Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019
Abstract
One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of entities. [...] This grand challenge extends this further by asking if we can create a knowledge graph of "everything" ranging from common sense concepts to location based entities. This knowledge graph should be "open to the public" in a FAIR manner democratizing this mass amount of knowledge." Although linked open data (LOD) is one knowledge graph, it is the closest realisation (and probably the only one) to a public FAIR Knowledge Graph (KG) of everything. Surely, LOD provides a unique testbed for experimenting and evaluating research hypotheses on open and FAIR KG. One of the most neglected FAIR issues about KGs is their ongoing evolution and long term preservation. We want to investigate this problem, that is to understand what preserving and supporting the evolution of KGs means and how these problems can be addressed. Clearly, the problem can be approached from different perspectives and may require the development of different approaches, including new theories, ontologies, metrics, strategies, procedures, etc. This document reports a collaborative effort performed by 9 teams of students, each guided by a senior researcher as their mentor, attending the International Semantic Web Research School (ISWS 2019). Each team provides a different perspective to the problem of knowledge graph evolution substantiated by a set of research questions as the main subject of their investigation. In addition, they provide their working definition for KG preservation and evolution.
Keywords
Cite
@article{arxiv.2012.11936,
title = {Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019},
author = {Nacira Abbas and Kholoud Alghamdi and Mortaza Alinam and Francesca Alloatti and Glenda Amaral and Claudia d'Amato and Luigi Asprino and Martin Beno and Felix Bensmann and Russa Biswas and Ling Cai and Riley Capshaw and Valentina Anita Carriero and Irene Celino and Amine Dadoun and Stefano De Giorgis and Harm Delva and John Domingue and Michel Dumontier and Vincent Emonet and Marieke van Erp and Paola Espinoza Arias and Omaima Fallatah and Sebastián Ferrada and Marc Gallofré Ocaña and Michalis Georgiou and Genet Asefa Gesese and Frances Gillis-Webber and Francesca Giovannetti and Marìa Granados Buey and Ismail Harrando and Ivan Heibi and Vitor Horta and Laurine Huber and Federico Igne and Mohamad Yaser Jaradeh and Neha Keshan and Aneta Koleva and Bilal Koteich and Kabul Kurniawan and Mengya Liu and Chuangtao Ma and Lientje Maas and Martin Mansfield and Fabio Mariani and Eleonora Marzi and Sepideh Mesbah and Maheshkumar Mistry and Alba Catalina Morales Tirado and Anna Nguyen and Viet Bach Nguyen and Allard Oelen and Valentina Pasqual and Heiko Paulheim and Axel Polleres and Margherita Porena and Jan Portisch and Valentina Presutti and Kader Pustu-Iren and Ariam Rivas Mendez and Soheil Roshankish and Sebastian Rudolph and Harald Sack and Ahmad Sakor and Jaime Salas and Thomas Schleider and Meilin Shi and Gianmarco Spinaci and Chang Sun and Tabea Tietz and Molka Tounsi Dhouib and Alessandro Umbrico and Wouter van den Berg and Weiqin Xu},
journal= {arXiv preprint arXiv:2012.11936},
year = {2020}
}