CLARIN is a European Research Infrastructure providing access to digital language resources and tools from across Europe and beyond to researchers in the humanities and social sciences. This paper focuses on CLARIN as a platform for the sharing of language resources. It zooms in on the service offer for the aggregation of language repositories and the value proposition for a number of communities that benefit from the enhanced visibility of their data and services as a result of integration in CLARIN. The enhanced findability of language resources is serving the social sciences and humanities (SSH) community at large and supports research communities that aim to collaborate based on virtual collections for a specific domain. The paper also addresses the wider landscape of service platforms based on language technologies which has the potential of becoming a powerful set of interoperable facilities to a variety of communities of use.

CLARIN is a European Research Infrastructure providing access to language resources and technologies for researchers in the humanities and social sciences. It supports the use and study of language data in general and aims to increase the potential for comparative research of cultural and societal phenomena across the boundaries of languages and disciplines, all in line with the European agenda for Open Science. Data infrastructures such as CLARIN have recently embarked on the emerging frameworks for the federation of infrastructural services, such as the European Open Science Cloud and the integration of services resulting from multidisciplinary collaboration in federated services for the wider SSH domain. In this paper we describe the interoperability requirements that arise through the existing ambitions and the emerging frameworks. The interoperability theme will be addressed at several levels, including organisation and ecosystem, design of workflow services, data curation, performance measurement and collaboration.

This paper describes our submission to Task 5 of SemEval 2017, Fine-Grained Sentiment Analysis on Financial Microblogs and News, where we limit ourselves to performing sentiment analysis on news headlines only (track 2). The approach presented in this paper uses a Support Vector Machine to do the required regression, and besides unigrams and a sentiment tool, we use various ontology-based features. To this end we created a domain ontology that models various concepts from the financial domain. This allows us to model the sentiment of actions depending on which entity they are affecting (e.g., ‘decreasing debt’ is positive, but ‘decreasing profit’ is negative). The presented approach yielded a cosine distance of 0.6810 on the official test data, resulting in the 12th position.

In this contribution we describe a collection of approximately 400 video interviews recorded in the context of the project Croatian Memories (CroMe) with the objective of documenting personal war-related experiences. The value of this type of sources is threefold: they contain information that is missing in written sources, they can contribute to the process of reconciliation, and they provide a basis for reuse of data in disciplines with an interest in narrative data. The CroMe collection is not primarily designed as a linguistic corpus, but is the result of an archival effort to collect so-called oral history data. For researchers in the fields of natural language processing and speech analy¬sis this type of life-stories may function as an object trouvé containing real-life language data that can prove to be useful for the purpose of modelling specific aspects of human expression and communication.

In The Low Countries, a major reference corpus for written Dutch is being built. We discuss the interplay between data acquisition and data processing during the creation of the SoNaR Corpus. Based on developments in traditional corpus compiling and new web harvesting approaches, SoNaR is designed to contain 500 million words, balanced over 36 text types including both traditional and new media texts. Beside its balanced design, every text sample included in SoNaR will have its IPR issues settled to the largest extent possible. This data collection task presents many challenges because every decision taken on the level of text acquisition has ramifications for the level of processing and the general usability of the corpus. As far as the traditional text types are concerned, each text brings its own processing requirements and issues. For new media texts - SMS, chat - the problem is even more complex, issues such as anonimity, recognizability and citation right, all present problems that have to be tackled. The solutions actually lead to the creation of two corpora: a gigaword SoNaR, IPR-cleared for research purposes, and the smaller - of commissioned size - more privacy compliant SoNaR, IPR-cleared for commercial purposes as well.

The re-use of spoken word audio collections maintained by audiovisual archives is severely hindered by their generally limited access. The CHoral project, which is part of the CATCH program funded by the Dutch Research Council, aims to provide users of speech archives with online, instead of on-location, access to relevant fragments, instead of full documents. To meet this goal, a spoken document retrieval framework is being developed. In this paper the evaluation efforts undertaken so far to assess and improve various aspects of the framework are presented. These efforts include (i) evaluation of the automatically generated textual representations of the spoken word documents that enable word-based search, (ii) the development of measures to estimate the quality of the textual representations for use in information retrieval, and (iii) studies to establish the potential user groups of the to-be-developed technology, and the first versions of the user interface supporting online access to spoken word collections.