LREC as a Graph: People and Resources in a Network

15732

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nan

Abstract

AbstractThis proposal describes a new way to visualise resources in the LREMap, a community-built repository of language resource descriptions and uses. The LREMap is represented as a force-directed graph, where resources, papers and authors are nodes. The analysis of the visual representation of the underlying graph is used to study how the community gathers around LRs and how LRs are used in research.

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LREC as a Graph: People and Resources in a Network Riccardo Del Gratta, Francesca Frontini, Monica Monachini, Gabriella Pardelli, Irene Russo Roberto Bartolini, Fahad Khan, Claudia Soria, Nicoletta Calzolari Istituto di Linguistica Computazionale “A . Zampolli” CNR Pisa, Italy name.surname@ilc.cnr.it Abstract This proposal describes a new way to visualise resources in the LREMap, a community-built repository of language resource descriptions and uses. The LREMap is represented as a force-directed graph, where resources, papers and authors are nodes. The analysis of the visual representation of the underlying graph is used to study how the community gathers around LRs and how LRs are used in research. Keywords: language resources, resources documentation, data visualisation 1. Introduction The availability of Language Resources (LRs) - such as cor- pora, computational lexicons and parsers - is crucial to most NLP technologies. Recent initiatives have monitored the availability of Language Resources for different languages, and highlighted a digital divide between English and other languages (Soria et al., 2012), (Rehm and Uszkoreit, 2012). While the economic potential of English ensures that En- glish LRs are developed and maintained not only in the aca- demic sector but also by commercial players, the involve- ment of research communities for other languages is much more crucial to ensure that the necessary instruments (both data and tools) are made available for natural language pro- cessing purposes. At the same time, production of quality LRs is only the first step; in order to be usable, LRs must also be documented and made available to the community in such a way that they are easy to find and to use. This en- tails the description of every Language Resource with a set of metadata that clarify its typology, its language, its size and licensing scheme, and the means of accessing it. Useful information in this sense can be found in the cata- logues of language resources associations, such as ELRA, LDC, NICT Universal Catalogue, ACL Data and Code Repository, OLAC, and LT World. These catalogues adopt a top-down approach to documenting resources and typi- cally list resources that have reached a high level of ma- turity - in terms of validation, documentation and clearing of Intellectual Property Rights (IPR) issues. As an alter- native to this approach, recent projects have been carried out within the LR community to create open, bottom-up repositories where LRs - even those under development - can be duly documented and searched. Such initiatives are for instance the META-SHARE platform (Gavrilidou et al., 2012), the CLARIN VLO (Broeder et al., 2010) and the LRE Map (Calzolari et al., 2012; Del Gratta et al., 2014b; Del Gratta et al., 2014a), with their sets of metadata. In particular, the LREMap was launched as an initiative at LREC 2010 in order to crowdsource reliable and accurate documentation for the largest possible set of resources. Au- thors submitting to that conference were asked to document the resources they used in their paper, both the resources they created and the ones created by others. This …

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Labeled Text

AbstractThis proposal describes a new way to visualise resources in the LREMap, a community-built repository of language resource descriptions and uses. The LREMap is represented as a force-directed graph, where resources, papers and authors are nodes. The analysis of the visual representation of the underlying graph is used to study how the community gathers around LRs and how LRs are used in research.

Publication Details

Paper ID:
15732
Year:
2016
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan