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# IDCite: A Large-Scale Multidisciplinary Citation Intent Dataset for Scholarly Knowledge Discovery
## Dataset Description
IDCite is a large-scale multidisciplinary dataset of citation contexts and citation intents spanning 21 Essential Science Indicators (ESI) fields.
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.
The dataset is intended to support research on:
* Citation context analysis
* Citation intent analysis
* Scientometric and bibliometric research
* Scholarly information retrieval
* Citation recommendation
* Research assessment
* Cross-disciplinary citation analysis
* Knowledge graph analytics
## Zenodo Repository and Documentation
The official archived Version 3 release of IDCite is available on Zenodo:
**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)
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:
**`IDCite_Project_and_Dataset_Documentation_Seohyun_Nam.pdf`**
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.
---
# Dataset Summary
| 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 |
---
## Representative Schema Definitions
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.
| 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` |
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.
The `kg_nodes.parquet` and `kg_edges.parquet` files provide a supplementary graph representation derived from these normalized entities and relationships.
---
# Citation Events
The main citation event files contain paper-level citation relations and citation semantics.
Important fields include:
| 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 |
---
# Seed Cited Papers
Seed papers represent highly cited papers used as cited targets.
Important fields include:
| 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 |
---
# Knowledge Graph
The dataset includes a heterogeneous scholarly knowledge graph.
## kg_nodes.parquet
| 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 |
## kg_edges.parquet
| Field | Description |
| ----------- | ---------------------- |
| `source` | Source node ID |
| `target` | Target node ID |
| `edge_type` | Type of graph relation |
---
# Intended Uses
This dataset can be used for:
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
---
# Dataset Construction
The dataset was constructed by integrating:
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
The normalized files provide ID-based mappings for relational and graph-based experiments.
---
# Dataset Structure
```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
```
# Ethical Considerations
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.
---
# Citation
```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}
}
```
---
# License
CC BY 4.0
---
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