Organizations › Nonprofit › ResearchOrganization

FAQ Page Blueprint — Research Organization

FAQ pages are where AI looks for direct answers. When someone asks an AI about collaboration opportunities, publication access, grant applications, or data sharing policies at your institute, structured FAQ data lets AI pull your answer verbatim — with attribution back to your organization.

View Prompt View JSON

What this page needs

FAQ pages are one of the highest-value pages for AI citation. When someone asks an AI "how do I collaborate with a climate research institute" or "can I access published datasets from this lab," AI looks for structured question-and-answer pairs it can use directly. Without structured data, AI has to parse your HTML and guess which text is a question and which is an answer.

FAQPage as primary type. Declaring the page as FAQPage tells AI the entire page is a collection of questions and answers about your research organization, not a generic web page that happens to contain some Q&A text.
mainEntity with Question/Answer pairs. Each question uses the Question type with a name (the question text) and an acceptedAnswer of type Answer. This explicit pairing removes all ambiguity about which answer belongs to which question.
Research-specific topics. Cover the questions prospective collaborators, funders, and journalists actually ask: How to propose a joint study, how to access published data, how to apply for grants, and what your data sharing policies are.
Clear, self-contained answers. Each Answer should contain a complete response in the text field. AI systems prefer answers that stand on their own without needing surrounding context from the page.

Why these fields matter to AI

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

ResearchOrganization

name: Non-negotiable. AI cannot cite or recommend an unnamed organization.
url: AI needs a stable URL to attribute recommendations and route users correctly.

Use This Prompt to Implement Your Schema

Copy 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 FAQ 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. Answer
2. Domain
3. Organization name
4. Question

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 FAQ"
- 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

Template — fill in your values

Copy the template below and replace every YOUR_* value with your own data. Add or remove Question objects in the mainEntity array to match the number of questions on your page.

{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "FAQPage",
      "@id": "https://YOUR_DOMAIN.com/faq/#faqpage",
      "name": "Frequently Asked Questions — YOUR_ORGANIZATION_NAME",
      "url": "https://YOUR_DOMAIN.com/faq/",
      "mainEntity": [
        {
          "@type": "Question",
          "name": "YOUR_QUESTION_1",
          "acceptedAnswer": {
            "@type": "Answer",
            "text": "YOUR_ANSWER_1"
          }
        },
        {
          "@type": "Question",
          "name": "YOUR_QUESTION_2",
          "acceptedAnswer": {
            "@type": "Answer",
            "text": "YOUR_ANSWER_2"
          }
        },
        {
          "@type": "Question",
          "name": "YOUR_QUESTION_3",
          "acceptedAnswer": {
            "@type": "Answer",
            "text": "YOUR_ANSWER_3"
          }
        },
        {
          "@type": "Question",
          "name": "YOUR_QUESTION_4",
          "acceptedAnswer": {
            "@type": "Answer",
            "text": "YOUR_ANSWER_4"
          }
        },
        {
          "@type": "Question",
          "name": "YOUR_QUESTION_5",
          "acceptedAnswer": {
            "@type": "Answer",
            "text": "YOUR_ANSWER_5"
          }
        }
      ]
    },
    {
      "@type": "WebPage",
      "@id": "https://YOUR_DOMAIN.com/faq/",
      "isPartOf": {
        "@id": "https://YOUR_DOMAIN.com/#website"
      },
      "about": {
        "@id": "https://YOUR_DOMAIN.com/#organization"
      },
      "breadcrumb": {
        "@id": "https://YOUR_DOMAIN.com/faq/#breadcrumb"
      }
    },
    {
      "@type": "ResearchOrganization",
      "@id": "https://YOUR_DOMAIN.com/#organization",
      "name": "YOUR_ORGANIZATION_NAME",
      "url": "https://YOUR_DOMAIN.com"
    },
    {
      "@type": "BreadcrumbList",
      "@id": "https://YOUR_DOMAIN.com/faq/#breadcrumb",
      "itemListElement": [
        {
          "@type": "ListItem",
          "position": 1,
          "name": "Home",
          "item": "https://YOUR_DOMAIN.com/"
        },
        {
          "@type": "ListItem",
          "position": 2,
          "name": "FAQ",
          "item": "https://YOUR_DOMAIN.com/faq/"
        }
      ]
    }
  ]
}

Frequently asked questions

What topics should a research organization FAQ cover?

Focus on the questions prospective collaborators, funders, and the public actually ask: how to propose a partnership, how to access published datasets, how to apply for grants or fellowships, what your data sharing and open-access policies are, and how media can request interviews with researchers. These are the queries AI systems encounter most often.

Should the FAQ page use FAQPage as the primary type instead of WebPage?

Yes. When the entire page is dedicated to answering questions, FAQPage should be the primary type in the graph. This tells AI the page is a structured Q&A resource, not a generic page that happens to have a few questions. If your FAQ section is a small part of a larger page, embed the FAQPage node in the graph alongside a WebPage primary type instead.

How many questions should I include?

Include every question that appears on the visible page. The structured data should mirror what a user sees. There is no upper limit — more questions mean more opportunities for AI to match your institute to specific queries. Each question-answer pair is an independent data point AI can surface when someone asks a related question.