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Language Data Commons RO-Crate Profile |
This document is a DRAFT RO-Crate profile for Language Data resources. The profile specifies the contents of RO-Crate Metadata Documents for language resources and gives guidance on how to structure language data collections both at the RO-Crate package level and in a repository containing multiple packages.
This profile assumes that the principles and standards set out in the Arkisto platform, or similar compatible approaches are being used.
The core metadata vocabularies for this profile are:
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RO-Crate recommendations for data packaging and basic discoverability metadata which is mostly Schema.org terms with a handful of additions. Following RO-Crate practice, basic metadata terms such as "who, what, where" and bibliographic-style descriptions are chosen from schema.org (in preference to other vocabularies such as Dublin Core or FOAF) where possible with domain-specific vocabularies used for things which are not common across domains (such as types of language).
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An updated version of the Open Language Archives Community (OLAC) vocabularies http://www.language-archives.org; originally expressed as XML schemas. The new vocabulary is under development here: https://purl.archive.org/language-data-commons/terms
This document is primarily for use by tool developers, data scientists and metadata specialists developing scripts or systems for user communities. It is not intended for use by non-specialists.
Just as we would not expect repository users to type in Dublin Core metadata in XML format by hand we do not expect our users to have to deal directly with the JSON-LD presented here, this document is for tool developers to build systems that crosswalk data from existing systems, or allow for user-friendly data entry.
This profile covers various kinds of crate metadata:
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Structural RO-Crate metadata - how the root dataset links to files, and the abstract structure of nested collections (e.g. collections/corpora or other curated datasets) and objects of study; linguistic Items, Sessions or Texts). This profile assumes that a repository (for example, an OCFL storage root, with an API for accessing it) exists and that it can at a minimum support (a) listing all items of the repository and returning their RO-Crate metadata, and (b) retrieving an item given its ID.
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Types of language data - is this resource a dialogue? A written text? A transcript or other annotation - which file has which kind of data in it? What is inside CSV and other structured files? The vocabulary used for language-specific data is the Language Data Commons vocabulary which is being developed alongside this profile. The vocabulary is described here: http://purl.archive.org/language-data-commons/terms
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Contextual metadata - how to link people who had speaking, authoring, collection roles, places, subjects.
The structural elements of a Language Data Commons RO-Crate are:
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A Collection / Object hierarchy to allow language data to be grouped - for example, a corpus with sub-corpora, or collections of items (objects) from a particular region.
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Dataset and File entities (as per RO-Crate). Files may be referenced locally or via URI - e.g. from an API. If an RO-Crate contains files they MUST be linked to the root dataset using
hasPartrelationships as per the RO-Crate specification.
NOTE: The terms Collection and Object are encoded in RO-Crate metadata using RepositoryCollection and RepositoryObject types respectively. These in turn are re-named versions of the Portland Common Data Model types, pcdm:Collection and pcdm:Object.
A conformant RO-Crate:
| Property | Required? | Expected value range | Descriptions |
| name | MUST | Text | The name of this dataset. |
| license | MUST | CreativeWork | Link to a document that describes the rights and obligations for users of this collection record. NOTE: This is does not necessarily cover the license terms that may apply to Objects in the collection which MAY have specific licensing. Licensing on other obkjects over-rides the license attached to a collection record. |
| rightsHolder | MUST | Text, Person, Organization | A person or organization owning or managing rights over the resource. |
| author | MUST | Person, Organization | The person or organisation responsible for creating this collection of data. |
| accountablePerson | MUST | Person, Organization | The person or organisation who is the data steward for this resource. |
| publisher | MUST | Organization | The organisation responsible for releasing this dataset. |
| description | MUST | TextArea | An abstract of the collection. Include as much detail as possible about the motivation and use of the dataset, including things that we do not yet have properties for. Max limit 200 words. |
| isAccessibleForFree | MAY | Boolean | This is available under an Open Access license. |
| isBasedOn | MAY | Text, URL | Link to or description of the an original resource at an institution that holds it. |
| usageInfo | MAY | Text | This field should contain either a free text bibliographic citation for this material, e.g. 'Cite as: Musgrave (2023). Title of work. DOI' or provide additional information on licensing options for using the data, e.g. 'Contact the Data Steward to discuss license terms'. If both are needed, use two fields. |
| funder | MAY | Organization | The organisation(s) responsible for funding the creation or collection of this dataset. |
| citation | MAY | CreativeWork | Associated publications. |
| temporalCoverage | MAY | DateTime, Text | The range of years of creation for items in this dataset using a slash, e.g. 1900/1945. If there are sub-collections with different coverages put this on the sub-collections not the top-level. |
| spatialCoverage | MAY | Place | The place(s) that are the focus of the content. It is a sub-property of contentLocation intended primarily for more technical and detailed materials. For example with a dataset, it indicates areas that the dataset describes: a dataset Cape York languages would have spatialCoverage which was the place: the outline of the Cape. |
| hasCollectionProtocol | MAY | CollectionProtocol | A link to a CollectionProtocol object with (at least) a summary of how resources were selected or elicited for this collection/sub-collection. |
| contentLocation | MAY | ContentLocation | The location depicted or described in the content. For example, the location in a photograph or painting. |
| hasMember | MAY | RepositoryCollection | The sub-collections, if any, associated with this collection. |
| hasPart | MAY | File | An item or CreativeWork that is part of this item, or CreativeWork (in some sense). |
A collection such as a corpus may be stored in a repository or transmitted either as:
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A distributed collection: a set of individual RO-Crates which reference separate collection records with ONE Object and one Collection per crate
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A bundled single crate which contains all the Collection and Object data.
Distributed Collections may reference member collections or Objects in hasMember property but should not include descriptions of Objects that are stored elsewhere in the repository.
Objects are placed in a Collection using the memberOf property (pcdm:memberOf), which is required. The reverse may also be encoded using the hasMember property on a Collection.
The following diagram shows how these relationships are encoded in a single "bundled" RO-Crate.
The next diagram shows how distributed crates (with one RO-Crate per Object and Collection) are linked.
Which linking strategy is used is an implementation choice for repository developers.
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Choose to use a single bundled crate for a collection when all of these conditions are true:
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The collection is final and is expected to be stable, i.e. there is negligible chance of having to withdraw any of its contents or files
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The collection and all its files can easily be transferred in a single transaction - say 20Gb total
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All the material in the corpus shares the same license for reuse
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Split a collection into fragmented RepositoryCollection and RepositoryObject crates - with one crate per repository object when any of these conditions are true:
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The collection is not yet stable
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New items are being added or changed.
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There is a chance that some data may have to be taken down or withdrawn at the request of participants.
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The total size of the collection will present challenges for data transfer.
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There is more than one data reuse license applicable.
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A collection is a group of related Objects. Examples of collections include corpora, and sub-corpora, as well as aggregations of cultural objects such as PARADISEC collections which bring together items collected in a region or on a session with informants. This follows the Alveo usage:
Items [Objects in this model] are grouped into collections which might correspond to curated corpora such as ACE or informal collections such as a sample of documents from the AustLit archive (http://www.austlit.edu.au/).
When an RO-Crate is used to package a collection which is part of another Collection it has a memberOf property which references a resolvable ID (within the context of a repository or service) of the parent Collection. The Collection may also list its members in a hasMember property, but this is not required.
The root dataset must have at least these @type values: ["Dataset", "RepositoryCollection"]
| Property | Required? | Expected value range | Descriptions |
| inLanguage | MUST | Language | The language(s) of the materials (including PromaryMaterials, DerivedMaterials and Annotations) in this collection. |
| subjectLanguage | MUST | Language | The languages that the materials in the collection are about (not the language that it is in). This is particularly used on Annotations that may talk about PrimaryMaterials or Derived |
| name | MUST | Text | The name of this collection. |
| accountablePerson | MUST | Person, Organization | The person or organisation who is the data steward for this resource. |
| conformsTo | MAY | Select | A link to the Text Commons RO-Crate profile for collections. |
| author | MAY | Person, Organization | The person or organisation responsible for creating this collection of data. Authors should be identified using URIs such as ORCiD or ROR. |
| funder | MAY | Organization | The organisation(s) responsible for funding the creation or collection of this data. |
| citation | MAY | CreativeWork | Associated publications. |
| isBasedOn | MAY | Text, URL | Link to or description of the an original resource at an institution that holds it. |
| description | MAY | TextArea | A description of the collection. |
| temporalCoverage | MAY | DateTime, Text | The range of years of creation for items in this collection using a slash, e.g. 1900/1945. If there are sub-collections with different coverages put this on the sub-collections not the top-level. |
| hasCollectionProtocol | MAY | CollectionProtocol | A link to a CollectionProtocol object with (at least) a summary of how resources were selected or elicited for this collection/sub-collection. |
| hasMember | MAY | RepositoryCollection | The sub-collection. |
| dateCreated | MAY | Date | The (earliest) date the data in this dataset were created. |
| dateFreeText | MAY | Text | Date information which cannot be put in one of that standard date formats, eg 'mid 1970s' or it is not clear for example if it is a creation or publication date. |
| holdingArchive | MAY | Organization, Text | Organization where the original of this work or collection is housed |
An Object is a single unit linked to tightly related files, for example - a dialogue or session in a speech study, or a work (document) in a written corpus. This is based on the use of the term Item in Alveo:
The data model that we have developed for the storage of language resources is built around the concept of an item which corresponds (loosely) to a record of a single communication event. An item is often associated with a single text, audio or video resource but could include a number of resources, for example, the different channels of audio recording or an audio recording and associated textual transcript. Items are grouped into collections which might correspond to curated corpora such as ACE or informal collections such as a sample of documents from the AustLit archive (http://www.austlit.edu.au/). https://www.researchonline.mq.edu.au/vital/access/services/Download/mq:37347/DS01
The definition of an object is necessarily loose and needs to reflect what data owners have chosen to do with their collections in the past.
If an RO-Crate contains a single Object the Root Dataset would have a
@type property of ["Dataset", "RepositoryObject"] with a
conformsTo property pointing to the language-data-commons Object profile
(this document).
If an RO-Crate contains an entire collection then each Object has a
@type property of ["Dataset", "RepositoryObject"] and a conformsTo
property referencing this document. For example:
Objects SHOULD have files (which may be included in an RO-Crate for the object, or as part of a collection crate).
In this example the Object in question is an interview from a speech corpus with three files - the diagram shows the relationships between the object and its files (and the contextual metadata of a Person who takes the role of the speaker/informant (discussed in more detail below).
There are a number of terms that can be used to characterise resources - these use the schema.org mechanism of DefinedTerm and DefinedTermSet.
| Property | Required? | Expected value range | Descriptions |
There are three important types of files (or references to other
works) that may be included - PrimaryMaterial - which is a recording or
original text, or a citation of or proxy for it, DerivedMaterial which
has been generated or sampled from primary material by a process such as format
conversion or digitization, and Annotation, which contains one or more types of
analysis of the PrimaryMaterial or DerivedMaterial.
PrimaryMaterial MAY be a video or audio file if it is available or MAY be a ContextualEntity referencing a primary text such as a book.
undefined
DerivedMaterial is a non-analytical derivation from PrimaryMaterial for example downsampled video or excerpted text.
undefined
undefined
An annotation is a description or analysis of other material. More than one type of annotation may be present in a file.
undefined
CSV or similar tabular files are often used to represent transcribed speech or sign language data, sometimes also with time codes. To enable automated location of which column is which, use a frictionless Table Schema described by a File entity in the crate.
For example:
{
"@id": "art_schema.json",
"@type": "File",
"name": "Frictionless Data Schema for CSV transcript files",
"encodingFormat": "application/json",
"conformsTo": {
"@id": "https://specs.frictionlessdata.io/table-schema/"
}
}| Property | Required? | Expected value range | Descriptions |
The place in which data was collected may be indicated using the contentLocation property.
{
"@id": "./",
"@type": [
"Dataset",
"RepositoryObject"
],
"additionalType": "item",
"bornDigital": 0,
"collector": {
"@id": "http://nla.gov.au/nla.party-479603"
},
"contentLanguages": [
{
"@id": "https://glottolog.org/resource/languoid/id/bisl1239"
},
{
"@id": "https://glottolog.org/resource/languoid/id/sout2856"
}
],
"dateCreated": "2012-09-27T10:08:00.000Z",
"dateModified": "2019-09-25T23:52:02.000Z",
"depositor": {
"@id": "http://nla.gov.au/nla.party-479603"
},
"description": "Elicitation with Silas Alban at Eratap village, Efate. (side B) 11/10/1995. Reading a wordlist in Nafsan.",
"digitisedOn": "Mon Jan 01 2001 00:00:00 GMT+1100 (Australian Eastern Daylight Time)",
"external": 0,
"hasPart": [
{
"@id": "NT1-001-001A.wav"
},
{
"@id": "NT1-001-001B.mp3"
},
{
"@id": "NT1-001-001B.wav"
},
{
"@id": "NT1-001-001A.mp3"
}
],
"identifier": [
{
"@id": "#identifier_domain"
},
{
"@id": "#identifier_id"
},
{
"@id": "#identifier_hashid"
},
{
"@id": "#identifier_itemId"
},
{
"@id": "#identifier_collectionId"
}
],
"languageAsGiven": "Nafsan",
"license": {
"@id": "LICENSE.txt"
},
"memberOf": {
"@id": "https://catalog.paradisec.org.au/collections/NT1"
},
"metadataExportable": 1,
"name": "Elicitation with Silas Alban",
"operator": {
"@id": "jommij@yahoo.com"
},
"originalMedia": "audiocassette",
"originatedOn": "1995-08-16",
"private": 0,
"publisher": {
"@id": "http://nla.gov.au/nla.party-593909"
},
"recorder": {
"@id": "http://nla.gov.au/nla.party-479603"
},
"speaker": {
"@id": "#Sailas Alban"
},
"subjectLanguages": {
"@id": "https://glottolog.org/resource/languoid/id/sout2856"
},
"tapesReturned": 0,
"conformsTo": {
"@id": "https://purl.archive.org/language-data-commons/profile#Object"
},
"datePublished": "2019-09-25T23:52:02.000Z",
"inLanguage": [
{
"@id": "https://glottolog.org/resource/languoid/id/bisl1239"
},
{
"@id": "https://glottolog.org/resource/languoid/id/sout2856"
}
],
"contentLocation": {
"@id": "https://www.ethnologue.com/country/VU"
}
}{
"@id": "https://www.ethnologue.com/country/VU",
"@type": "Country",
"geojson": {
"@id": "#Vanuatu"
},
"isoA2": "VU",
"isoA3": "VUT",
"name": "Vanuatu"
}{
"@id": "#Vanuatu",
"@type": "GeoShape",
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"name": "Geographical coverage for Vanuatu"
}Identifiers for Objects and Collections MUST be URIs.
Internally, identifiers for all entities that do not have their own URIs MAY use the Archive and Packaging identifier scheme ([ARCP]) - which allows for a DNS-like namespacing of identifiers. For example, for the Sydney Speaks corpus the top-level collection would have the ID:
arcp://name,http://www.dynamicsoflanguage.edu.au/sydney-speaks/corpus/
A sub-corpus (collection) would have an ID like:
arcp://name,http://www.dynamicsoflanguage.edu.au/sydney-speaks/corpus/collection/SSP
An object:
arcp://name,http://www.dynamicsoflanguage.edu.au/sydney-speaks/corpus/object/331
A person:
arcp://name,http://www.dynamicsoflanguage.edu.au/sydney-speaks/corpus/person/54
Some corpora express ages and other demographics of participants - this presents a data modelling challenge, as age and some other variables change over time so if the same person appears over time then we need to have a base Person with DoB etc and then time-based instances of the person with an age, social status, gender etc at that time.
There are three levels at which contributions to an object can be modelled:
-
Include one or more Person items as context in a crate and reference them with properties such as schema:creator or the language-data-commons contribution properties such as ldac:compiler or ldac:depositor. The @id of the person MUST be a URI and SHOULD be re-used where the same person appears in multiple objects in a collection or repository.
-
For longitudinal studies where it is important to record changing demographic information for a Person, or where precision is required in listing contributions to a work use ldac:PersonSnapshot.
-
If it is important to record lots of contributions to a work (e.g. in analysis of a joint work) use schema:Action. If more precision is required in describing the provenance of items - e.g. this work on The Declaration of Rights of Man and of the Citizen (Lorber-Kasunic & Sweetapple).
NOTE: if this approach is used special care will have to be taken in developing user interfaces and/or training communities to use this way of modelling metadata - the user need not see the underlying structure. This profile does not give advice about how to do this as we have not seen a use case that requires it.
Where data is collected from participants in a speech study with elicitation tasks such as "sessions" (see this [IMDI document]](https://www.mpi.nl/ISLE/documents/draft/ISLE_MetaData_2.5.pdf)) or field interviews this can be recorded in metadata via the CollectionEvent class.
The indirection in this conforms-to relationship is to allow multiple objects to have a conformsTo property which indicates that they conform to the same schema while having a local copy of the schema, as per RO-Crate best practice of having all local context to use a data packages in the package where possible.
Himmelmann, Nikolaus P. 2012. Linguistic data types and the interface between language documentation and description. Language documentation & conservation. University of Hawai'i Press 6. 187--207.
Paterson, Hugh Joseph. 2021. Language Archive Records: Interoperability of Referencing Practices and Metadata Models. United States -- North Dakota: The University of North Dakota M.A. https://www.proquest.com/docview/2550236802/abstract/22686A0E508D4E5CPQ/1 (3 May 2022).