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PubMed Central: Technology, History, Art & Science
PubMed Central (PMC) is a free digital repository that archives open access full-text scholarly articles that have been published in biomedical and life sciences journals. As one of the major research databases developed by the National Center for Biotechnology Information (NCBI), PubMed Central is more than a document repository. Submissions to PMC are…
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PubMed Central topic overview
The analysis highlights Technology, History, Art and Science as prominent areas in the source structure around PubMed Central.
Related topics
60
Source areas
6
Connected nodes
66
Extracted relationships
85
Concept neighborhoods
24
Bridge connections
66
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
History · 19 topics
Adoption · 12 topics
Overview · 11 topics
Reception · 7 topics
Technology · 6 topics
PMCID · 5 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Cost
Free
Disciplines
Medicine
Format coverage
Journal articles
History
2000–present
No. of records
10,800,000
Producer
United States National Library of Medicine (United States)
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How PubMed Central connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around PubMed Central shows recurring relationship patterns in the source. For example, PubMed Central → British Library, Consolidated Appropriations Act, Europe PubMed Central, February, Health, In, January, Launched, National Institutes, NIH, NIH Public Access Policy, NIH-funded, November, October, On, PubMed Central Canada, PubMed Central International, The Canadian, These, This Another extracted example is PubMed Central → Articles, DTDs, Graphics, Interchange DTD, Many, NLM Archiving, NLM Journal Publishing DTD, Older, PDF, Received, SGML, The, This, XML, XSLT. Use these groups to spot repeated connection types before inspecting the individual relationships.
PubMed Central
Top relations
related to Adoption· 25
PubMed Central → British Library, Consolidated Appropriations Act, Europe PubMed Central, February, Health, In, January, Launched, National Institutes, NIH, NIH Public Access Policy, NIH-funded, November, October, On, PubMed Central Canada, PubMed Central International, The Canadian, These, This
PubMed Central relationships Subject–Predicate–Object triples
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 85 structured relationships around PubMed Central. Examples in this analysis include PubMed Central → Cost → Free and PubMed Central → Disciplines → Medicine. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
PubMed Central
Cost
Free
1.00
infobox
PubMed Central
Disciplines
Medicine
1.00
infobox
PubMed Central
Format coverage
Journal articles
1.00
infobox
PubMed Central
History
2000–present
1.00
infobox
PubMed Central
No. of records
10,800,000
1.00
infobox
PubMed Central
Producer
United States National Library of Medicine (United States)
1.00
infobox
PubMed Central
Record depth
Index, abstract & full-text
1.00
infobox
PubMed Central
Title list(s)
pmc.ncbi.nlm.nih.gov/journals/
1.00
infobox
PubMed Central
Website
pmc.ncbi.nlm.nih.gov
1.00
infobox
PubMed Central
is a
free digital archive of full articles
0.90
text
PubMed Central
is a
key example of
0.90
text
AIP
instance of
Organizations
0.80
text
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around PubMed Central bring nearby vocabulary together. In this analysis, examples include Pubmed, Nih and Articles. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
PubMed Central
Pubmed
Nih
Articles
Research
Full-text
Article
Database
National
Also
Library
Open
Biomedical
pubmed central
Pubmed
Nih
Research
Articles
Full-text
Article
Database
National
Also
Library
Open
Biomedical
open access
Access
Open
Repository
Public
Nih
Pmc
Research
Free
Papers
Biomedical
Published
Publishers
pubmed
Nih
Articles
Research
Full-text
Article
Database
National
Also
Library
Open
Biomedical
Nlm
harold varmus
National
Library
Free
Accessible
Nlm
Journals
E-biomed
Nih
Full-text
Linking
Ncbi
Publishers
nih public access policy
Open
Repository
Public
Nih
Pmc
Research
Pubmed
Free
Biomedical
Varmus
Publishers
Papers
uk pubmed central (ukpmc)
Pubmed
Nih
Research
Articles
Full-text
Article
Database
National
Also
Library
Open
Biomedical
europe pubmed central
Pubmed
Nih
Research
Articles
Full-text
Article
Database
National
Also
Library
Open
Biomedical
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For PubMed Central, one of the stronger structural bridges in this analysis connects PubMed Central with History. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Min side: 3
PubMed Central — History· splits 47 ⟂ 20PubMed Central — Adoption· splits 54 ⟂ 13PubMed Central — Overview· splits 55 ⟂ 12PubMed Central — Reception· splits 59 ⟂ 8PubMed Central — Technology· splits 60 ⟂ 7PubMed Central — PMCID· splits 61 ⟂ 6
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
PubMed Central
Nodes67
Edges66
Triples85
Avg. degree1.97
Density0.029851
Components1
Source & methodology
TTTA analyzes the structure around PubMed Central to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Technology, History, Art & Science, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
