Showing posts with label Linked data. Show all posts
Showing posts with label Linked data. Show all posts

Tuesday, March 4, 2025

Kerameikos.org: defining the intellectual concepts of pottery

[First posted in AWOL 20 October 2014, updated 4 March 2025]

Kerameikos.org
Kerameikos.org is a collaborative project dedicated to defining the intellectual concepts of pottery following the tenets of linked open data and the formulation of an ontology for representing and sharing ceramic data across disparate data systems. While the project is focused primarily on the definition of concepts within Greek black- and red-figure pottery, Kerameikos.org is extensible toward the definition of concepts in other fields of pottery studies.
See the github account at https://github.com/kerameikos, which contains repositories for the RDF data and the publication framework. This framework could be applied to other linked data thesauri.

Kerameikos Linked Data

 

Wednesday, March 6, 2019

LiLa: Linking Latin: Building a Knowledge Base of Linguistic Resources for Latin

LiLa: Linking Latin: Building a Knowledge Base of Linguistic Resources for Latin
LiLa: Linking Latin
Despite the headway made in the last decade in building, sharing and exploiting linguistic resources and tools for the automatic processing of Latin, these remain incompatible.
The objective of LiLa (2018-2023) is to connect and ultimately exploit the wealth of linguistic resources and NLP tools for Latin created so far, in order to bridge the gap between raw language data, NLP and knowledge descriptions. To do so, LiLa is building an open-ended Knowledge Base using the Linked Data paradigm, concurrently adding Latin to the multilingual Linguistic Linked Open Data (LLOD) cloud.
Read more →

Tuesday, July 28, 2015

Nature.com Ontologies

Nature.com Ontologies
This site describes the RDF ontologies used by Macmillan Science and Education for content publishing. We are sharing these in order to contribute to the wider linked data community and to provide a public reference for our data models.
Model Extents Diagram
Our aims at Macmillan Science and Education in embracing linked data technologies are:
  • To provide a superior content discovery experience for our audience and to facilitate emergent behaviours and interactions
  • To evolve a data model which is highly responsive to new and legacy business needs and can drive an in-flight publishing operation