Complexity and Expressiveness of ShEx for RDF
Angela Bonifati, Anastasia Dimou, Stefania Dumbrava, George Fletcher, Katja Hose, George Ath Konstantinidis, José Emilio Labra Gayo, Wim Martens, Nina Pardal, Liat Peterfreund, Katherine Thornton, María-Esther Vidal, Hannes Voigt · arXiv (Cornell University) · 2015
Graph data abstractions are often assumed to be intuitive, but experience shows that they are not equally understandable or usable in practice. In this vision and challenges paper, we examine the human-centricity of contemporary graph data abstractions through four lenses: researchability, usability, teachability, and societal impact. Drawing on diverse real-world use cases, ranging from clinical data and collaborative knowledge bases to biological and pangenomic graphs, we distill insights from database research, human-computer interaction, and education. Based on this analysis, we identify open research challenges that must be addressed to make graph abstractions easier to study, use, learn, and reason about.