activity
20192022
most citedUsing Mapping Languages for Building Legal Knowledge Graphs from XML Files

6 citations · 7 across the 7 of their papers we have counts for

collaborators
Showing cs.DBShow all

7 papers · 1 filter

cs.DB2022

Link Climate: An Interoperable Knowledge Graph Platform for Climate Data

Jiantao Wu, Fabrizio Orlandi, Declan O'Sullivan +1

Climate science has become more ambitious in recent years as global awareness about the environment has grown. To better understand climate, historical climate (e.g. archived meteo…

cs.DB2021

Automated Climate Analyses Using Knowledge Graph

Jiantao Wu, Huan Chen, Fabrizio Orlandi +3

The FAIR (Findable, Accessible, Interoperable, Reusable) data principles are fundamental for climate researchers and all stakeholders in the current digital ecosystem. In this pape…

cs.DB2021

An Interoperable Open Data Portal for Climate Analysis

Jiantao Wu, Huan Chen, Fabrizio Orlandi +3

This work proposes an open interoperable data portal that offers access to a Web-wide climate domain knowledge graph created for Ireland and England's NOAA climate daily data. Ther…

cs.DB2021

Ontology Modeling for Decentralized Household Energy Systems

Jiantao Wu, Fabrizio Orlandi, Tarek AlSkaif +2

In a decentralized household energy system consisting of various devices such as washing machines, heat pumps, and solar panels, understanding the electric energy consumption and p…

cs.DB20211 cited

An Ontology Model for Climatic Data Analysis

Jiantao Wu, Fabrizio Orlandi, Declan O'Sullivan +1

Recently ontologies have been exploited in a wide range of research areas for data modeling and data management. They greatly assists in defining the semantic model of the underlyi…

cs.DB20196 cited

Using Mapping Languages for Building Legal Knowledge Graphs from XML Files

Ademar Crotti Junior, Fabrizio Orlandi, Declan O'Sullivan +2

This paper presents our experience on building RDF knowledge graphs for an industrial use case in the legal domain. The information contained in legal information systems are often…