Making the complete OpenAIRE citation graph easily accessible through compact data representation
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
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| _version_ | 1866913139250954240 |
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| author | Skarding, Joakim Sanda, Pavel |
| author_facet | Skarding, Joakim Sanda, Pavel |
| contents | The OpenAIRE graph contains a large citation graph dataset, with over 200 million publications and over 2 billion citations. The current graph is available as a dump with metadata which, when uncompressed, totals $\sim$2.5 TB. This makes it hard to process on conventional computers. To make this network more accessible for the community, we provide a processed OpenAIRE graph which is downscaled to 16 GB RAM, while preserving the full graph structure. Apart from this we offer the processed data in a very simple format, which allows for further straightforward manipulation. We also provide (1) a Python pipeline, which can be used to process the next releases of the OpenAIRE graph, and (2) a larger version of the dataset including more publication fields such as, the title, list of authors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_12206 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Making the complete OpenAIRE citation graph easily accessible through compact data representation Skarding, Joakim Sanda, Pavel Social and Information Networks Digital Libraries The OpenAIRE graph contains a large citation graph dataset, with over 200 million publications and over 2 billion citations. The current graph is available as a dump with metadata which, when uncompressed, totals $\sim$2.5 TB. This makes it hard to process on conventional computers. To make this network more accessible for the community, we provide a processed OpenAIRE graph which is downscaled to 16 GB RAM, while preserving the full graph structure. Apart from this we offer the processed data in a very simple format, which allows for further straightforward manipulation. We also provide (1) a Python pipeline, which can be used to process the next releases of the OpenAIRE graph, and (2) a larger version of the dataset including more publication fields such as, the title, list of authors. |
| title | Making the complete OpenAIRE citation graph easily accessible through compact data representation |
| topic | Social and Information Networks Digital Libraries |
| url | https://arxiv.org/abs/2602.12206 |