Linguistic Linked Open Data


In natural language processing, linguistics, and neighboring fields, Linguistic Linked Open Data describes a method and an interdisciplinary community concerned with creating, sharing, and using language resources in accordance with Linked Data principles. The Linguistic Linked Open Data Cloud was conceived and is being maintained by the Open Linguistics Working Group of the Open Knowledge Foundation, but has been a point of focal activity for several W3C community groups, research projects, and infrastructure efforts since then.

Definition and Development

Linguistic Linked Open Data describes the publication of data for linguistics and natural language processing using the following principles:
The primary benefits of LLOD have been identified as:
The home of the LLOD cloud diagram is under linguistic-lod.org

LLOD vocabularies

Aside from gathering metadata and generating the LLOD cloud diagram, the LLOD community is driving the development of community standards with respect to vocabularies, metadata and best practice recommendations.
According to the state-of-the-art overview by Cimiano et al., these include:
As of mid-2020, most of these community standards are actively worked on. Particularly problematic is the existence of multiple incompatible standards for linguistic annotations, and in early 2020, the W3C Community Group Linked Data for Language Technology has begun to work towards a consolidation of these vocabularies for linguistic annotations on the web.

Community

The LLOD cloud diagram has been developed and is maintained by the Open Linguistics Working Group of the Open Knowledge Foundation, an open and interdisciplinary of experts in language resources.
The OWLG organizes community events and coordinates LLOD developments and facilitates interdisciplinary communication between and among LLOD contributors and users.
Several W3C Business and Community Groups focus on specialized aspects of LLOD:
LLOD development is driven forward by and documented in a series of international workshops, datathons, and associated publications. Among others, these include
Linguistic Linked Open Data is applied to address a number of scientific research problems:
Linguistic Linked Open Data is closely related with the development of
Uses and development of LLOD have been subject to several large-scale research projects, including
As of October 2018, the 10 most frequently linked resources in the LLOD diagram are :
There are a number of recurring discussions regarding the applicability and use of the term to a particular type of resources.

Linguistic Data: Scope and Classification

Aside from resources used in and created for linguistic research, the LLOD cloud diagram also includes ontologies, terminologies and general knowledge bases whose development was not originally driven by interest in language sciences or language technology, e.g., the DBpedia. As a criterion for inclusion into the LLOD diagram, the OWLG requires "linguistic relevance": " dataset is linguistically relevant if it provides or describes language data that can be used for the purpose of linguistic research or natural language processing." This does include linguistic resources in a strict sense, but also resources "that can be used for annotating, enriching, retrieving or classifying language resources... can be verified by the existence of links between a resource and resources fulfilling condition ".
A related issue is the classification of linguistically relevant datasets. The OWLG developed the following classification for the LLOD cloud diagram:
Note that in this classification, term bases are at the fringes of linguistic relevance, as these are normally created for purposes other than language technology or linguistic research.

Open Data: Availability

LLOD is defined in relation to Linked Open Data, and LLOD resources should thus conform to licenses in accordance with the Open Definition. For generating the LLOD cloud diagram, this does, however, not seem to be enforced yet, so that the technical criterion is availability over the web and a metadata entry. In the OWLG, it has been repeatedly discussed whether non-commercial resources could be included with a general consensus of admitting them for the moment but subsequently enforcing stricter requirements along with the growth of the LLOD cloud. As of January 2018, it was not agreed upon yet when this move was about to happen. As of January 2020, machine-readable license metadata was available for 86 LLOD resources, of these, 82 adopted open licenses, 4 adopted non-commercial licenses.
In a broader sense, the term LLOD technology can also used to refer to the technology independently from whether actually open resources are involved, e.g., in the name of the EU project Pret-a-LLOD that features several commercial business cases. This is justified for applications that consume open data, but moreover, also when linked data technology and the adoptation of other LLOD conventions are applied in order to facilitates the seamless integration of LLOD resources.
The abbreviation "LLOD" can be used to refer to either LLOD technology and LLOD resources. For disambiguation, the terms "LLOD resources" and "LLOD technology" can be used. For emphasizing application or applicability to non-open resources, also "LLD" has been used. A possible compromise is the acronym "LLD" for the technology. A "Licensed Linguistic Linked Data" cloud that contains non-open resources does currently not exist.

Linked Data: Formats

The definition of Linked Data requires the application of RDF or related standards. This includes the W3C recommendations SPARQL, Turtle, JSON-LD, RDF-XM, RDFa, etc. In language technology and the language sciences, however, other formalisms are currently more popular, and the inclusion of such data into the LLOD cloud diagram has been occasionally requested. For several such languages, W3C-standardized wrapping mechanisms exist, but according to the current definition of Linked Data only the generated data would qualify for LLOD cloud inclusion, not the source data.

Selected literature

An exhaustive description on the state of the art on LLOD is provided by
The concept of a Linguistic Linked Open Data cloud has been originally introduced by
The first book on the topic is
According to Cimiano et al., other seminal publications since then include
Developments from 2015 to 2019 are summarized in the collected volume by