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| # IDCite: A Large-Scale Multidisciplinary Citation Intent Dataset for Scholarly Knowledge Discovery |
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| ## Dataset Description |
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| IDCite is a large-scale multidisciplinary dataset of citation contexts and citation intents spanning 21 Essential Science Indicators (ESI) fields. |
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| The dataset contains citation records linking citing papers and highly cited seed papers, enriched with citation contexts, citation-intent annotations, publication metadata, disciplinary information, and normalized scholarly entities. A supplementary knowledge graph representation is additionally provided for graph-based analysis. |
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| The dataset is intended to support research on: |
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| * Citation context analysis |
| * Citation intent analysis |
| * Scientometric and bibliometric research |
| * Scholarly information retrieval |
| * Citation recommendation |
| * Research assessment |
| * Cross-disciplinary citation analysis |
| * Knowledge graph analytics |
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| ## Zenodo Repository and Documentation |
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| The official archived Version 3 release of IDCite is available on Zenodo: |
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| **IDCite: A Large-Scale Multidisciplinary Citation Intent Dataset for Scholarly Knowledge Discovery (Version 3)** |
| DOI: [10.5281/zenodo.20796923](https://doi.org/10.5281/zenodo.20796923) |
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| For a detailed description of the dataset design, release lineage, construction pipeline, data sources, schema definitions, multidisciplinary sampling strategy, citation-intent representation, knowledge graph structure, technical validation, reproducibility considerations, and the relationship between IDCite and CitationHub, please refer to the accompanying documentation: |
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| **`IDCite_Project_and_Dataset_Documentation_Seohyun_Nam.pdf`** |
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| The documentation is included in the Zenodo Version 3 release and serves as the primary reference for understanding the structure, scope, provenance, and recommended use of IDCite. |
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| --- |
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| # Dataset Summary |
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| | File | Rows | Columns | Description | |
| | -------------------------------------- | --------: | ------: | -------------------------------------------------------------------------------------- | |
| | `citation_events.parquet` | 1,857,503 | 20 | Raw citation event records | |
| | `citation_events_enriched.parquet` | 1,857,503 | 32 | Citation events enriched with cited seed paper metadata | |
| | `citation_events_normalized.parquet` | 1,857,503 | 23 | Citation events with normalized intent and field identifiers | |
| | `citing_papers.parquet` | 1,467,045 | 7 | Metadata of citing papers | |
| | `citing_papers_normalized.parquet` | 1,467,045 | 8 | Citing papers with normalized journal IDs | |
| | `seed_cited_papers.parquet` | 23,479 | 42 | Highly cited seed paper metadata | |
| | `seed_cited_papers_normalized.parquet` | 23,479 | 48 | Seed papers with normalized journal, author, affiliation, city, country, and field IDs | |
| | `kg_edges.parquet` | 6,855,117 | 3 | Heterogeneous knowledge graph edges | |
| | `kg_nodes.parquet` | 3,418,433 | 14 | Heterogeneous knowledge graph nodes | |
| | `authors.parquet` | 16,839 | 2 | Author ID-name mapping | |
| | `affiliations.parquet` | 5,271 | 2 | Affiliation ID-name mapping | |
| | `affiliation_geo.parquet` | 5,352 | 6 | Affiliation, city, and country mappings | |
| | `journals.parquet` | 46,237 | 2 | Journal ID-name mapping | |
| | `fields.parquet` | 21 | 3 | Field ID-name mapping | |
| | `intents.parquet` | 31 | 2 | Citation intent ID-name mapping | |
| | `cities.parquet` | 1,899 | 2 | City ID-name mapping | |
| | `countries.parquet` | 108 | 2 | Country ID-name mapping | |
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| --- |
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| ## Representative Schema Definitions |
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| The following table summarizes the representative schema of the primary IDCite tables. Only the main analytical and relational fields are shown here for readability; individual files may contain additional metadata and provenance fields. |
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| | Table | Representative Columns | |
| | --- | --- | |
| | `citation_events.parquet` | `citation_event_id`, `citing_paper_id`, `cited_seed_paper_id`, `citing_doi`, `citing_title`, `citing_year`, `citing_venue`, `primary_intent`, `context_count`, `intent_count`, `source_file` | |
| | `citation_events_enriched.parquet` | `citation_event_id`, `cited_title`, `cited_publication_name`, `cited_creator`, `cited_affiliation_country`, `cited_group`, `cited_category`, `cited_journal_clarivate`, `cited_citedby_count` | |
| | `citation_events_normalized.parquet` | `citation_event_id`, `citing_paper_id`, `cited_seed_paper_id`, `primary_intent`, `field_id`, `category_id`, `normalized_intent`, `source_file` | |
| | `seed_cited_papers.parquet` | `seed_paper_id`, `doi`, `title`, `publication_name`, `creator`, `citedby_count`, `affilname`, `affiliation_country`, `authkeywords`, `fund_sponsor`, `group`, `category` | |
| | `seed_cited_papers_normalized.parquet` | `seed_paper_id`, `doi`, `title`, `publication_name`, `creator`, `citedby_count`, `affiliation_id`, `journal_id`, `field_id`, `category_id` | |
| | `citing_papers.parquet` | `citing_paper_id`, `doi`, `title`, `year`, `venue`, `oa_pdf` | |
| | `citing_papers_normalized.parquet` | `citing_paper_id`, `doi`, `title`, `year`, `venue`, `journal_id`, `field_id` | |
| | `authors.parquet` | `author_id`, `author_name` | |
| | `affiliations.parquet` | `affiliation_id`, `affiliation_name` | |
| | `affiliation_geo.parquet` | `affiliation_id`, `city_id`, `country_id`, `latitude`, `longitude` | |
| | `cities.parquet` | `city_id`, `city_name` | |
| | `countries.parquet` | `country_id`, `country_name` | |
| | `journals.parquet` | `journal_id`, `journal_name` | |
| | `fields.parquet` | `field_id`, `field_name`, `category_raw` | |
| | `intents.parquet` | `intent_id`, `intent_name` | |
| | `kg_nodes.parquet` | `node_id`, `label`, `doi`, `publication_name`, `group`, `citedby_count`, `node_type`, `venue`, `year`, `primary_intent` | |
| | `kg_edges.parquet` | `source`, `target`, `edge_type` | |
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| The schema is designed to support both direct tabular analysis and relational or graph-based workflows. Stable normalized identifiers such as `journal_id`, `affiliation_id`, `field_id`, and `intent_id` allow records to be joined across the released tables, while `citation_event_id`, `citing_paper_id`, and `cited_seed_paper_id` preserve the relationships between citation events and scholarly publications. |
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| The `kg_nodes.parquet` and `kg_edges.parquet` files provide a supplementary graph representation derived from these normalized entities and relationships. |
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| --- |
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| # Citation Events |
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| The main citation event files contain paper-level citation relations and citation semantics. |
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| Important fields include: |
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| | Field | Description | |
| | ----------------------- | ----------------------------------------------------------- | |
| | `citation_event_id` | Unique citation event identifier | |
| | `citing_paper_id` | Identifier of the citing paper | |
| | `cited_seed_paper_id` | Identifier of the cited seed paper | |
| | `citing_doi` | DOI of the citing paper | |
| | `citing_title` | Title of the citing paper | |
| | `citing_year` | Publication year of the citing paper | |
| | `citing_venue` | Venue of the citing paper | |
| | `primary_intent` | Primary citation intent label | |
| | `all_intents` | List of citation intents associated with the citation event | |
| | `contexts` | Citation context text snippets | |
| | `context_count` | Number of citation contexts | |
| | `intent_count` | Number of intent annotations | |
| | `is_influential` | Whether the citation is marked as influential | |
| | `has_semantic_evidence` | Whether semantic evidence is available | |
| | `field_id` | Normalized field identifier | |
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| --- |
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| # Seed Cited Papers |
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| Seed papers represent highly cited papers used as cited targets. |
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| Important fields include: |
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| | Field | Description | |
| | ------------------- | ----------------------------------------------------------------- | |
| | `seed_paper_id` | Unique seed paper identifier | |
| | `doi` | DOI of the seed paper | |
| | `title` | Title of the seed paper | |
| | `publication_name` | Publication venue | |
| | `creator` | Main creator or first author | |
| | `citedby_count` | Citation count | |
| | `group` | Broad research group | |
| | `category` | Research category | |
| | `journal_clarivate` | Clarivate journal name | |
| | `is_seed_top5pct` | Whether the seed paper belongs to the selected highly cited group | |
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| --- |
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| # Knowledge Graph |
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| The dataset includes a heterogeneous scholarly knowledge graph. |
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| ## kg_nodes.parquet |
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| | Field | Description | |
| | ------------------ | ---------------------------------------- | |
| | `node_id` | Unique node identifier | |
| | `label` | Human-readable node label | |
| | `node_type` | Type of node | |
| | `doi` | DOI if the node corresponds to a paper | |
| | `publication_name` | Publication venue | |
| | `group` | Research group | |
| | `citedby_count` | Citation count | |
| | `venue` | Venue information | |
| | `year` | Publication year | |
| | `primary_intent` | Citation intent for citation-event nodes | |
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| ## kg_edges.parquet |
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| | Field | Description | |
| | ----------- | ---------------------- | |
| | `source` | Source node ID | |
| | `target` | Target node ID | |
| | `edge_type` | Type of graph relation | |
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| --- |
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| # Intended Uses |
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| This dataset can be used for: |
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| 1. Citation context analysis |
| 2. Citation intent classification |
| 3. Scientometric and bibliometric research |
| 4. Scholarly information retrieval |
| 5. Citation recommendation |
| 6. Research assessment |
| 7. Cross-disciplinary citation analysis |
| 8. Knowledge graph analytics and network analysis |
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| --- |
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| # Dataset Construction |
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| The dataset was constructed by integrating: |
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| 1. Citation event records |
| 2. Citation contexts and citation intent labels |
| 3. Highly cited seed paper metadata |
| 4. Citing paper metadata |
| 5. Journal, author, affiliation, city, country, and field normalization tables |
| 6. Heterogeneous scholarly knowledge graph nodes and edges |
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| The normalized files provide ID-based mappings for relational and graph-based experiments. |
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| --- |
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| # Dataset Structure |
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| ```text |
| IDCite/ |
| ├── affiliation_geo.parquet |
| ├── affiliations.parquet |
| ├── authors.parquet |
| ├── citation_events.parquet |
| ├── citation_events_enriched.parquet |
| ├── citation_events_normalized.parquet |
| ├── cities.parquet |
| ├── citing_papers.parquet |
| ├── citing_papers_normalized.parquet |
| ├── countries.parquet |
| ├── fields.parquet |
| ├── intents.parquet |
| ├── journals.parquet |
| ├── kg_edges.parquet |
| ├── kg_nodes.parquet |
| ├── seed_cited_papers.parquet |
| └── seed_cited_papers_normalized.parquet |
| ``` |
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| # Ethical Considerations |
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| This dataset is intended for scholarly analysis and research support. Citation-based metrics should not be used as the sole basis for evaluating researchers, institutions, journals, or countries. |
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| --- |
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| # Citation |
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| ```bibtex |
| @dataset{idcite2026, |
| title={IDCite: A Large-Scale Multidisciplinary Citation Intent Dataset for Scholarly Knowledge Discovery}, |
| author={Nam, Seohyun}, |
| year={2026}, |
| publisher={Hugging Face}, |
| url={https://huggingface.co/datasets/Daniel0315/IDCite} |
| } |
| ``` |
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| --- |
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| # License |
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| CC BY 4.0 |
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| --- |
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