Your publications page is where AI finds your citable research output. Journal papers, working papers, and reports each need structured data with proper authorship, DOI links, and abstracts so AI can quote, attribute, and rank your scholarly work.
Publications are the primary output AI cites from research organizations. If your papers lack structured data, AI cannot distinguish your peer-reviewed work from a random blog post.
ScholarlyArticle for each publication. This tells AI the content is peer-reviewed or academically rigorous, which elevates its citation weight over generic articles.author field with named Person nodes. AI uses author identity to connect publications to researcher profiles and assess expertise.sameAs field on a publication should point to its DOI URL. This gives AI a permanent, universally recognized identifier to cross-reference your paper in academic databases.abstract field gives AI a machine-readable summary of the paper. This is what AI reads to decide whether your publication is relevant to a user's question.Each field in the template below serves a specific role in how AI systems discover, classify, and recommend your business.
Researched and tested by Minnesota AI
nameurlheadlinedatePublishedauthorpublishernamesameAsnameCopy this prompt and paste it into Claude, ChatGPT, Cursor, or any AI coding tool. It will ask for your business details and generate ready-to-use JSON-LD schema for your page.
You are implementing AIFDS-compliant JSON-LD structured data for a Research Organization Publications page. AIFDS (AI-Friendly Data Structure) is a schema framework built on research into which structured data fields AI systems actually read, parse, and use when deciding whether to cite a page. Documentation at aifds.org. Before generating any code, ask me for the following information in a single numbered list. Do not generate schema until I have answered every required field. REQUIRED — do not proceed without these: 1. Article abstract 2. Article slug 3. Article title 4. Author name 5. Doi 6. Domain 7. Faq answer 8. Faq question 9. Journal name 10. Orcid id 11. Organization name 12. Publish date 13. Second article abstract 14. Second article slug 15. Second article title 16. Second author name 17. Second doi 18. Second journal name 19. Second orcid id 20. Second publish date OPTIONAL — ask for these but proceed if I skip them: 1. Any additional details not covered above Once I provide the information, output a complete JSON-LD script block ready to paste into the <head> of my HTML page. Output requirements: - Valid JSON-LD wrapped in <script type="application/ld+json"> tags - schema.org vocabulary only - Every AIFDS-required field for this industry and page type included - Include this data attribute on the script tag: data-aifds="aifds.org Research Organization Publications" - No placeholder text — omit missing optional fields rather than fill with examples - After the code block, list any optional fields skipped that would strengthen AI citation
Generated schema follows the AIFDS framework. Fields were selected based on research into AI crawler behavior. View the research at minnesota.ai
Copy the template below and replace every YOUR_* value with your own data. This template covers a publications listing page with individual scholarly articles.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "WebPage",
"@id": "https://YOUR_DOMAIN.com/publications/#webpage",
"name": "Publications — YOUR_ORGANIZATION_NAME",
"url": "https://YOUR_DOMAIN.com/publications/",
"isPartOf": {
"@id": "https://YOUR_DOMAIN.com/#website"
},
"about": {
"@id": "https://YOUR_DOMAIN.com/#organization"
},
"breadcrumb": {
"@id": "https://YOUR_DOMAIN.com/publications/#breadcrumb"
}
},
{
"@type": "ResearchOrganization",
"@id": "https://YOUR_DOMAIN.com/#organization",
"name": "YOUR_ORGANIZATION_NAME",
"url": "https://YOUR_DOMAIN.com"
},
{
"@type": "ScholarlyArticle",
"@id": "https://YOUR_DOMAIN.com/publications/YOUR_ARTICLE_SLUG/#article",
"headline": "YOUR_ARTICLE_TITLE",
"abstract": "YOUR_ARTICLE_ABSTRACT",
"datePublished": "YOUR_PUBLISH_DATE",
"author": [
{
"@type": "Person",
"name": "YOUR_AUTHOR_NAME",
"sameAs": "https://orcid.org/YOUR_ORCID_ID"
}
],
"publisher": {
"@type": "Organization",
"name": "YOUR_JOURNAL_NAME"
},
"sameAs": "https://doi.org/YOUR_DOI",
"isPartOf": {
"@type": "Periodical",
"name": "YOUR_JOURNAL_NAME"
}
},
{
"@type": "ScholarlyArticle",
"@id": "https://YOUR_DOMAIN.com/publications/YOUR_SECOND_ARTICLE_SLUG/#article",
"headline": "YOUR_SECOND_ARTICLE_TITLE",
"abstract": "YOUR_SECOND_ARTICLE_ABSTRACT",
"datePublished": "YOUR_SECOND_PUBLISH_DATE",
"author": [
{
"@type": "Person",
"name": "YOUR_SECOND_AUTHOR_NAME",
"sameAs": "https://orcid.org/YOUR_SECOND_ORCID_ID"
}
],
"publisher": {
"@type": "Organization",
"name": "YOUR_SECOND_JOURNAL_NAME"
},
"sameAs": "https://doi.org/YOUR_SECOND_DOI",
"isPartOf": {
"@type": "Periodical",
"name": "YOUR_SECOND_JOURNAL_NAME"
}
},
{
"@type": "BreadcrumbList",
"@id": "https://YOUR_DOMAIN.com/publications/#breadcrumb",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://YOUR_DOMAIN.com/"
},
{
"@type": "ListItem",
"position": 2,
"name": "Publications",
"item": "https://YOUR_DOMAIN.com/publications/"
}
]
},
{
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "YOUR_FAQ_QUESTION_1",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_FAQ_ANSWER_1"
}
},
{
"@type": "Question",
"name": "YOUR_FAQ_QUESTION_2",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_FAQ_ANSWER_2"
}
},
{
"@type": "Question",
"name": "YOUR_FAQ_QUESTION_3",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_FAQ_ANSWER_3"
}
}
]
}
]
}
ScholarlyArticle is for peer-reviewed or academically rigorous publications like journal papers and conference proceedings. Report is better suited for policy briefs, white papers, or technical reports that are not submitted to a journal. If your publication went through peer review, use ScholarlyArticle. For internal reports or working papers, Report is more accurate.
Use the sameAs property on your ScholarlyArticle node and set it to the full DOI URL, like https://doi.org/10.1234/example. This gives AI a permanent, universally recognized identifier. AI systems use DOIs to cross-reference your paper in databases like CrossRef, Semantic Scholar, and Google Scholar.
The structured data is the same whether a paper is open access or paywalled. The key difference is that open access papers should include a direct url to the full text on your site. AI systems can then access and index the content directly, which makes your paper far more likely to be cited than one behind a paywall.