Open Research Knowledge Graph: Next Generation Infrastructure for Semantic Scholarly Knowledge

Jaradeh, Mohamad Yaser; Oelen, Allard; Farfar, Kheir Eddine; Prinz, Manuel; D’Souza, Jennifer; Kismihók, Gábor; Stocker, Markus; Auer, Sören

doi:10.48550/arxiv.1901.10816

Cited by 1 publication

(2 citation statements)

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“…Knowledge graphs have recently seen rapid adoption as a key solution to support several industry-specific applications [39] and research data management use cases including: dataset integration and search at web scale [11], research data integration [29,47] and scholarly data publication [5,23]. Thanks to the increasingly growing fields of knowledge graph embedding [43,48] and graph to text conversion [1], knowledge graphs are also used in the context of recommender systems, question answering and natural language processing (NLP) tasks.…”

Section: Knowledge Graphs For Research Data Managementmentioning

confidence: 99%

“…Consequently, the system enables resource identifiers to be shortened and compacted by means of aliases and prefix mappings defined in the project's configuration. All resource types except files have a JSON-LD 29 representation format. Files have a dual representation accessible through content negotiation: a JSON-LD representation for metadata such as file name and size and a binary representation for the actual file content.…”

Section: Resource-centric Restful Apimentioning

confidence: 99%

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Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Roman

Kerrien

et al. 2023

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Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simulating the whole rodent brain in the Swiss EPFL Blue Brain Project (BBP) required a solution to managing large-scale highly heterogeneous data, and tracking their provenance to ensure quality, reproducibility and attribution throughout these iterative cycles. Here, we describe Blue Brain Nexus (BBN), an ecosystem of open source, domain agnostic, scalable, extensible data and knowledge graph management systems built by BBP to address these challenges. BBN builds on open standards and interoperable semantic web technologies to enable the creation and management of secure RDF-based knowledge graphs validated by W3C SHACL. BBN supports a spectrum of (meta)data modeling and representation formats including JSON and JSON-LD as well as more formally specified SHACL-based schemas enabling domain model-driven runtime API. With its streaming event-based architecture, BBN supports asynchronous building and maintenance of multiple extensible indices to ensure high performance search capabilities and enable analytics. We present four use cases and applications of BBN to large-scale data integration and dissemination challenges in computational modeling, neuroscience, psychiatry and open linked data.

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