#  Executive Summary

This document describes the Data Management Plan (DMP) adopted within CRACKER
and provides information on CRACKER’s data management policy and key
information on all datasets that have been and will be produced within
CRACKER, as well as resources developed by the “Cracking the language barrier”
federation of projects (also known as the “ICT-17 group of projects”) and
other projects who wish to follow a common line of action, as provisioned in
the CRACKER Description of Action.

This second version includes the principles according to which the plan is
structured, the standard practices for data management that are being
implemented, and the description of the actual datasets produced within
CRACKER. The final update of the CRACKER DMP document will be provided in M36
(December 2017).

The document is structured as follows:

  * Background and rationale of a DMP within H2020 (section 2) 

  

  * Implementation of the CRACKER DMP (section 3) 

  

  * Collaboration of CRACKER with other projects and initiatives (section 4) 

  

  * Recommendations for a harmonized approach and structure for a Data Management Plan to be optionally adopted by the “Cracking the language barrier” federation of projects (section 5). 

  

#  Background

The use of a Data Management Plan (DMP) is required for projects participating
in the Open Research Data Pilot, which aims to improve and maximise access to
and re-use of research data generated by projects. The elaboration of DMPs in
Horizon 2020 projects is specified in a set of guidelines applied to any
project that collects or produces data. These guidelines explain how projects
participating in the Pilot should provide their DMP, i.e. to detail the types
of data that will be generated or gathered during the project, and after it is
completed, the metadata and standards which will be used, the ways how these
data will be exploited and shared for verification or reuse and how they will
be preserved.

In principle, projects participating in the Pilot are required to deposit the
research data described above, preferably into a research data repository.
Projects must then take measures, to the extent possible, to enable for third
parties to access, mine, exploit, reproduce and disseminate, free of charge,
this research data.

The guidance for DMPs calls for clarifications and analysis regarding the main
elements of the data management policy within a project. The respective
template identifies in brief the following five coarse categories  1  :

  1. **Data set reference and name** : an identifier for the data set; use of a standard identification mechanism to make the data and the associated software easily discoverable, readily located and identifiable. 

  

  2. **Data set description** : details describing the produced and/or collected data and associated software and accounting for their usability, documentation, reuse, assessment and integration (i.e., origin, nature, volume, usefulness, documentation/publications, similar data, etc.). 

  

  3. **Standards and metadata** : related standards employed or metadata prepared, including information about interoperability that allows for data exchange and compliance with related software or applications. 

  

  4. **Data sharing** : procedures and mechanisms enabling data access and sharing, including details about the type or repositories, modalities in which data are accessible, scope and licensing framework. 

  

  5. **Archiving and preservation (including storage and backup)** : procedures for long-term preservation of the data including details about storage, backup, potential associated costs, related metadata and documentation, etc. 

  

  

#  The CRACKER DMP

##  Introduction and Scope

For its own datasets, CRACKER follows META-SHARE’s ( _http://www.meta-_

_share.eu/_ ) best practices for data documentation, verification and
distribution, as well as for curation and preservation, ensuring the
availability of the data throughout and beyond the runtime of CRACKER and
enabling access, exploitation and dissemination, thereby also complying with
the standards of the Open Research Data Pilot  2  .

META-SHARE is a pan-European infrastructure bringing online together providers
and consumers of language data, tools and services It is organized as a
network of repositories that store language resources (data, tools and
processing services) documented with high-quality metadata, aggregated in
central inventories allowing for uniform search and access. It serves as a
component of a language resource marketplace for researchers, developers,
professionals and industrial players, catering for the full development cycle
of language resources and technology, from research through to innovative
products and services [Piperidis, 2012].

Language resources in META-SHARE span the whole spectrum from monolingual and
multilingual data sets, both structured (e.g., lexica, terminological
databases, thesauri) and unstructured (e.g., raw text corpora), as well as
language processing tools (e.g., part-of-speech taggers, chunkers, dependency
parsers, named entity recognisers, parallel text aligners, etc.). Resources
are described according to the META-SHARE metadata schema [Gavrilidou et al.
2012], catering in particular for the needs of the HLT community, while the
META-SHARE model licensing scheme has a firm orientation towards the creation
of an openness culture respecting, however, legacy and less open, or
permissive, licensing options.

META-SHARE has been in operation since 2012, and it is currently in its 3.0.3
version, released in May 2016. It currently features 29 repositories set up
and maintained by 37 organisations in 25 countries of the EU. The observed
usage as well as the number of nodes, resources, users, queries, views and
downloads are all encouraging and considered as supportive of the choices made
so far [Piperidis et al., 2014]. Resource sharing in CRACKER will build upon
and extend the existing META-SHARE resource infrastructure, its specific MT-
dedicated repository ( _http://qt21.metashare.ilsp.gr_ ) as well as editing
and annotation tools in support of translation evaluation and translation
quality scoring (e.g., _http://www.translate5.net/_ ).

This infrastructure, together with its bridges, provides support mechanisms
for the identification, acquisition, documentation and sharing of MT-related
data sets and language processing tools.

##  Dataset Reference and Name

CRACKER opts for a standard identification mechanism to be employed for each
data set, in addition to the identifier used internally by META-SHARE itself.

Reference to the a dataset ID can be optionally made with the use of an ISLRN
( _International Standard Language Resource Number_ ), the most recent
universal identification schema for LRs which provides LRs with unique
identifiers using a standardized nomenclature, ensuring that LRs are
identified, and consequently recognized with proper references (cf. figures 1
and 2).

**Figure 1. An example resource entry from the ISLRN website indicating the
resource metadata, including the
ISLRN,_http://www.islrn.org/resources/060-785-139-403-2/_ . **

**Figure 2. Examples of resources with the ISLRN indicated, from the ELRA
(left) and the LDC (right) catalogues.**

##  Dataset Description

In accordance with META-SHARE, CRACKER is addressing the following resource
and media types:

  * **corpora** (text, audio, video, multimodal/multimedia corpora, n-gram resources), 

  

  * **lexical/conceptual resources** (e.g., computational lexicons, ontologies, machine-readable dictionaries, terminological resources, thesauri, multimodal/ multimedia lexicons and dictionaries, etc.) 

  

  * **language descriptions** (e.g., computational grammars) 

  

  * **technologies** (tools/services) that can be used for the processing of data resources 

  

Several datasets that have been and will be produced (test data, training
data) by the WMT, IWSLT and QT Marathon events and, later on, extended with
information on the results of their respective evaluation and benchmarking
campaigns (documentation, performance of the systems etc.) will be documented
and made available through META-SHARE.

A list of CRACKER resources with brief descriptive information is provided
below. This list is only indicative of the resources to be included in CRACKER
and more detailed information and descriptions will be provided in the course
of the project.

###  R#1 WMT Test Sets  
  
<table>  
<tr>  
<th>

**Resource Name**

</th>  
<th>

WMT Test Sets

</th> </tr>  
<tr>  
<td>

**Resource Type**

</td>  
<td>

Corpus

</td> </tr>  
<tr>  
<td>

**Media Type**

</td>  
<td>

Text

</td> </tr>  
<tr>  
<td>

**Language(s)**

</td>  
<td>

The core languages are German-English and Czech-English; other guest language
pairs will be introduced in each year.

For 2015 the guest language was Romanian. We also included Russian, Turkish
and Finnish, with funding from other sources.

</td> </tr>  
<tr>  
<td>

**License**

</td>  
<td>

The source data are crawled from online news sites and carry the respective
licensing conditions.

</td> </tr>  
<tr>  
<td>

**Distribution**

**Medium**

</td>  
<td>

Downloadable

</td> </tr>  
<tr>  
<td>

**Usage**

</td>  
<td>

For tuning and testing MT systems.

</td> </tr>  
<tr>  
<td>

**Size**

</td>  
<td>

3000 sentences per language pair, per year.

</td> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

These are the test sets for the WMT shared translation task. They are small
parallel data sets used for testing MT systems, and are typically created by
translating a selection of crawled articles from online news sites.

WMT15 test sets are available at _http://www.statmt.org/wmt15/_

WMT16 test sets are available at

_http://data.statmt.org/wmt16/translation-task/test.tgz_

</td> </tr> </table>

###  R#2 WMT Translation Task Submissions  
  
<table>  
<tr>  
<th>

**Resource Name**

</th>  
<th>

WMT Translation Task Submissions

</th> </tr>  
<tr>  
<td>

**Resource Type**

</td>  
<td>

Corpus

</td> </tr>  
<tr>  
<td>

**Media Type**

</td>  
<td>

Text

</td> </tr>  
<tr>  
<td>

**Language(s)**

</td>  
<td>

They match the languages of the test sets.

</td> </tr>  
<tr>  
<td>

**License**

</td>  
<td>

Preferably CC BY 4.0.

</td> </tr>  
<tr>  
<td>

**Distribution**

**Medium**

</td>  
<td>

Downloadable

</td> </tr>  
<tr>  
<td>

**Usage**

</td>  
<td>

Research into MT evaluation. MT error analysis.

</td> </tr>  
<tr>  
<td>

**Size**

</td>  
<td>

The 2015 tarball is 25M

The 2016 tarball is 44M

</td> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

These are the submissions to the WMT translation task from all teams. We
create a tarball for use in the metrics task, but it is available for future
research in MT evaluation.

The WMT15 version is available at _http://www.statmt.org/wmt15/_ The WMT16
version is available at

_http://data.statmt.org/wmt16/translation-task/wmt16-submitted-datav2.tgz_

</td> </tr> </table>

###  R#3 WMT Human Evaluations  
  
<table>  
<tr>  
<th>

**Resource Name**

</th>  
<th>

WMT Human Evaluations

</th> </tr>  
<tr>  
<td>

**Resource Type**

</td>  
<td>

Pairwise rankings of MT output.

</td> </tr>  
<tr>  
<td>

**Media Type**

</td>  
<td>

Numerical data (in csv)

</td> </tr>  
<tr>  
<td>

**Language(s)**

</td>  
<td>

N/a

</td> </tr>  
<tr>  
<td>

**License**

</td>  
<td>

Preferably CC BY 4.0

</td> </tr>  
<tr>  
<td>

**Distribution**

**Medium**

</td>  
<td>

Downloadable

</td> </tr>  
<tr>  
<td>

**Usage**

</td>  
<td>

In conjunction with the WMT Translation Task Submissions, this can be used for
research into MT evaluation.

</td> </tr>  
<tr>  
<td>

**Size**

</td>  
<td>

For 2014, it was 0.5MB

</td> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

These are the pairwise rankings of the translation task submissions.

The WMT15 versions are available at _http://www.statmt.org/wmt15/_

The WMT16 versions will be available at _http://www.statmt.org/wmt16/_ .

They will be made available in time for the workshop in August 2016\.

</td> </tr> </table>

###  R#4 WMT News Crawl  
  
<table>  
<tr>  
<th>

**Resource Name**

</th>  
<th>

WMT News Crawl

</th> </tr>  
<tr>  
<td>

**Resource Type**

</td>  
<td>

Corpus

</td> </tr>  
<tr>  
<td>

**Media Type**

</td>  
<td>

Text

</td> </tr>  
<tr>  
<td>

**Language(s)**

</td>  
<td>

English, German, Czech plus variable guest languages.

</td> </tr>  
<tr>  
<td>

**License**

</td>  
<td>

The source data are crawled from online news sites and carry the respective
licensing conditions.

</td> </tr>  
<tr>  
<td>

**Distribution**

**Medium**

</td>  
<td>

Downloadable

</td> </tr>  
<tr>  
<td>

**Usage**

</td>  
<td>

Building MT systems

</td> </tr>  
<tr>  
<td>

**Size**

</td>  
<td>

For 2014, it was 5.3G (compressed)

The WMT16 version was 4.8G

</td> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

This data set consists of text crawled from online news, with the html
stripped out and sentences shuffled.

For WMT15 it is available at _http://www.statmt.org/wmt15/_

For WMT16 it is available at
_http://data.statmt.org/wmt16/translationtask/training-monolingual-news-
crawl.tgz_

</td> </tr> </table>

###  R#5 Quality Estimation Datasets  
  
<table>  
<tr>  
<th>

**Resource Name**

</th>  
<th>

Quality Estimation Datasets

</th> </tr>  
<tr>  
<td>

**Resource Type**

</td>  
<td>

Bilingual corpora labelled for quality at phrase-level

</td> </tr>  
<tr>  
<td>

**Media Type**

</td>  
<td>

Text

</td> </tr>  
<tr>  
<td>

**Language(s)**

</td>  
<td>

German-English, English-German and one of the challenging language pairs
addressed in WMT (either Romanian or Latvian)

</td> </tr>  
<tr>  
<td>

**License**

</td>  
<td>

Creative Commons

</td> </tr>  
<tr>  
<td>

**Distribution**

**Medium**

</td>  
<td>

Downloadable

</td> </tr>  
<tr>  
<td>

**Usage**

</td>  
<td>

Other researchers working on quality estimation or evaluation of machine
translation

</td> </tr>  
<tr>  
<td>

**Size**

</td>  
<td>

At least 1,000 machine translations will be annotated for quality to train and
test quality estimation systems for each language pair.

</td> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

The corpus will consist of source segments in English, their machine
translation, a segmentation of these translations into phrases and a binary
score given by humans indicating the quality of these phrases.

</td> </tr> </table>

###  R#6 WMT 2016 Automatic Post-­‐editing data set  
  
<table>  
<tr>  
<th>

**Resource Name**

</th>  
<th>

WMT 2016 Automatic Post-editing data set

</th> </tr>  
<tr>  
<td>

**Resource Type**

</td>  
<td>

corpus

</td> </tr>  
<tr>  
<td>

**Media Type**

</td>  
<td>

text

</td> </tr>  
<tr>  
<td>

**Language(s)**

</td>  
<td>

English to German

</td> </tr>  
<tr>  
<td>

**License**

</td>  
<td>

TAUS Terms of Use

(https://lindat.mff.cuni.cz/repository/xmlui/page/licence-TAUS_QT21). TAUS
grants to QT21 User access to the WMT Data Set with the following rights:

i) the right to use the target side of the translation units into a commercial
product, provided that QT21 User may not resell the WM

T Data Set as if it is its own new translation;

  2. the right to make Derivative Works; and 

  

  3. the right to use or resell such Derivative Works commercially and for the following goals: 

  

  

i) research and benchmarking; ii) piloting new solutions; and iii) testing of
new commercial services.

</td> </tr>  
<tr>  
<td>

**Distribution**

**Medium**

</td>  
<td>

downloadable

</td> </tr>  
<tr>  
<td>

**Usage**

</td>  
<td>

Training of Automatic Post-editing and Quality Estimation components

</td> </tr>  
<tr>  
<td>

**Size**

</td>  
<td>

1294 kb

</td> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

Training, development and text data (the same used for the Sentencelevel
Quality Estimation task) consist of English-German triplets ( _source_ ,
_target_ and _post-edit_ ) belonging to the Information Technology domain and
already tokenized. Training and development respectively contain 12,000 and
1,000 triplets, while the test set contains 2,000 instances. Target sentences
are machine-translated with the KIT system. Post-edits are collected by
Text&Form from professional translators. All data is provided by the EU
project QT21 ( _http://www.qt21.eu/_ ).

</td> </tr> </table>

##  Standards and Metadata

CRACKER follows META-SHARE’s best practices for data documentation. The basic
design principles of the META-SHARE model have been formulated according to
specific needs identified, namely: (a) a typology for language resources (LR)
identifying and defining all types of LRs and the relations between them; (b)
a common terminology with as clear semantics as possible; (c) minimal schema
with simple structures (for ease of use) but also extensive, detailed schema
(for exhaustive description of LRs); (d) interoperability between descriptions
of LRs and associated software across repositories.

In answer to these needs, the following design principles were formulated:

  * expressiveness, i.e., cover any type of resource; 

  

  * extensibility, allowing for future extensions and catering for combinations of LR types for the creation of complex resources; 

  

  * semantic clarity, through a bundle of information accompanying each schema element; 

  

  * flexibility, by employing both exhaustive and minimal descriptions; 

  

  * interoperability, through mappings to widely used schemas (DC, Clarin Concept Registry (which has taken over the ISOcat DCR)). 

  

The central entity of the META-SHARE ontology is the Language Resource. In
parallel, LRs are linked to other satellite entities through relations,
represented as basic elements. The interconnection between the LR and these
satellite entities pictures the LR’s lifecycle from production to use:
reference documents related to the LR (papers, reports, manuals etc.),
persons/organizations involved in its creation and use (creators, distributors
etc.), related projects and activities (funding projects, activities of usage
etc.), accompanying licenses, etc. CRACKER will follow these standard
practices for data documentation, in line with their design principles of
expressiveness, extensibility, semantic clarity, flexibility and
interoperability.

The META-SHARE metadata can also be represented as linked data following the
work being done in Task 3.3 of the CRACKER project, the LD4LT group
(https://www.w3.org/community/ld4lt/), and the LIDER project, which has
produced an OWL version of the META-SHARE metadata schema
(http://purl.org/net/def/metashare). Such representation can be generated by
the mapping process initiated by the above tasks and initiatives.

As an example, a subset of the META-SHARE metadata records has been converted
to Linked Data and is accessible via the Linghub portal (
_http://linghub.liderproject.eu_ ).

Included in the conversion process to OWL was the legal rights module of the
METASHARE schema ( _http://purl.org/NET/ms-­‐rights_ ), taking into account
the ODRL model & vocabulary v.2.1
(https://www.w3.org/community/odrl/model/2.1/).

##  Data Sharing

As said, resource sharing will build upon META-SHARE. CRACKER will maintain
and release an improved version of the META-SHARE software.

For its own data sets, CRACKER will continue to apply, whenever possible, the
permissive licensing and open sharing culture which has been one of the key
components of META-SHARE for handling research data in the digital age.

Consequently, for the MT/LT research and user communities, sharing of all
CRACKER data sets will be organised through META-SHARE. The metadata schema
provides components and elements that address copyright and Intellectual
Property Rights (IPR) issues, restrictions imposed on data sharing and also
IPR holders. These together with an existing licensing toolkit can serve as
guidance for the selection of the appropriate licensing solution and creating
the respective metadata. In parallel, ELRA/ELDA has recently implemented a
licensing wizard  3  , helping rights holders in defining and selecting the
appropriate license under which they can distribute their resources. The
wizard will be possibly integrated or linked to

META-SHARE.

##  Archiving and Preservation

All datasets produced will be provided and made sustainable through the
existing META-SHARE repositories, or new repositories that partners may choose
to set up and link to the META-SHARE network. Datasets will be locally stored
in the repositories’ storage layer in compressed format.

#  Collaboration with Other Projects and Initiatives

CRACKER has created an umbrella initiative that includes all currently running
and recently completed EU-supported projects working on technologies for a
multilingual Europe, namely the Cracking the Language Barrier initiative  4  .
This federation of projects is set up around a short multi-lateral Memorandum
of Understanding (MoU)  5  .

The MoU contains a non-exhaustive list of general areas of collaboration, and
all projects and organisations that sign this document are invited to
participate in these collaborative activities.

At the time of writing (June 2016), the MoU has been signed by 10
organisations and 23 projects (including service contracts):

  * _Organisations:_ CITIA, CLARIN, ELEN, EFNIL, GALA, LT-Innovate, META-NET, NPLD, TAUS, W3C. 

  

  * _Projects:_ ABUMATRAN, CRACKER, DLDP, ELRC, EUMSSI, EXPERT, Falcon, FREME, HimL, KConnect, KRISTINA, LIDER, LT_Observatory, MixedEmotions, MLi, MMT, MultiJEDI, MultiSensor, Pheme, QT21, QTLeap, SUMMA, XLiMe 

  

Additional organisations and projects have been approached for participation
in the initiative. The group of members is constantly growing.

#  Recommendations for Harmonised DMPs for the ICT-­‐17 Federation of Projects

One of the areas of collaboration included in the CRACKER MoU refers to the
data management and repositories for data, tools and technologies; thus, all
projects and organisations participating in the initiative are invited to join
forces and to collaborate on harmonising data management plans (metadata, best
practices etc.) as well as data, tools and technologies distribution through
open repositories.

At the kick-off meeting of the ICT-17 group of projects on April 28, 2015,
CRACKER offered support to the “Cracking the language barrier” federation of
projects by proposing a Data Management Plan template with shared key
principles that can be applied, if deemed helpful, by all projects, again,
advocating an open sharing approach whenever possible (also see D1.2). This
plan has been included in the overall communication plan and it will inform
the working group that will maintain and update the roadmap for European MT
research.

In future face-to-face or virtual meetings of the federation, we propose to
discuss the details about metadata standards, licenses, or publication types.
Our goal is to prepare a list of planned tangible outcomes of all projects,
i.e., all datasets, publications, software packages and any other results,
including technical aspects such as data formats. We would like to stress that
the intention is not to provide the primary distribution channel for all
projects’ data sets but to provide, in addition to the channels foreseen in
the projects’ respective Descriptions of Actions, one additional, alternative
common distribution platform and approach for metadata description for all
data sets produced by the “Cracking the language barrier” federation of
projects.  
  
<table>  
<tr>  
<th>

**In this respect, the activities that the participating projects may
optionally undertake are the following:**

  1. Participating projects may consider using META-SHARE as an additional, alternative distribution channel for their tools or data sets, using one of the following options: 

    1. projects may set up a project or partner specific META-SHARE repository, and use either open or even restrictive licences; 

  

    2. projects may join forces and set up one dedicated “Cracking the language barrier” META-SHARE repository to host the resources developed by all participating projects, and use either open or even restrictive licences (as appropriate). 

  
  

  

  2. Participating projects may wish to use the META-SHARE repository software  6  for documenting their resources, even if they do not wish to link to the network. 

  

  

</th> </tr> </table>

As mentioned above, the collaboration in terms of harmonizing data management
plans and recommending distribution through open repositories forms one of the
six areas of collaboration indicated in the _“Cracking the Language Barrier”
MoU_ . Participation in one or more of the potential areas of collaboration in
this joint community activity, is optional.

An example of harmonized DMP is that of the _FREME_ project. FREME signed the
corresponding Memorandum of Understanding and is participating in this
initiative. As part of the effort, FREME will make available its metadata from
existing datasets that are used by FREME, using a combined metadata scheme:
this covers both the META-SHARE template provided by CRACKER, as well as the
DataID schema  7  . FREME will follow both META-SHARE and DataID practices for
data documentation, verification and distribution, as well as for curation and
preservation, ensuring the availability of the data and enabling access,
exploitation and dissemination. Further details as well as the actual dataset
descriptions have been documented in the FREME Data management Plan  8  . See
section 3.1.2 of that plan for an example of the combined approach.

##  Recommended Template of a DMP

As pointed out already, the collaboration in terms of harmonizing data
management plans is considered an important aspect of convergence within the
groups of projects. In this respect, any project that is interested in and
intends to collaborate towards a joint approach for a DMP may follow the
proposed structure of a DMP template. The following section describes a
recommended template, while the previous section (3) has provided a concrete
example of such an implementation, i.e. the CRACKER DMP. It is, of course,
expected that any participating project may accommodate its DMP content
according to project-specific aspects and scope. These DMPs are also expected
to be gradually completed as the project(s) progress into their
implementation.  
  
<table>  
<tr>  
<th>

**I. The ABC Project DMP**

  1. **Introduction/ Scope**

  

  2. **Data description**

  

  3. **Identification mechanism iv. Standards and Metadata**

  

  

**v. Data Sharing vi. Archiving and preservation**

</th> </tr> </table>

**Figure 3. The recommended template for the implementation and structuring of
a DMP.**

###  Introduction and Scope

Overview and approach on the resource sharing activities underpinning the
language technology and machine translation research and development within
each participating project and as part of the “Cracking the language barrier”
initiative of projects.

###  Dataset Reference and Name

It is recommended that a standard identification mechanism should be employed
for each data set, e.g., (a) a PID (Persistent Identifier as a long-lasting
reference to a dataset) or (b) _ISLRN_ (International Standard Language
Resource Number).

###  Dataset Description

It is recommended that the following resource and media types are addressed:

  * **corpora** (text, audio, video, multimodal/multimedia corpora, n-gram resources), 

  

  * **lexical/conceptual resources** (e.g., computational lexicons, ontologies, machine-readable dictionaries, terminological resources, thesauri, multimodal/ multimedia lexicons and dictionaries, etc.) 

  

  * **language descriptions** (e.g., computational grammars) 

  

  * **technologies** (tools/services) that can be used for the processing of data resources 

  

In relation to the resource identification of the “Cracking the language
barrier” initiative and to have a first rough estimation of their number,
coverage and other core characteristics, CRACKER will circulate two templates
dedicated to datasets and associated tools and services respectively. Projects
that wish and decide to participate in this uniform cataloguing are invited to
fill in these templates with brief descriptions of the resources they estimate
to be produced and/or collected. The templates are as follows (also in the
Appendix):  
  
<table>  
<tr>  
<th>

**Resource Name**

</th>  
<th>

Complete title of the resource

</th> </tr>  
<tr>  
<td>

**Resource Type**

</td>  
<td>

Choose one of the following values:

Lexical/conceptual resource, corpus, language description (missing values can
be discussed and agreed upon with CRACKER)

</td> </tr>  
<tr>  
<td>

**Media Type**

</td>  
<td>

The physical medium of the content representation, e.g., video, image, text,
numerical data, n-grams, etc.

</td> </tr>  
<tr>  
<td>

**Language(s)**

</td>  
<td>

The language(s) of the resource content

</td> </tr>  
<tr>  
<td>

**License**

</td>  
<td>

The licensing terms and conditions under which the LR can be used

</td> </tr>  
<tr>  
<td>

**Distribution**

**Medium**

</td>  
<td>

The medium, i.e., the channel used for delivery or providing access to the
resource, e.g., accessible through interface, downloadable, CD/DVD, hard copy
etc.

</td> </tr>  
<tr>  
<td>

**Usage**

</td>  
<td>

Foreseen use of the resource for which it has been produced

</td> </tr>  
<tr>  
<td>

**Size**

</td>  
<td>

Size of the resource with regard to a specific size unit measurement in form
of a number

</td> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

A brief description of the main features of the resource (including url, if
any)

</td> </tr> </table>

**Table 1. Template for datasets description**  
  
<table>  
<tr>  
<th>

**Technology Name**

</th>  
<th>

Complete title of the tool/service/technology

</th> </tr>  
<tr>  
<td>

**Technology Type**

</td>  
<td>

Tool, service, infrastructure, platform, etc.

</td> </tr>  
<tr>  
<td>

**Technology Type**

</td>  
<td>

The function of the tool or service, e.g., parser, tagger, annotator, corpus
workbench etc.

</td> </tr>  
<tr>  
<td>

**Media Type**

</td>  
<td>

The physical medium of the content representation, e.g., video, image, text,
numerical data, n-grams, etc.

</td> </tr>  
<tr>  
<td>

**Language(s)**

</td>  
<td>

The language(s) that the tool/service operates on

</td> </tr>  
<tr>  
<td>

**License**

</td>  
<td>

The licensing terms and conditions under which the tool/service can be used

</td> </tr>  
<tr>  
<td>

**Distribution Medium**

</td>  
<td>

The medium, i.e., the channel used for delivery or providing access to the
tool/service, e.g., accessible through interface, downloadable, CD/DVD, etc.

</td> </tr>  
<tr>  
<td>

**Usage**

</td>  
<td>

Foreseen use of the tool/service for which it has been produced

</td> </tr>  
<tr>  
<td>

**Description**

</td>  
<td>

A brief description of the main features of the tool/service

</td> </tr> </table>

**Table 2. Template for technologies description**

###  Standards and Metadata

Participating projects are recommended to deploy the META-SHARE metadata
schema for the description of their resources and provide all details
regarding their name, identification, format, etc.

Providers of resources wishing to participate in the initiative will be able
to request and get assistance through dedicated helpdesks on questions
concerning (a) the metadata based LR documentation at _helpdesk-metadata@meta-
share.eu_ (b) the use of licences, rights of use, IPR issues, etc. at
_helpdesk-legal@meta-share.eu_ and (c) the repository installation and use at
_helpdesk-technical@meta-share.eu_ .

###  Data Sharing

It is recommended that all datasets (including all relevant metadata records)
to be produced by the participating projects will be made available under
licenses, which are as open and as standardised as possible, as well as
established as best practice. as Any interested provider can consult the META-
SHARE licensing options and pose related questions to the respective helpdesk.

###  Archiving and Preservation

As regards the procedures for long-term preservation of the datasets, two
options may be considered:

  1. As part of the further development and maintenance of the META-SHARE infrastructure, a project that participates in the “Cracking the language barrier” initiative may opt to set up its own project or partner specific META-SHARE repository and link to the META-SHARE network, with CRACKER providing all support necessary in the installation, configuration and set up process. 

  

  2. Alternatively, one dedicated “Cracking the language barrier” META-SHARE repository can be set up to host the resources developed by all participating projects, with CRACKER catering for procedures and mechanisms enabling long-term preservation of the datasets. 

  

  

It should be repeated at this point that following the META-SHARE principles,
the curation and preservation of the datasets, together with the rights of
their use and possible restrictions, are under the sole control and
responsibility of the data providers.