularies)
with minimal expenditure on learning the underlying semantic representations.
To this end we have proposed a coherent vocabulary ‘lifecycle’ methodology
(creation, collaborative editing, linking and searching/use) – see Fig 2. This
uses SMW as a collaborative vocabulary building tool to create and edit vo-
cabularies (1), link (1) these to existing IVOA vocabularies (2) and have them
automatically exported to (3) and imported from (5) their corresponding SKOS
representations (4) for use in the Web Vocabulary Explorer.
& creation
curation
Semantic Astronomers
MediaWiki
(1)
Python lookup
D2R/XSLT parsing (5) maintenance (3) Jena parser
(JSON?)
tools
(7)
(2)
(4)
(6)
SKOS vocabs
UML RDBMS Vocabulary Lookup
& mappings
models schemas Explorer service
[master copy]
Vocabulary Tool Technical
Fig. 2. Information flows in Semantic MediaWiki (see text for numbered notes)
To link SMW to our existing tools (6), we have developed a general set of
python scripts (7), using pywikipediabot9 and the rdflib10 library to automate
the uploading and parsing of our SKOS vocabularies into Wikipedia pages11 . The
SMW pages are based on a simple semantic form/template structure, parsed
from the main SKOS vocabularies (4) and uploaded using the python bots.
Similarly we use a Jena-based parser to parse the SMW OWL/RDF export (3)
for a particular vocabulary and create the corresponding SKOS version for re-
inclusion in the Web Vocabulary Explorer search.
This linking of the five main IVOA vocabularies into SMW pages means that
we now have a base set of terms for users to begin using in their own experi-
mental vocabularies. To help users find related terminology (e.g. for broader,
narrower, or related matches in their SKOS terms) we use simple inline queries
embedded in the main vocabulary term template to show (on each term’s page)
the possible related terminology. Fig. 1 (right) shows the inline query used in
the main template of the vocabulary wiki pages and an example, the AOIM
term ‘Galaxy’. This shows the main definition (scopenote, prefLabel, altlabel,
broader, narrower and related) and a table of the possible related terms (includ-
ing TheGalaxy in the AAKeys vocabulary and the src.class.starGalaxy from the
9
http://meta.wikimedia.org/wiki/Pywikipedia
10
http://www.rdflib.net/
11
We currently host this testbed at http://vocabularies.referata.com
UCD vocabulary) that may be linked to by the user as cross-vocabulary related
terms.
4 Related and future work
There are other vocabulary development systems in existence, including the
NeOn project’s ontology editor12 , and its Cicero project, which is also based
on SMW, and which supports an elaborate argumentation structure for collab-
orative ontology development (NeOn deliverable 2.3.1). On a similar theme is
LexWiki13 , which is a platform for developing a biomedical vocabulary. The
problem we are addressing, however, is not that of collaboratively creating a
large ontology from scratch, but supporting the collaborative inter-relation of
multiple existing vocabularies from various sources, with a community which
is made more rather than less comfortable by having some of the underlying
technology visible, and repurposable from user-written applications.
At present we are working on a mediawiki extension that will allow us to use
the XML-RPC search from the Web Vocabulary Explorer to find related terms.
This will use the Terrier search described above, to provide more accurate ranked
searches for related terms, than is possible with the existing inline searches.
A key advantage, for us, of using a wiki-based solution is that it provides a
good match to the expectations of the domain experts – they feel comfortable
and in control when using it. Both the wiki and its embedded functionality must
therefore evolve in tune with the user base, and an important strand of our
future work on this project is to evaluate the provided functionality in use.
References
1. Gray, A., Gray, N., Ounis, I.: Vocabularies in the VO. In Bohlender, D., et al.,
eds.: Proc. Astronomical Data Analysis and Software Systems Conference (ADASS
XVIII). Volume 411., Astronomical Society of the Pacific (2009) 179–182
2. Gray, A.J.G., Gray, N., Hall, C.W., Ounis, I.: Finding the right term: Retrieving and
exploring semantic concepts in astronomical vocabularies. Information Processing
and Management (2009). In press.
3. Ounis, I., Amati, G., Plachouras, V., He, B., Macdonald, C., Lioma, C.: Terrier:
A high performance and scalable information retrieval platform. In: Proceedings
of ACM SIGIR’06 Workshop on Open Source Information Retrieval (OSIR 2006),
Seattle (Washington, USA), ACM (2006)
4. Gray, A.J.G., Gray, N., Hessman, F.V., Preite Martinez, A.: Vocabularies in the
virtual observatory. IVOA Recommendation (2009) Available at: http://www.ivoa.
net/Documents/latest/Vocabularies.html.
5. Gray, N., Linde, T., Andrews, K.: SKUA - retrofitting semantics. In Auer, S., et al.,
eds.: Proc. 5th Workshop on Scripting and Development for the Semantic Web at
ESWC 2009, Heraklion, Greece. Volume 449 of CEUR Workshop Proceedings ISSN
1613-0073. (2009)
12
http://www.neon-project.org/
13
http://informatics.mayo.edu/vkcdemo/lexwiki1/