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ILastic: Linked Data Generation Workflow and User Interface for iMinds Scholarly Data
[chapter]
2018
Lecture Notes in Computer Science
Enriching scholarly data with metadata enhances the publications' meaning. Unfortunately, different publishers of overlapping or complementary scholarly data neglect general-purpose solutions for metadata and instead use their own ad-hoc solutions. This leads to duplicate efforts and entails non-negligible implementation and maintenance costs. In this paper, we propose a reusable Linked Data publishing workflow that can be easily adjusted by different data owners to (i) generate and publish
doi:10.1007/978-3-030-01379-0_2
fatcat:kto4cn7udff2neo2azuhpdru7a