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We present SemOpenAlex, an extensive RDF knowledge graph that contains over 26 billion triples about scientific publications and their associated entities, such as authors, institutions, journals, and concepts.
Linked Data – Design Issues (July 2006) https://www.w3.org/DesignIssues/LinkedData.html
Berners-Lee, T.: · 2006
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SwetoDblp ontology of Computer Science publications
Aleman-Meza, B., Hakimpour, F., Budak Arpinar, I., Sheth, A.P.: · 2007
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Translating Embeddings for Modeling Multi-Relational Data
Bordes, A., Usunier, N., Garcia-Durán, A., Weston, J., Yakhnenko, O.: · 2013
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Five stars of Linked Data vocabulary use
Janowicz, K., Hitzler, P., Adams, B., Kolas, D., Vardeman, C.: · 2014
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Embedding Entities and Relations for Learning and Inference in Knowledge Bases
Yang, B., Yih, W.t., He, X., Gao, J., Deng, L.: · 2014
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University rankings and social science
Marginson, S.: · 2014
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Do Nobel Laureates Create Prize-Winning Networks? An Analysis of Collaborative Research in Physiology or Medicine
Wagner, C.S., Horlings, E., Whetsell, T.A., Mattsson, P., Nordqvist, K.: · 2015
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Setting our bibliographic references free: towards open citation data
Peroni, S., Dutton, A., Gray, T., Shotton, D.: · 2015
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An Overview of Microsoft Academic Service (MAS) and Applications
Sinha, A., Shen, Z., Song, Y., Ma, H., Eide, D., Hsu, B.J.P., Wang, K.: · 2015
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An Overview of Microsoft Academic Service (MAS) and Applications
Sinha, A., Shen, Z., Song, Y., Ma, H., Eide, D., Hsu, B.P., Wang, K.: · 2015
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The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J., et al.: · 2016
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An Analysis of the Microsoft Academic Graph
Herrmannova, D., Knoth, P.: · 2016
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Complex Embeddings for Simple Link Prediction (June 2016)
Trouillon, T., Welbl, J., Riedel, S., Gaussier, E., Bouchard, G.: · 2016
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Current state of Linked Data in digital libraries
Carrasco, M.H., Luján-Mora, S., Maté, A., Trujillo, J.: · 2016
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Research performance based funding systems: A comparative assessment
Jonkers, K., Zacharewicz, T., et al.: · 2016
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Veličković, P., Cucurull, G., Casanova, A., Romero, A., Liò, P., Bengio, Y.: · 2017
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Towards a Knowledge Graph Representing Research Findings by Semantifying Survey Articles
Fathalla, S., Vahdati, S., Auer, S., Lange, C.: · 2017
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Towards a Knowledge Graph for Science
Auer, S., Kovtun, V., Prinz, M., Kasprzik, A., Stocker, M., Vidal, M.E.: · 2018
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AceKG: A Large-scale Knowledge Graph for Academic Data Mining
Wang, R., Yan, Y., Wang, J., Jia, Y., Zhang, Y., Zhang, W., Wang, X.: · 2018
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The SPAR ontologies
Peroni, S., Shotton, D.: · 2018
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Inductive Representation Learning on Large Graphs (September 2018) arXiv:1706.02216
Hamilton, W.L., Ying, R., Leskovec, J.: · 2018
Cited alongside, same era.
Smart Papers: Dynamic Publications on the Blockchain
Hoffman, M.R., Ibáñez, L.D., Fryer, H., Simperl, E.: · 2018
Cited alongside, same era.
Prost: Distributed execution of SPARQL queries using mixed partitioning strategies
Cossu, M., Färber, M., Lausen, G.: · 2018
Cited alongside, same era.
The Microsoft Academic Knowledge Graph: A Linked Data Source with 8 Billion Triples of Scholarly Data
Färber, M.: · 2019
Cited alongside, same era.
Open Research Knowledge Graph: Next Generation Infrastructure for Semantic Scholarly Knowledge
Jaradeh, M.Y., Oelen, A., Farfar, K.E., Prinz, M., D’Souza, J., Kismihók, G., Stocker, M., Auer, S.: · 2019
Cited alongside, same era.
Goodbye, Microsoft Academic – Hello, open research infrastructure? (May 2021) https://blogs.lse.ac.uk/impactofsocialsciences/2021/05/27/goodbye-microsoft-academic-hello-open-research-infrastructure/
Tay, A., Martín-Martín, A., Hug, S.E.: · 2021
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AIDA: A knowledge graph about research dynamics in academia and industry
Angioni, S., Salatino, A., Osborne, F., Recupero, D.R., Motta, E.: · 2021
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The data set knowledge graph: Creating a linked open data source for data sets
Färber, M., Lamprecht, D.: · 2021
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Identifying Used Methods and Datasets in Scientific Publications
Färber, M., Albers, A., Schüber, F.: · 2021
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Wikibase as an Infrastructure for Knowledge Graphs: The EU Knowledge Graph
Diefenbach, D., Wilde, M.D., Alipio, S.: · 2021
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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metaphactory: A platform for knowledge graph management
Haase, P., Herzig, D.M., Kozlov, A., Nikolov, A., Trame, J.: · 2019
Cited alongside, same era.
ScholarSight: Visualizing Temporal Trends of Scientific Concepts
Färber, M., Nishioka, C., Jatowt, A.: · 2019
Cited alongside, same era.
Open Research Knowledge Graph: Towards Machine Actionability in Scholarly Communication
Jaradeh, M.Y., Auer, S., Prinz, M., Kovtun, V., Kismihók, G., Stocker, M.: · 2019
Cited alongside, same era.
OpenCitations, an infrastructure organization for open scholarship
Peroni, S., Shotton, D.: · 2020
Cited alongside, same era.
Special issue on bibliographic data sources
Waltman, L., Larivière, V.: · 2020
Cited alongside, same era.
A Glimpse of the First Eight Months of the COVID-19 Literature on Microsoft Academic Graph: Themes, Citation Contexts, and Uncertainties
Chen, C.: · 2020
Cited alongside, same era.
Microsoft Academic Graph: When experts are not enough
Wang, K., Shen, Z., Huang, C., Wu, C.H., Dong, Y., Kanakia, A.: · 2020
Cited alongside, same era.
Flexible and Extensible Competency Management with Knowledge Graphs
Heist, N., Haase, P.: · 2021
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OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts
Priem, J., Piwowar, H., Orr, R.: · 2022
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Wissenschaftliche Literatur entdecken: Was bibliothekarische Discovery-Systeme von der Konkurrenz lernen und was sie ihr zeigen können
Christensen, A.: · 2022
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WDQS Backend Alternatives Working Paper (2022) Version 1.1, 29 March 2022. Wikimedia Foundation, San Franciscio, CA, USA. https://www.wikidata.org/wiki/File:WDQS_Backend_Alternatives_working_paper.pdf
WDQS Search Team: · 2022
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Towards transdisciplinary impact of scientific publications: A longitudinal, comprehensive, and large-scale analysis on Microsoft Academic Graph
Huang, Y., Lu, W., Liu, J., Cheng, Q., Bu, Y.: · 2022
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OpenAIRE Research Graph Dump (June 2022) Version Number: 4.1 https://doi.org/10.5281/zenodo.6616871
Manghi, P., Atzori, C., Bardi, A., Baglioni, M., Schirrwagen, J., Dimitropoulos, H., La Bruzzo, S., Foufoulas, I., Mannocci, A., Horst, M., Czerniak, A., Kiatropoulou, K., Kokogiannaki, A., De Bonis, M., Artini, M., Ottonello, E., Lempesis, A., Ioannidis, A., Manola, N., Principe, P.: · 2022
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The Microsoft Academic Knowledge Graph enhanced: Author name disambiguation, publication classification, and embeddings
Färber, M., Ao, L.: · 2022
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MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks (2022)
Waleffe, R., Mohoney, J., Rekatsinas, T., Venkataraman, S.: · 2022
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The Green AI Ontology: An Ontology for Modeling the Energy Consumption of AI Models
Färber, M., Lamprecht, D.: · 2022
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A multi-domain benchmark for personalized search evaluation
Bassani, E., Kasela, P., Raganato, A., Pasi, G.: · 2022
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Effectiveness of research grants funded by European Research Council and Polish National Science Centre
Dzieżyc, M., Kazienko, P.: · 2022
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Towards innograph: A knowledge graph for ai innovation
Massri, M.B., Spahiu, B., Grobelnik, M., Alexiev, V., Palmonari, M., Roman, D.: · 2023
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S2abEL: A Dataset for Entity Linking from Scientific Tables
Lou, Y., Kuehl, B., Bransom, E., Feldman, S., Naik, A., Downey, D.: · 2023
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unarxive 2022: All arxiv publications pre-processed for nlp, including structured full-text and citation network
Saier, T., Krause, J., Färber, M.: · 2023
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