Linguistic Linked Open Data

In natural language processing, linguistics, and neighboring fields, Linguistic Linked Open Data (LLOD) describes a method and an interdisciplinary community concerned with creating, sharing, and (re-)using language resources in accordance with Linked Data principles.

According to the state-of-the-art overview by Cimiano et al. (2020),[4] these include: As of mid-2020, most of these community standards are actively worked on.

The OWLG developed the following classification for the LLOD cloud diagram:[35] Note that in this classification, term bases might be slightly different in that they do not provide grammatical information, however, since they formalize semantic knowledge, they are of immanent relevance for natural language processing tasks, such as named entity recognition or anaphora resolution.

In the OWLG, it has been repeatedly discussed whether non-commercial (academic) resources could be included with a general consensus of admitting them for the moment (2015) but subsequently enforcing stricter requirements along with the growth of the LLOD cloud.

A "Licensed Linguistic Linked Data" cloud that contains non-open resources does currently (June 2020) not exist.

A 2022 review paper is: 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. (2020),[41] other seminal publications since then include Developments from 2015 to 2019 are summarized in the collected volume by