The idea that ambiguity can be productive in data science remains controversial. Efforts to
make scientific publications and data intelligible to computers generally assume that …

What value does semantic data modeling offer? As an information architect or data science
professional, let's say you have an abundance of the right data and the technology to extract …

This paper presents an overview of the LL (O) D and NLP methods, tools and data for
detecting and representing semantic change, with its main application in humanities …

This study investigates the phenomena of semantic drift through the lenses of language and
situated simulation (LASS) and the word frequency effect (WFE) within a timed word …

Graph databases are a straightforward technology for storing knowledge graphs. However,
they are schema-less. We apply the GraphBRAIN Schema (GBS) format to describe Time …

This paper interrogates the informational practices shared between human and computer
machine learners as they train to sense the world through lines of order, or vectors. The …

In this article, we introduce a new framework, the Intensional–Ontological Model (IOM), for
representing meaning, and especially for representing semantic change, in linguistic linked …

In this chapter we aim to investigate semantic change in a scientific concept underpinned by
the evolutionary framework of scientific knowledge production. The aim of this article is …

The paper proposes an interdisciplinary approach including methods from disciplines such
as history of concepts, linguistics, natural language processing (NLP) and Semantic Web, to …

With the increasing availability of wordnets for ancient languages, such as Ancient Greek
and Latin, gaps remain in the coverage of less studied languages of antiquity. This paper …