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This paper presents the application of the <tiger2/> format to various linguistic scenarios with the aim of making it the standard serialisation for the ISO 24615 [1] (SynAF) standard. After outlining the main characteristics of both the SynAF metamodel and the <tiger2/> format, as extended from the initial Tiger XML format [2], we show through a range of different language families how <tiger2/> covers a variety of constituency and dependency based analyses.
XML has been designed for creating structured documents, but the information that is encoded in these structures are, by definition, out of scope for XML. Additional sources, normally not easily interpretable by computers, such as documentation are needed to determine the intention of specific tags in a tag-set. The Component Metadata Infrastructure (CMDI) takes a rather pragmatic approach to foster interoperability between XML instances in the domain of metadata descriptions for language resources. This paper gives an overview of this approach.
We present SPLICR, the Web-based Sustainability Platform for Linguistic Corpora and Resources. The system is aimed at people who work in Linguistics or Computational Linguistics: a comprehensive database of metadata records can be explored in order to find language resources that could be appropriate for one’s spe cific research needs. SPLICR also provides a graphical interface that enables users to query and to visualise corpora. The project in which the system is developed aims at sustainably archiving the ca. 60 language resources that have been constructed in three collaborative research centres. Our project has two primary goals: (a) To process and to archive sustainably the resources so that they are still available to the research community in five, ten, or even 20 years time. (b) To enable researchers to query the resources both on the level of their metadata as well as on the level of linguistic annotations. In more general terms, our goal is to enable solutions that leverage the interoperability, reusability, and sustainability of heterogeneous collec- tions of language resources.
We present an approach to an aspect of managing complex access scenarios to large and heterogeneous corpora that involves handling user queries that, intentionally or due to the complexity of the queried resource, target texts or annotations outside of the given user’s permissions. We first outline the overall architecture of the corpus analysis platform KorAP, devoting some attention to the way in which it handles multiple query languages, by implementing ISO CQLF (Corpus Query Lingua Franca), which in turn constitutes a component crucial for the functionality discussed here. Next, we look at query rewriting as it is used by KorAP and zoom in on one kind of this procedure, namely the rewriting of queries that is forced by data access restrictions.
This paper describes a new research initiative addressing the issue of sustainability of linguistic resources. The initiative is a cooperation between three collaborative research centres in Germany – the SFB 441 “Linguistic Data Structures” in Tübingen, the SFB 538 “Multilingualism” in Hamburg, and the SFB 632 “Information Structure” in Potsdam/Berlin. The aim of the project is to develop methods for sustainable archiving of the diverse bodies of linguistic data used at the three sites. In the first half of the paper, the data handling solutions developed so far at the three centres are briefly introduced. This is followed by an assessment of their commonalities and differences and of what these entail for the work of the new joint initiative. The second part then sketches seven areas of open questions with respect to sustainable data handling and gives a more detailed account of two of them – integration of linguistic terminologies and development of best practice guidelines.
Beyond Citations: Corpus-based Methods for Detecting the Impact of Research Outcomes on Society
(2020)
This paper proposes, implements and evaluates a novel, corpus-based approach for identifying categories indicative of the impact of research via a deductive (top-down, from theory to data) and an inductive (bottom-up, from data to theory) approach. The resulting categorization schemes differ in substance. Research outcomes are typically assessed by using bibliometric methods, such as citation counts and patterns, or alternative metrics, such as references to research in the media. Shortcomings with these methods are their inability to identify impact of research beyond academia (bibliometrics) and considering text-based impact indicators beyond those that capture attention (altmetrics). We address these limitations by leveraging a mixed-methods approach for eliciting impact categories from experts, project personnel (deductive) and texts (inductive). Using these categories, we label a corpus of project reports per category schema, and apply supervised machine learning to infer these categories from project reports. The classification results show that we can predict deductively and inductively derived impact categories with 76.39% and 78.81% accuracy (F1-score), respectively. Our approach can complement solutions from bibliometrics and scientometrics for assessing the impact of research and studying the scope and types of advancements transferred from academia to society.
The present submission reports on a pilot project conducted at the Institute for the German Language (IDS), aiming at strengthening the connection between ISO TC37SC4 “Language Resource Management” and the CLARIN infrastructure. In terminology management, attempts have recently been made to use graph-theoretical analyses to get a better understanding of the structure of terminology resources. The project described here aims at applying some of these methods to potentially incomplete concept fields produced over years by numerous researchers serving as experts and editors of ISO standards. The main results of the project are twofold. On the one hand, they comprise concept networks dynamically generated from a relational database and browsable by the user. On the other, the project has yielded significant qualitative feedback that will be offered to ISO. We provide the institutional context of this endeavour, its theoretical background, and an overview of data preparation and tools used. Finally, we discuss the results and illustrate some of them.