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• Nederlab, online laboratory for humanities research on Dutch text collections

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  The Nederlab project aims to bring together all digitized texts relevant to Dutch national heritage, the history of Dutch language and culture (c. 800 - present) in one user-friendly and tool-enriched open access web interface, allowing scholars to simultaneously search and analyze data from texts spanning the full recorded history of the Netherlands, its language and culture. The project builds on various initiatives: for corpora Nederlab collaborates with the scientific libraries and institutions, for infrastructure with CLARIN (and CLARIAH), for tools with eHumanities programmes such as Catch, IMPACT and CLARIN (TICCL, frog). Nederlab will offer a large number of search options with which researchers can find the occurrence of a particular term in a particular corpus or subcorpus. It'll also offer visualization of search results through line graphs, bar graphs, circle graphs, or scatter graphs. Furthermore, this online lab will offer a large set of tools, like tokenization tools, tools for spelling normalization, PoS-tagging tools, lemmatization tools, a computational historical lexicon and indices. Also, the use of (semi-) automatic syntactic parsing, tools for text mining, data mining and sentiment mining, Named Entity Recognition tools, coreference resolution tools, plagiarism detection tools, paraphrase detection tools and cartographical tools is offered The first version of Nederlab was launched in early 2015, it’ll be expanded until the end of 2017. Nederlab is financed by NWO, KNAW, CLARIAH and CLARIN-NL.

  http://www.nederlab.nl/wp/?page_id=12

• CLARIN Vocabulary Service

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  The CLARIN Vocabulary Service is a running instance of the OpenSKOS exchange and publication platform for SKOS vocabularies. OpenSKOS offers several ways to publish SKOS vocabularies (upload SKOS file, harvest from another OpenSKOS instance with OAI-PMH, construct using the RESTful API) and to use vocabularies (search and autocomplete using the API, harvest using OAI-PMH, inspect in the interactive Editor or consult as Linked Data). This CLARIN OpenSKOS instance is hosted by the Meertens Institute. Contents This OpenSKOS instance currently publishes SKOS versions of three vocabularies: - ISO-639-3 language codes, as published by SIL. - Closed and simple Data Categories from the ISOcat metadata profile. - A manually constructed and curated list of Organizations, based on the CLARIN VLO. .

  Brugman, H. 2017. CLAVAS: A CLARIN Vocabulary and Alignment Service. In: Odijk J. & van Hessen A, CLARIN in the Low Countries, ch 5, pp 61-69. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.5

• CMDI to RDF conversion

  There is growing amount of on-line information available in RDF format as Linked Open Data (LOD) and a strong community very actively promotes its use. The publication of information as LOD is also considered an important signal that the publisher is actively searching for information sharing with a world full of new potential users. Added advantages of LOD, when well used, are the explicit semantics and high interoperability. But the problematic modelling by non-expert users offsets these advantages, which is a reason why modelling systems as CMDI are used. The CMDI2RDF project aims to bring the LOD advantages to the CMDI world and make the huge store of CMDI information available to new groups of users and at the same time offer CLARIN a powerful tool to experiment with new metadata discovery possibilities. The CMD2RDFservice was created to allow connection with the growing LOD world, and facilitate experiments within CLARIN merging CMDI with other, RDF based, information sources. One of the promises of LOD is the ease to link data sets together and answer queries based on this ‘cloud’ of LOD datasets. Thus in the enrichment and use cases part of the project we looked at other datasets to link to the CLARIN joint metadata domain. We used the WALS N3 RDF dump for one of the use cases. Although it is in the end relatively easy to go from a specific typological feature to the CMD records via a shared URI, it still showcased a weakness of the Linked Data approach. One has to carefully inspect the property paths involved. And in this case the path was broken as there was no clear way to go from the WALS feature data to the WALS language info except for extracting the WALS language code from the feature URI pattern and insert it the language URI pattern. This showcases that although the big LOD cloud shows potential for knowledge discovery by crossing dataset boundaries, design decisions in the individual datasets can still hamper algorithms and manual inspection is needed. The CMD2RDF service was developed at the TLA/MPI for Psycholinguistics and DANS and later moved to Meertens Institute where the expertise remains.

  Use "CMDI to RDF conversion"

• MIMORE: Microcomparative Morphosyntax Research Tool

  With the MIMORE search engine one can search three databases together, with text strings, part of speech tags and syntactic variables. The researcher can combine categories and features into complex tags or use predefined tags. All categories and features are defined in ISOcat. Since all sentences have a location code, the morphosyntactic phenomena found in a set of sentences resulting from a search can be automatically plotted on a geographic map. It is possible to include more than one morphosyntactic phenomenon in one map, thus visualizing potential correlations between these phenomena. There is also a user-friendly function to export the data to a statistical program. The data in DynaSAND, the dynamic syntactic atlas of the Dutch dialects (http://www.meertens.knaw.nl/sand/ (link is external)), were collected between 2000 and 2005 by oral interviews (fieldwork and telephone) in about 300 locations across The Netherlands, Belgium and a small part of north-west France. Dialect speakers were asked to judge and/or translate some 150 test sentences. DynaSAND makes available the full recordings and transcriptions of these interviews. Together, the DynSAND data cover the syntactic variation in the Dutch language area in the left periphery of the clause (the complementizer system and complementizer agreement), variation in subject pronoun form depending on syntactic position, subject pronoun doubling, cliticization on YES/NO, the reflexive system, fronting constructions (Wh-clauses, relative clauses, topicalization), word order and morphological variation in verb clusters, negation and quantification. The data in DiDDD (Diversity in Dutch DP Design; http://www.meertens.knaw.nl/diddd/ (link is external)) were collected between 2005 and 2009 with oral and written interviews in about 200 locations in the Dutch language area, with a methodology highly parallel to DynaSAND. The data involve translations of and judgements on test sentences. For 29 interviews there are sound recordings which have been lined up with their transcriptions. The DIDDD data cover the morphosyntactic variation within nominal groups, in particular possessives, partitives, noun ellipsis, the demonstrative system, the numeral modification system, what-for constructions, quantitative er, adjectival inflection, negation and exclamatives. The data in GTRP (Goeman, Taeldeman, van Reenen Project; http://www.meertens.knaw.nl/mand/database/ (link is external)) were collected between 1979 and 2000 with oral interviews in about 600 locations in the Dutch language area. Informants were asked to translate words or short sentences. Part of the transcriptions have been lined up with the sound recordings. The morphological data in GTRP include plural forms of nouns, diminutives, gender on nouns and adjectives, comparatives, superlatives, verbal inflection including participles, subject, object and possessive pronouns.

  S. Barbiers, M. van Koppen, H. Bennis, N. Corver, MIcrocomparative MOrphosyntactic REsearch (MIMORE): Mapping partial grammars of Flemish, Brabantish and Dutch. Lingua Vol. 178, 5-31. doi:10.1016/j.lingua.2015.10.018