Journal Dataset for Machine Learning and Data Analysis
This ready-made synthetic dataset contains journal article information, author details, and citation records. It is ideal for practicing SQL joins and data exploration techniques. A free sample of 1000 rows is available for preview.
At a glance
- 4tables
- 45,756rows
- 20columns
- Jan 2000 – Dec 2024date range
The 4 tables
preview and data dictionary per tableArticles articles · table · 2,000 rows
Information about academic journal articles.
Preview
| article_iduuid | titlestring | abstractstring | publication_datedate | journal_namestring | issnstring | keywordsstring |
|---|---|---|---|---|---|---|
| 30d911ea-e574-4d02-8547-f0a6792a14f1 | The effect of novel therapeutic interventions on the progression of type 2 diabetes in a large, multi-center, randomized controlled trial: A 5-year follow-up study | Type 2 diabetes mellitus (T2DM) remains a significant global health challenge, necessitating the development and evaluation of effective therapeutic strategies. This large-scale, multi-center, randomized controlled trial investigated the long-term efficacy and safety of a novel combination therapy comprising an SGLT2 inhibitor and a GLP-1 receptor agonist in patients with inadequately controlled T2DM. A total of 3,500 participants were randomized to receive either the novel combination therapy or standard of care for a period of five years. Primary endpoints included changes in glycated hemoglobin (HbA1c) levels, body weight, and the incidence of major adverse cardiovascular events. Secondary endpoints assessed renal function, lipid profiles, and patient-reported outcomes. Our findings demonstrate a statistically significant and clinically meaningful reduction in HbA1c levels and body weight in the intervention group compared to the control group. | 2013-01-15 | The Lancet | 0140-6736 | Type 2 diabetes, novel therapies, SGLT2 inhibitor, GLP-1 receptor agonist, randomized controlled trial, cardiovascular events, renal function, HbA1c, metabolic syndrome, long-term efficacy |
| 3b6159c7-acb7-432a-a908-b1c2325dd2b7 | Synthesis and Characterization of Novel Luminescent Lanthanide Complexes for Advanced Photonic Applications: A Detailed Spectroscopic and Structural Investigation | The development of efficient and stable luminescent materials is crucial for a wide range of advanced photonic applications, including solid-state lighting, bio-imaging, and sensing. This study reports on the rational design, synthesis, and comprehensive characterization of a series of novel lanthanide complexes incorporating tailored organic ligands. We focused on europium(III) and terbium(III) ions, known for their characteristic sharp emission lines in the visible region. The organic ligands were designed to possess efficient antenna effects, facilitating energy transfer from the ligand to the lanthanide center, thereby enhancing luminescence quantum yields. Various synthetic routes were explored to optimize complex formation and purity. The synthesized complexes were characterized using a combination of techniques, including elemental analysis, infrared spectroscopy, UV-Vis absorption spectroscopy, and luminescence spectroscopy. | 2011-10-17 | Journal of the American Chemical Society | 0002-7863 | Luminescent materials, lanthanide complexes, europium, terbium, organic ligands, photophysics, spectroscopy, X-ray diffraction, photonic applications, energy transfer, quantum yield, synthesis |
| 35947d09-fa8b-47dc-a4fb-f580595b0b07 | Investigating the Role of Gut Microbiota in Modulating Immune Responses in a Cohort of Patients with Inflammatory Bowel Disease | Inflammatory Bowel Disease (IBD) is a chronic condition characterized by aberrant immune responses in the gastrointestinal tract. The gut microbiota, a complex ecosystem of microorganisms, is increasingly recognized for its profound influence on host immunity. This study aimed to comprehensively analyze the composition and functional potential of the gut microbiota in a cohort of IBD patients compared to healthy controls, and to correlate these findings with specific immune markers and disease severity. We employed 16S rRNA gene sequencing and shotgun metagenomics to characterize the microbial communities, alongside multiplex cytokine assays and flow cytometry to assess immune cell populations and cytokine profiles. Our results revealed significant dysbiosis in IBD patients, characterized by a reduction in beneficial bacteria such as Faecalibacterium prausnitzii and an increase in pro-inflammatory taxa. | 2023-11-24 | PLOS ONE | 1932-6203 | Gut microbiota, Inflammatory Bowel Disease, IBD, Immune response, Dysbiosis, 16S rRNA sequencing, Metagenomics, Cytokines, T-cells, Host-microbe interactions |
| 333c2e28-b31f-417b-8891-81fd7f7818bf | A Novel High-Throughput Screening Assay for Identifying Inhibitors of Protein-Protein Interactions Relevant to Cancer Metastasis | Protein-protein interactions (PPIs) play critical roles in numerous cellular processes, including cancer progression and metastasis. Disrupting key oncogenic PPIs represents a promising therapeutic strategy. Developing robust high-throughput screening (HTS) assays for PPI inhibitors is essential for drug discovery. This study reports the development and validation of a novel, luminescence-based HTS assay designed to identify small molecules that inhibit the interaction between MDM2 and p53, a well-established target in cancer therapy. The assay demonstrates high sensitivity, specificity, and Z'-factor, making it suitable for large-scale screening campaigns. We screened a library of 100,000 small molecules and identified several promising hit compounds with IC50 values in the low micromolar range. Further characterization of these hits confirmed their ability to disrupt the MDM2-p53 interaction in cells and inhibit tumor cell proliferation. | 2009-03-12 | PLOS ONE | 1932-6203 | Protein-protein interactions, PPI inhibitors, High-throughput screening, HTS, Cancer metastasis, MDM2, p53, Drug discovery, Assay development, Luminescence assay |
| ac72fe77-7f80-44aa-b512-b3c1b8c72590 | Elucidating the Role of MicroRNA-122 in Regulating Lipid Metabolism and its Implications for Non-Alcoholic Fatty Liver Disease | Non-alcoholic fatty liver disease (NAFLD) is a prevalent metabolic disorder characterized by excessive fat accumulation in the liver, often progressing to more severe liver damage. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally and are implicated in various diseases. MicroRNA-122 (miR-122) is the most abundant miRNA in the liver and is known to play a crucial role in lipid homeostasis. This study investigated the specific mechanisms by which miR-122 regulates hepatic lipid metabolism and its contribution to NAFLD pathogenesis. Using a combination of in vitro cell culture models and in vivo mouse models of NAFLD, we demonstrated that reduced expression of miR-122 leads to increased fatty acid uptake and de novo lipogenesis, thereby promoting hepatic steatosis. We identified key target genes, including fatty acid translocase (CD36) and sterol regulatory element-binding protein-1c (SREBP-1c), that are directly regulated by miR-122. | 2005-03-10 | PLOS ONE | 1932-6203 | MicroRNA-122, miR-122, Non-alcoholic fatty liver disease, NAFLD, Lipid metabolism, Hepatic steatosis, Gene regulation, CD36, SREBP-1c, Metabolic disorder |
| beee0cf9-a2f7-4c49-81d2-f854bc378886 | Genome-Wide Association Study Identifies Novel Genetic Loci Associated with Susceptibility to Rheumatoid Arthritis in a Diverse Population Cohort | Rheumatoid Arthritis (RA) is a chronic autoimmune disease characterized by systemic inflammation, primarily affecting the joints. While genetic factors are known to contribute to RA susceptibility, the underlying genetic architecture remains incompletely understood. This genome-wide association study (GWAS) aimed to identify novel genetic loci associated with RA risk in a large, diverse population cohort comprising individuals of European, Asian, and African ancestry. We genotyped over 1 million single nucleotide polymorphisms (SNPs) in 5,000 RA cases and 5,000 healthy controls. Our analysis revealed several novel genetic loci, including variants in genes involved in immune regulation and inflammatory pathways, that reached genome-wide significance. Notably, we identified a novel association with a variant in the PTPN22 gene, which has previously been implicated in other autoimmune diseases. | 2016-08-16 | PLOS ONE | 1932-6203 | Rheumatoid Arthritis, RA, Genome-wide association study, GWAS, Genetic loci, Autoimmune disease, Immune regulation, PTPN22, SNP, Population genetics |
| b322d4e3-d732-4c4c-ba91-69f2c599a6fc | Structural and Functional Characterization of a Novel DNA Repair Enzyme from Extremophilic Archaea | DNA repair mechanisms are essential for maintaining genomic integrity, particularly in organisms living under harsh environmental conditions such as high temperature, radiation, or extreme pH. Extremophilic archaea have evolved sophisticated DNA repair systems to cope with these challenges. This study focuses on the structural and functional characterization of a novel DNA repair enzyme, tentatively named Archaeal Nucleotide Excision Repair Protein 1 (ANERP1), isolated from the hyperthermophilic archaeon *Thermococcus litoralis*. We employed X-ray crystallography to determine the three-dimensional structure of ANERP1 at atomic resolution, revealing a unique structural fold distinct from known repair enzymes. Biochemical assays demonstrated that ANERP1 possesses potent endonucleolytic activity, capable of excising damaged nucleotides from DNA. Kinetic analyses indicated high catalytic efficiency and thermostability, consistent with its extremophilic origin. | 2011-09-29 | Nucleic Acids Research | 0305-1048 | DNA repair, Extremophiles, Archaea, Thermococcus litoralis, X-ray crystallography, Enzyme structure, Endonuclease, Nucleotide excision repair, Genomic integrity, Protein function |
| 864b716f-ba22-43de-812b-9bd2e138c125 | CRISPR-Cas9 Mediated Gene Editing for the Correction of Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) Mutations in Human Bronchial Epithelial Cells | Cystic Fibrosis (CF) is a genetic disorder caused by mutations in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene, leading to defective ion transport and mucus accumulation in various organs, particularly the lungs. Gene editing technologies, such as CRISPR-Cas9, offer a promising avenue for correcting these disease-causing mutations. This study aimed to develop and optimize a CRISPR-Cas9-based gene editing strategy to correct common CFTR mutations in human bronchial epithelial cells (HBECs). We designed specific single-guide RNAs (sgRNAs) and donor DNA templates to target and repair the F508del mutation, the most prevalent CF mutation. Using lentiviral delivery, we achieved efficient delivery of the CRISPR-Cas9 components and donor DNA into primary HBECs. Subsequent analysis, including next-generation sequencing and functional assays measuring chloride channel activity, demonstrated successful correction of the F508del mutation and restoration of CFTR function. | 2013-12-25 | Nucleic Acids Research | 0305-1048 | CRISPR-Cas9, Gene editing, Cystic Fibrosis, CFTR, F508del mutation, Bronchial epithelial cells, HBECs, Gene therapy, Lentiviral delivery, Ion channel function |
| 51794b1f-b5e3-4120-8e7d-c30aa08f4368 | High-Resolution Cryo-EM Structure of the Human Ribosome Elucidates the Mechanism of Translation Initiation | The ribosome is the molecular machine responsible for protein synthesis, a fundamental process in all living cells. Translation initiation is a critical regulatory step that determines where and when protein synthesis begins. Understanding the structural dynamics of the ribosome during initiation is essential for comprehending gene expression control. This study presents a high-resolution cryo-electron microscopy (cryo-EM) structure of the human 80S ribosome engaged in translation initiation. We captured the ribosome in a pre-initiation complex bound to an mRNA and the initiator tRNA. The cryo-EM map reveals detailed interactions between ribosomal subunits, initiation factors, mRNA, and tRNA, providing unprecedented atomic insights into the scanning mechanism and start codon recognition. Our structural data elucidate how the ribosome discriminates between start and non-start codons and how initiation factors facilitate the formation of the functional initiation complex. | 2014-04-22 | Nucleic Acids Research | 0305-1048 | Ribosome, Translation initiation, Cryo-EM, Protein synthesis, Gene expression, mRNA, tRNA, Initiation factors, Eukaryotic ribosome, Molecular mechanism |
| e3e4d6db-c0d6-46af-9681-7e76db23e6c6 | Investigating the Impact of Urban Green Spaces on Mental Well-being and Stress Reduction in a Metropolis | Urbanization is associated with increasing levels of stress and mental health challenges. Access to green spaces within cities has been hypothesized to mitigate these negative effects. This study investigated the relationship between exposure to urban green spaces and mental well-being, including stress levels and mood, among residents of a large metropolitan area. We employed a mixed-methods approach, combining quantitative surveys assessing perceived stress, anxiety, depression, and frequency of green space visits with qualitative interviews exploring participants' experiences and perceptions of urban nature. Objective measures of green space availability and quality were also incorporated using GIS data. Our findings indicate a significant positive correlation between regular use of urban green spaces and improved mental well-being, characterized by lower self-reported stress and anxiety levels, and enhanced mood. | 2017-03-18 | PLOS ONE | 1932-6203 | Urban green spaces, Mental well-being, Stress reduction, Urbanization, Public health, Nature exposure, Mixed-methods research, GIS, Environmental psychology, Restorative environments |
10 of 2,000 rows · 7 columns
Data dictionary
| column | type | description | example | null % |
|---|---|---|---|---|
article_ | uuid | Primary key uniquely identifying each academic journal article.unique | 30d911ea-e574-4d02-8547-f0a6792a14f1 | 0% |
title | string | Full title of the scientific research paper. | The effect of novel therapeutic interventions on the progression of type 2 diabe | 0% |
abstract | string | Detailed synopsis summarizing the article's background, methodology, and conclusions. | Type 2 diabetes mellitus (T2DM) remains a significant global health challenge, n | 0% |
publication_ | date | Official peer-reviewed publication release date. | 2013-01-15 | 0% |
journal_ | string | Name of the peer-reviewed scholarly journal publishing the paper. | The Lancet | 0% |
issn | string | Standard International Standard Serial Number (ISSN) for the publishing journal. | 0140-6736 | 0% |
keywords | string | Comma-separated list of 5 to 10 topical indexing keywords. | Type 2 diabetes, novel therapies, SGLT2 inhibitor, GLP-1 receptor agonist, rando | 0% |
Citations citations · bridge table · 22,944 rows
Records of citations between articles, indicating relationships.
Preview
| citation_iduuid | citation_typestring | cited_article_iduuid | citing_article_iduuid |
|---|---|---|---|
| 82231c14-21d8-48d0-ac94-f90eddbe500a | Reference | 3b6159c7-acb7-432a-a908-b1c2325dd2b7 | c446434b-cad7-4d72-8276-efa0d79d540e |
| 8738fdae-d6ac-436e-9dd4-043a648bd2fc | Reference | 3b6159c7-acb7-432a-a908-b1c2325dd2b7 | 08107b88-bcaf-467c-a991-b1a528c0b8f1 |
| 7653ec9f-f90b-4c58-87c2-23c55ae75262 | Reference | 864b716f-ba22-43de-812b-9bd2e138c125 | e39c61c4-6bef-4d60-b4b5-6fae11257bba |
3 of 22,944 rows · 4 columns
Data dictionary
| column | type | description | example | null % |
|---|---|---|---|---|
citation_ | uuid | Unique identifier for the citation edge record. | bb1f19d4-6277-498c-9725-a852d32984f9 | 0% |
citation_ | string | The contextual purpose or category of the citation. | Reference | 0% |
cited_ | uuid | Foreign key to articles.article_id, indicating the article being cited. | 2d8ee1eb-a045-4f31-ae69-897b39bbf320 | 0% |
citing_ | uuid | Foreign key to articles.article_id, indicating the article that is doing the citing. | dd6437a4-0147-4679-8dfd-2e865f8c5251 | 0% |
How the tables join
article_authors.article_id references articles.article_idmany to one: each Article authors row points to one Articles rowarticle_authors.author_id references authors.author_idmany to one: each Article authors row points to one Authors rowcitations.cited_article_id references articles.article_idmany to one: each Citations row points to one Articles rowcitations.citing_article_id references articles.article_idmany to one: each Citations row points to one Articles row
Questions to answer with it
Find the top 10 most cited articles and list their titles.
You'll need to count citations for each article and join with the articles table to get the title.
tables: articles, citations
List all articles published in 2023 and their corresponding journal names.
Filter articles by publication year and select title and journal name.
tables: articles
Identify authors who have published more than 5 articles.
Join article_authors with authors, group by author, and count their articles.
tables: articles, authors, article_authors
Analyze the distribution of citation types across all citations.
Group citations by citation_type and count the occurrences of each type.
tables: citations
Starter SQL
run against this data before publishingTable names match the SQLite file and the SQL script.
Top 10 Most Cited Articles
SELECT a.title, COUNT(c.citation_id) AS citation_count
FROM articles AS a
JOIN citations AS c ON a.article_id = c.cited_article_id
GROUP BY a.article_id, a.title
ORDER BY citation_count DESC
LIMIT 10;Articles Published in 2023
SELECT title, journal_name
FROM articles
WHERE STRFTIME('%Y', publication_date) = '2023'
LIMIT 20;Authors with More Than 5 Publications
SELECT au.first_name, au.last_name, COUNT(aa.article_id) AS num_articles
FROM authors AS au
JOIN article_authors AS aa ON au.author_id = aa.author_id
GROUP BY au.author_id, au.first_name, au.last_name
HAVING num_articles > 5
LIMIT 20;Citation Type Distribution
SELECT citation_type, COUNT(*) AS count
FROM citations
GROUP BY citation_type
LIMIT 20;Load it with pandas
import pandas as pd
# Unzip the CSV download first: one file per table
articles = pd.read_csv("articles.csv")
authors = pd.read_csv("authors.csv")
citations = pd.read_csv("citations.csv")
article_authors = pd.read_csv("article_authors.csv")
# Join article_authors to articles
df = article_authors.merge(articles, left_on="article_id", right_on="article_id", how="left", suffixes=("", "_articles"))
print(df.groupby("journal_name").size().sort_values(ascending=False))Using it in your tool
- Excel
- Load each table into a separate sheet. Use Power Query to join tables based on common IDs (e.g., article_id, author_id). Create a PivotTable on the 'articles' sheet to summarize publication counts by journal.
- Power BI
- Load all tables. Create relationships: articles.article_id to citations.cited_article_id and citations.citing_article_id; authors.author_id to article_authors.author_id; articles.article_id to article_authors.article_id. Create measures for total citations and article counts.
- SQL
- Load the SQLite or SQL dump into your preferred SQL environment. Use foreign keys defined in the schema for join paths. For example, join 'articles' and 'citations' on 'article_id' to analyze citation data.
Formats available
- CSV (zip)One CSV file per table, zipped
- Excel workbookOne worksheet per table
- SQLite databaseA ready-to-query database file with every table
- Parquet (zip)One Parquet file per table, zipped
- SQL scriptCREATE TABLE with primary and foreign keys, then INSERTs
- CSVA single CSV file
- JSONA single JSON file
How this data was generated
Synthetic data. Every row was generated: no real people, customers or companies are in this dataset.
Synthetic data generated by GoMask DataFactory from a relational blueprint: keys, links and rules are enforced in code, text columns are filled by a language model. No real people, companies or transactions.
- Data generated using GoMask DataFactory.
- Synthetic entities and relationships mimic academic publishing patterns.
- Includes a range of publication dates from 2000 to 2024.
- Checked by an automated quality gate: unique keys, no orphan foreign keys, required columns filled, declared rules and date ranges (realism score 92).
Limitations
- The dataset is synthetic and does not represent real-world research or authors.
- Citation counts are based on the synthetic citation records provided.
- Author affiliations and countries are generalized.
- Distributions and correlations are modelled, not measured from real records.
blueprint · journal-dataset
Scale this dataset
Same tables. As many rows as you need.
Open the blueprint behind these 4 tables in Data Factory: keep the relationships, change a column, and generate it at the size you need.
- 200,000 rows
- 1,000,000 rows
- Tables
- articles, authors, citations, article_authors
- Licence
- yours to use, including commercially
- API slug
- journal-dataset