Route a page to it's subdomain

Features

• graph view
• citation
• summariser
• community summariser
• NLP translator
• community translation

Navigation

• My library (User’s saved/read papers)

You're absolutely right — a search engine and a research IDE are fundamentally different in purpose, behavior, and user flow, even if they share overlapping capabilities like saving papers or referencing.

Let’s break down the distinction:

1. Research Search Engine (e.g., Hub)

Purpose:
To explore the external world of research. Find, filter, discover, save, and track academic content.

Key Traits:

• Exploratory: You're browsing, searching, filtering, learning.
• Global Scope: Pulls from open databases, preprints, journals.
• Passive Actions: Save, bookmark, follow, cite.
• Public-first: You’re stepping into the shared research ecosystem.
• Heavy on filters & metadata: Date, source, citations, field, OA, etc.

Primary UX Flow:

1. Search
2. Browse
3. Open + inspect papers
4. Save or export
5. Maybe: add to a workspace

1. Core Features of the Platform

1. Paper Exploration & Study
2. Collaborative Editing & Contributions
3. Citation & Network Analysis

2. Homepage

2.1 Elements on the Homepage

• Header (Navigation Bar)
  • Search bar (with AI suggestions)
  • Home
  • Explore Papers (Browse by category, new additions, trending)
  • Categories (Sub-disciplines, Topics, Authors, Institutions)
  • Graph view
  • My Library
  • Summarizer (AI-assisted summaries) on demand
  • Account/Profile
• Main Content
  • Hero Section – Introduction to the platform & CTA (Call-to-action) for searching papers.
  • Trending Papers – Most read, discussed, or cited recently.
  • Featured Collections – Special curated lists, such as Nobel-winning research.
  • Latest Submissions – Recently added or updated papers.
  • Paper Summarizer – Users can input a paper URL or upload a PDF for AI-generated summaries.
  • Recommended for You – AI-driven personalized suggestions.
  • Collaboration Zone – List of active discussions, pull requests on GitHub, and open contribution areas.
• Footer
  • About | Terms of Use | Privacy Policy
  • API Access (if allowing programmatic access to paper metadata)
  • Open Source Contributions
  • Social Links

3. Navigation & Page Breakdown

1. Explore Papers
   • Layer 1: Subject Areas – AI, Physics, Medicine, Economics, etc.
   • Layer 2: Sub-Subjects – AI → Computer Vision, NLP, Robotics, etc.
   • Layer 3: Paper Lists – Sorted by popularity, recency, or impact.
   • Layer 4: Individual Paper Page
2. Summarizer
   • Layer 1: Input Paper (URL, PDF, Markdown)
   • Layer 2: AI Summary
   • Layer 3: Compare with Community Summaries
3. Citation Network
   • Layer 1: Paper Citations – Shows how many times cited.
   • Layer 2: Visualization of References – Graph-based exploration (like Litmaps).
4. My Library
   • Layer 1: Saved Papers
   • Layer 2: Reading History
   • Layer 3: Personal Notes & Highlights
5. Author & Institution Profiles
   • Layer 1: List of Authors/Institutions
   • Layer 2: Individual Profile (Papers, Citations, Impact Score)

4. The Paper Page (Detailed Structure)

Each paper page will have several interactive elements:

• Basic Metadata
  • Title
  • Author(s)
  • Institution
  • Date of Publication
  • Source (arXiv, Springer, Nature, etc.)
  • Open Access / Subscription Required
• Main Content
  • Abstract (Original + AI Summary)
  • Sections with Expand/Collapse
  • Figures & Tables with Interactive Annotations
  • Mathematical Equations (LaTeX Support)
  • User Highlights & Notes
• Interactive Features
  • AI-generated explanations (like “Explain Like I’m 5”)
  • Discussion Threads (like Reddit-style comments)
  • Collaborative Editing Panel (Links to GitHub PRs)
• Citation & References
  • Citation Count (How many times it has been cited)
  • Reference Graph (Like Litmaps)
  • Suggested Related Papers

5. Editing & Collaboration

5.1 Markdown Editing on GitHub

• Papers are stored as Markdown files on GitHub.
• Users can propose edits via pull requests.
• A version history will track changes over time.

5.2 Other Editing Options

• In-Browser Editor – Users can edit and submit suggestions without GitHub, using an integrated text editor.

6. Citation & Network Analysis

6.1 Citation Count Feature

• Every paper will display how many times it has been cited.
• Sources for Citation Data:
  • CrossRef
  • Google Scholar
  • OpenCitations
  • Semantic Scholar

6.2 Reference Graph (Like Litmaps)

• A visual citation network showing:
  • References (Papers cited by this paper)
  • Citations (Other papers citing this one)
  • Clusters (Papers in the same research area)

Scholarly World
Account.Scholarly