Knowledge Graphs Evolution and Preservation -- A Technical Report from
ISWS 2019
- URL: http://arxiv.org/abs/2012.11936v1
- Date: Tue, 22 Dec 2020 11:21:09 GMT
- Title: Knowledge Graphs Evolution and Preservation -- A Technical Report from
ISWS 2019
- Authors: Nacira Abbas, Kholoud Alghamdi, Mortaza Alinam, Francesca Alloatti,
Glenda Amaral, Claudia d'Amato, Luigi Asprino, Martin Beno, Felix Bensmann,
Russa Biswas, Ling Cai, Riley Capshaw, Valentina Anita Carriero, Irene
Celino, Amine Dadoun, Stefano De Giorgis, Harm Delva, John Domingue, Michel
Dumontier, Vincent Emonet, Marieke van Erp, Paola Espinoza Arias, Omaima
Fallatah, Sebasti\'an Ferrada, Marc Gallofr\'e Oca\~na, Michalis Georgiou,
Genet Asefa Gesese, Frances Gillis-Webber, Francesca Giovannetti, Mar\`ia
Granados Buey, Ismail Harrando, Ivan Heibi, Vitor Horta, Laurine Huber,
Federico Igne, Mohamad Yaser Jaradeh, Neha Keshan, Aneta Koleva, Bilal
Koteich, Kabul Kurniawan, Mengya Liu, Chuangtao Ma, Lientje Maas, Martin
Mansfield, Fabio Mariani, Eleonora Marzi, Sepideh Mesbah, Maheshkumar Mistry,
Alba Catalina Morales Tirado, Anna Nguyen, Viet Bach Nguyen, Allard Oelen,
Valentina Pasqual, Heiko Paulheim, Axel Polleres, Margherita Porena, Jan
Portisch, Valentina Presutti, Kader Pustu-Iren, Ariam Rivas Mendez, Soheil
Roshankish, Sebastian Rudolph, Harald Sack, Ahmad Sakor, Jaime Salas, Thomas
Schleider, Meilin Shi, Gianmarco Spinaci, Chang Sun, Tabea Tietz, Molka
Tounsi Dhouib, Alessandro Umbrico, Wouter van den Berg, Weiqin Xu
- Abstract summary: One of the most neglected FAIR issues about Knowledge Graphs 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.
This document reports a collaborative effort performed by 9 teams of students.
- Score: 34.67467325805731
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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.
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