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From Open Source to Open Information. Collaborative Methods in Creating XML-based Markup Languages
(2000)
Linguistic corpora have been annotated by means of SGML-based markup languages for almost 20 years. We can, very roughly, differentiate between three distinct evolutionary stages of markup technologies. (1)Originally, single SGML tree-based document instances were deemed sufficient for the representation of linguistic structures. (2) Linguists began to realize that alternatives and extensions to the traditional model are needed. Formalisms such as, for example, NITE were proposed: the NITE Object Model (NOM) consists of multi-rooted trees. (3) We are now on the threshold of the third evolutionary stage: even NITE's very flexible approach is not suited for all linguistic purposes. As some structures, such as these, cannot be modeled by multi-rooted trees, an even more flexible approach is needed in order to provide a generic annotation format that is able to represent genuinely arbitrary linguistic data structures.
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.
On the Lossless Transformation of Single-File, Multi-Layer Annotations into Multi-Rooted Trees
(2007)
The Generalised Architecture for Sustainability (GENAU) provides a framework for the transformation of single-file, multi-layer annotations into multi-rooted trees. By employing constraints expressed in XCONCUR-CL, this procedure can be performed lossless, i.e., without losing information, especially with regard to the nesting of elements that belong to multiple annotation layers. This article describes how different types of linguistic corpora can be transformed using specialised tools, and how constraint rules can be applied to the resulting multi-rooted trees to add an additional level of validation.
Digital Text Collections, Linguistic Research Data, and Mashups: Notes on the Legal Situation
(2008)
Comprehensive data repositories are an essential part of practically all research carried out in the digital humanities nowadays. For example, library science, literary studies, and computational and corpus linguistics strongly depend on online archives that are highly sustainable and that contain not only digitized texts but also audio and video data as well as additional information such as metadata and arbitrary annotations. Current Web technologies, especially those that are related to what is commonly referred to as the Web 2.0, provide a number of novel functions such as multiuser editing or the inclusion of third-party content and applications that are also highly attractive for research applications in the areas mentioned above. Hand in hand with this development goes a high degree of legal uncertainty. The special nature of the data entails that, in quite a few cases, there are multiple holders of personal rights (mostly copyright) to different layers of data that often have different origins. This article discusses the legal problems of multiple authorships in private, commercial, and research environments. We also introduce significant differences between European and U.S. law with regard to the handling of this kind of data for scientific purposes.