Constructing Knowledge Graphs from Data Catalogues

Abstract

We have witnessed about a decade's effort in opening up government institutions around the world by making data about their services, performance and programmes publicly available on open data portals. While these efforts have yielded some economic and social value particularly in the context of city data ecosystems, there is a general acknowledgment that the promises of open data are far from being realised. A major barrier to better exploitation of open data is the difficulty in finding datasets of interests and those of high value on data portals. This article describes how the implicit relatedness and value of datasets can be revealed by generating a knowledge graph over data catalogues. Specifically, we generate a knowledge graph based on a self-organizing map (SOM) constructed from an open data catalogue. Following this, we show how the generated knowledge graph enables value characterisation based on sociometric profiles of the datasets as well as dataset recommendation.

The data set knowledge graph: Creating a linked open data source for data sets

“…The Data Set Knowledge Graph: Creating a Linked Open Data Source for Data Sets (Brickley et al, 2019), (2) (Neumaier et al, 2016), (3) (Ohno-Machado et al, 2017), (4) (Ojo & Sennaike, 2020), (5) (Younsi Dahbi et al, 2020)…”

“…Existing data set knowledge graphs which use data from one source Ojo and Sennaike (2020) propose an approach to constructing a knowledge graph based on metadata of an open data catalogue. The edges between the data sets of the knowledge graph represent the similarity of the data sets.…”