The WeScience initiative is an on-going effort to provide resources that enable eScience research and development in our own field, i.e. Computational Linguistics (or Natural Language Processing). Some of the motivating ideas and goals are sketched by Ytrestøl, Flickinger, & Oepen (2009). WeScience aims to (help) improve the accessibility of scholarly literature and digital libraries, with a special emphasis on community or open access resources. Current development is focused on semantic parsing of encyclopedic articles (from the on-line community resource Wikipedia), with the long-term goal of relating natural language semantics and taxonomic knowledge, for example in relation extraction or ontology learning applications. As a complementary element, we plan to include a selection of scientific articles (from the ACL Anthology, for example), with candidate applications ranging over, among others, function and attitude analysis for citations, attribution tracking, indexing by complex content properties (for example specific sub-fields, hypotheses, methods used), association to encyclopedia entries (or ontology nodes), or so-called 'semantic search'.

WeScience, in its early stages of 2008, 2009, and 2010, was a semi-formal collaboration between the University of Oslo, the Center for the Study of Language and Information, the German Research Center for AI, and Saarland University, with partial funding from the University of Oslo, the Norwegian Open Research Archives, and the Norwegian Metacenter for Computational Science. Since 2011, WeScience is partially supported by the WeSearch project.

Current State of Development

WeScience comprises two components, the WeScience Corpus (discussed in more detail by Ytrestøl, et al. (2009)) and the WeScience Treebank. The corpus comprises a selection of Wikipedia articles in the domain of Natural Language Processing, pre-processed to strip irrelevant markup and segmented into sentence-like units. WeScience defines a simple, line-oriented textual exchange format for the corpus, aiming to strike a good balance between computer and human readability (there are formal considerations too that make the use of XML infeasible). Each sentence-like unit has a unique 8-digit identifier, with the first four digits referencing the underlying article. The corpus is broken into 16 sections, each of a maximum of 1000 segments, where no article is split across sections. Sections 14 through 16 are reserved for evaluation purposes.

The corpus is extracted from a Wikipedia snapshot of July 2008, and more details of the corpus construction (selection, pre-processing, organization, et al.) are available as a technical report (Ytrestøl, 2009).

Development of the WeScience Treebank builds on the LinGO English Resource Grammar (ERG) and Redwoods discriminant-based treebanking approach. Starting with its April 2010 version, releases of the ERG include the majority of the WeScience Corpus in treebanked form (see below).

Obtaining the Corpus and Treebank

As of early 2009, the WeScience Corpus has been released in three versions. Revisions 0.1 and 0.2 were purely internal releases and are now superseded by the present release, revision 0.3. This is publicly and freely available in a variety of formats. The recommend method of obtaining the WeScience Corpus is by virtue of the SubVersion (SVN) revision management system. A command like:

  svn co wescience

will retrieve the latest development version (i.e. revision 0.3, as of early 2009) and create a new subdirectory wescience/. This directory will contain both the raw, un-processed Wikipedia articles (in the raw/ sub-directory) and the actual WeScience Corpus, in the format described above (in the txt/ sub-directory). For those without a functional SVN client (M$ Windoze users, maybe), this data is also available as a compressed Un*x tar(1) archive.

Regarding availability of the first release of the WeScience Treebank, please watch this space (or the DELPH-IN mailing lists). At present, treebanks for the first thirteen WeScience sections are provided in [incr tsdb()] format as part of the ERG release.

Exporting Various Plain-Text Formats

To experiment with these treebanks, however, for the time being, large parts of the DELPH-IN toolchain are required. We recommend working with the trunk (aka head revision) of the integrated LOGON distribution. For a quick-start guide to installing this software, please see the ErgProcessing page (specifically the Output Formats section; however, we strongly advise perusing the full LOGON documentation, linked from the LogonTop page, for more technical background).

Assuming a functional, up-to-date LOGON installation, one can export the [incr tsdb()] treebanks into various textual formats, for example using a command like the following:

  ./redwoods --binary --erg --target /tmp/wescience \
    --export derivation,tree,mrs,eds ws01

If there were broad interest, we may also provide a textual export version of WeScience for direct download in the future (as is available for the WikiWoods Treecache, where running the export step requires non-trivial computational resources).

Further Notes for DELPH-IN Users

The WeScience Corpus is available as so-called [incr tsdb()] skeletons too, i.e. the result of importing the text files (the pre-processed ones, obviously) into the [incr tsdb()] database. These skeletons have been part of the [incr tsdb()] distribution through the LOGON tree (see the LogonTop page) since late 2008. The WeScience skeletons are called ws01 through ws16, and these same names are used in organizing the WeScience Treebank.

Outlook: Next Steps


WeScience (last edited 2012-08-05 20:53:14 by StephanOepen)

(The DELPH-IN infrastructure is hosted at the University of Oslo)