[Corpora-List] 3rd CFP: Challenges in the Management of Large Corpora 8 (CMLC-8)

Piotr Banski banski at ids-mannheim.de
Mon Feb 3 12:35:33 CET 2020


The 8th edition of "Challenges in the Management of Large Corpora" is going to be held on the 16th of May 2020 (morning session) in Marseille, during the LREC-2020 conference.

See http://corpora.ids-mannheim.de/cmlc-2020.html for updates.

This is the 3rd Call for Papers. Deadline for abstract submission: 16 February 2020, 23:59 CET. See below for more details.

Workshop description

Large textual datasets require careful design, collection, cleaning, encoding, annotation, storage, retrieval, and curation to be of use for a wide range of research questions and to users across a number of disciplines. A growing number of national and other very large corpora are being made available, many historical archives are being digitised, numerous publishing houses are opening their textual assets for text mining, and many billions of words can be quickly sourced from the web and online social media.

A number of key themes and questions emerge of interest to the contributing research communities: (a) what can be done to deal with IPR and data protection issues? (b) what sampling techniques can we apply? (c) what quality issues should we be aware of? (d) what infrastructures and frameworks are being developed for the efficient storage, annotation, analysis and retrieval of large datasets? (e) what affordances do visualisation techniques offer for the exploratory analysis approaches of corpora? (f) what kinds of APIs or other means of access would make the corpus data as widely usable as possible without interfering with legal restrictions? (g) how to guarantee that corpus data remain available and usable in a sustainable way?

The CMLC workshop series invites papers dealing with challenges that arise in particular in connection with very large corpora, on topics such as: sampling approaches; web harvesting approaches; quality assessment; efficient solutions for storage, processing, querying and analysis; dimension reduction and exploratory data visualization; interfaces/APIs and other approaches to make the corpus data as widely usable as possible; sustainability and interoperability in general; intellectual property rights and licensing. This year’s event will cover the whole range of the standard CMLC themes, with some new additions and adopting some of LREC 2020’s focus topics.

Topics

This year’s event will cover the whole range of the standard CMLC themes, with some new additions and adopting some of LREC 2020’s focus topics:

* Interoperability and accessibility

o How to make corpora as accessible as possible

o Interoperable APIs for query and analysis software

o Provision of multiple levels of access for different tasks

* Machine/Deep Learning

o Data preparation for machine learning input

o Creation, curation, maintenance and dissemination of language

models based on machine learning (including, for example, word

embeddings and entre shallow and deep learning networks)

o Legal issues concerning language model distribution

* Linguistic content challenges

o Dealing with the variety of language: multilinguality,

historical texts, noisy OCR texts, user-generated content, etc.

o Integration of human computation (crowdsourcing) and automatic

annotation

o Quality management of annotations

o Dealing with different linguistic data types (corpora,

facsimiles, experimental data, neuroimaging data, …)

* Technical challenges

o Storage and retrieval solutions for big textual data corpora:

primary data (potentially including facsimiles, etc.), metadata,

and annotation data

o Scalable and efficient NLP tooling for annotating and analysing

large datasets: distributed and GPGPU computing; using big data

analysis frameworks for language processing

o Dealing with streaming data (e.g. Social Media) and rapidly

changing corpora

o Environmental impact of big language data computing

* Exploitation challenges

o Legal and privacy issues

o Query languages, data models, and standardization

o Licensing models of open and closed data, coping with

intellectual property restrictions

o Innovative approaches for aggregation and visualisation of text

analytics

In the tradition of CMLC, we invite reports on national corpus initiatives; submitters of these reports should be prepared to present a poster.

Important dates

* Deadline for abstract submission: 16 February 2020, 23:59 CET, via

the START manager exclusively

(https://www.softconf.com/lrec2020/CMLC-8/)

* Notification of acceptance: 12 March 2020

* Deadline for the submission of camera-ready papers: 26 March 2020

* Meeting: 16 May 2020, morning session

Submission categories

We invite anonymised extended abstracts for oral presentations on the topics listed above (PDF, 1000-1500 words excluding references, font preferably 11 pt, line spacing 1.5).

CMLC has always reserved a track for national corpus project reports, and to this end, we invite poster proposals of 500-750 words. National project reports need not be anonymised. The number of poster slots is limited. If there is spare capacity in the poster session, we reserve the right to change the presentation format of accepted papers from oral presentation to poster. Such a change will not affect how the paper is presented in the proceedings.

Submissions will be accepted exclusively through the START system (https://www.softconf.com/lrec2020/CMLC-8/).

Identify, Describe and Share your LRs!

Describing your LRs in the LRE Map is now a normal practice in the submission procedure of LREC (introduced in 2010 and adopted by other conferences). To continue the efforts initiated at LREC 2014 about “Sharing LRs” (data, tools, web-services, etc.), authors will have the possibility, when submitting a paper, to upload LRs in a special LREC repository. This effort of sharing LRs, linked to the LRE Map for their description, may become a new “regular” feature for conferences in our field, thus contributing to creating a common repository where everyone can deposit and share data.

As scientific work requires accurate citations of referenced work so as to allow the community to understand the whole context and also replicate the experiments conducted by other researchers, LREC 2018 endorses the need to uniquely Identify LRs through the use of the International Standard Language Resource Number (ISLRN,www.islrn.org <http://www.islrn.org/>), a Persistent Unique Identifier to be assigned to each Language Resource. The assignment of ISLRNs to LRs cited in LREC papers will be offered at submission time.

Proceedings

Online proceedings will be published by ELRA.

Programme Committee

# Laurence Anthony (Waseda University, Japan) # Vladimír Benko (Slovak Academy of Sciences) # Felix Bildhauer (IDS Mannheim) # Sonja Bosch (University of South Africa) # Dan Cristea ("Alexandru Ioan Cuza" University of Iasi) # Damir Ćavar (Indiana University) # Tomaž Erjavec (Jožef Stefan Institute) # Johannes Graën (University of Gothenburg, Pompeu Fabra University) # Andrew Hardie (Lancaster University) # Serge Heiden (ENS de Lyon) # Miloš Jakubíček (Lexical Computing Ltd.) # Dawn Knight (Cardiff University) # Natalia Kotsyba (Samsung Poland) # Michal Křen (Charles University, Prague) # Sandra Kübler (Indiana University, Bloomington) # Gaël Lejeune (Sorbonne Université) # Paul Rayson (Lancaster University) # Martin Reynaert (Tilburg University) # Laurent Romary (INRIA) # Kevin Scannell (Saint-Louis University) # Roland Schäfer (FU Berlin) # Serge Sharoff (University of Leeds) # Irena Spasic (Cardiff University) # Marko Tadić (University of Zagreb, Faculty of Humanities and Social Sciences) # Ludovic Tanguy (University of Toulouse) # Dan Tufiş (Romanian Academy, Bucharest)

Organising Committee

    Institut für Deutsche Sprache, Mannheim

    Piotr Bański,Marc Kupietz,Harald Lüngen

    Berlin-Brandenburg Academy of Sciences

    Adrien Barbaresi

    Institute of Computational Linguistics, University of Zurich

    Simon Clematide

Homepage

CMLC series homepage is located athttp://corpora.ids-mannheim.de/cmlc.html

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