  Web and artificial intelligence technologies, especially semantic web and
knowledge graph (KG), have recently raised significant attention in educational
scenarios. Nevertheless, subject-specific KGs for K-12 education still lack
sufficiency and sustainability from knowledge and data perspectives. To tackle
these issues, we propose EDUKG, a heterogeneous sustainable K-12 Educational
Knowledge Graph. We first design an interdisciplinary and fine-grained ontology
for uniformly modeling knowledge and resource in K-12 education, where we
define 635 classes, 445 object properties, and 1314 datatype properties in
total. Guided by this ontology, we propose a flexible methodology for
interactively extracting factual knowledge from textbooks. Furthermore, we
establish a general mechanism based on our proposed generalized entity linking
system for EDUKG's sustainable maintenance, which can dynamically index
numerous heterogeneous resources and data with knowledge topics in EDUKG. We
further evaluate EDUKG to illustrate its sufficiency, richness, and
variability. We publish EDUKG with more than 252 million entities and 3.86
billion triplets. Our code and data repository is now available at
https://github.com/THU-KEG/EDUKG.
