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‎.gitignore‎

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# Ignore folders generated by Bundler
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.bundle/
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vendor/
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.DS_Store
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**/.DS_Store
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public/
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resources/

‎assets/images/bdiviz-screenshot.png‎

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‎assets/images/gradient-mobile.webp‎

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‎assets/images/new-matching-task.gif‎

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‎assets/jsconfig.json‎

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{
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"compilerOptions": {
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"baseUrl": ".",
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"paths": {
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"*": [
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"../../../../../Library/Caches/hugo_cache/modules/filecache/modules/pkg/mod/github.com/gohugoio/hugo-mod-jslibs-dist/popperjs/[email protected]/package/dist/cjs/*",
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"../../../../../Library/Caches/hugo_cache/modules/filecache/modules/pkg/mod/github.com/twbs/[email protected]+incompatible/js/*"
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]
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}
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}
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}

‎content/docs/_index.md‎

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---
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weight: 999
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title: "BDIViz Documentations"
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subtitle: "Explore our guides and examples to deploy and improve your data integration workflow with BDIViz."
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description: "Explore our guides and examples to deploy and improve your data integration workflow with BDIViz."
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icon: "article"
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date: "2025-04-19T22:16:51-04:00"
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lastmod: "2025-04-19T22:16:51-04:00"
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draft: false
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toc: true
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---

‎content/docs/get-started/_index.md‎

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---
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weight: 999
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title: "Get Started"
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description: "Start your first BDIViz workflow."
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icon: "rocket"
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date: "2025-04-19T13:38:17-04:00"
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lastmod: "2025-04-19T13:38:17-04:00"
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draft: false
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toc: true
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---

‎content/docs/get-started/explore-matches.md‎

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---
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weight: 200
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title: "Explore Matches"
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description: "Once the files finished loading, you will be presented with the main BDIViz interface."
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icon: "zoom_in"
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date: "2025-04-19T13:38:17-04:00"
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lastmod: "2025-04-19T13:38:17-04:00"
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draft: false
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toc: true
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---

‎content/docs/get-started/upload-your-data.md‎

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---
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weight: 100
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title: "Upload Your Data"
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description: "Start a new schema matching task by upload your data files."
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icon: "upload"
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date: "2025-04-19T13:38:17-04:00"
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lastmod: "2025-04-19T13:38:17-04:00"
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draft: false
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toc: true
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---
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## Start a New Matching Task
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Click the rightmost button labeled "New Matching Task" to begin. This will open the file upload interface (see screenshot below).
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![new-matching-task-gif](images/new-matching-task.gif)
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You will see three drop boxes stacked from top to bottom:
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- **Source CSV File** – for your raw dataset
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- **Target CSV File** – for the reference standard dataset
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- **Target Schema JSON File** – for metadata and attribute definitions
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To begin exploring schema matches, you’ll first need to upload these three types of files. These provide the information needed to visualize and compare your source dataset with a standardized target schema.
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## Upload Source CSV File
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Select a local .csv file that contains your raw or unaligned biomedical dataset.
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Example:
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```csv
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Case_ID, Gender, Ethnicity_Self_Identify, Path_Stage_Reg_Lymph_Nodes_pN
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C1234, Male, Asian, pN1
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C5678, Female, White, pN2
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C1111, Unknown, Unknown, pNX
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```

‎content/docs/overview.md‎

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---
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weight: 300
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title: "Overview"
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description: "BDIViz: An Interactive Visualization System for Biomedical Schema Matching with LLM-Supported Validation"
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icon: "circle"
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date: "2025-04-19T13:38:17-04:00"
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lastmod: "2025-04-19T13:38:17-04:00"
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draft: false
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toc: true
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---
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## :gear: Getting Started
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First, install the required dependencies:
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```bash
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npm i .
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```
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Then, run the development server:
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```bash
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npm run dev
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```
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## :gear: Introduction
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**BDIViz** is an interactive web-based application developed as part of the ARPA-H ASKEM project to support schema matching and value mapping tasks in biomedical data integration. It provides users with a rich visual interface—including heatmaps, explanations, and value comparisons—to streamline the process of aligning raw biomedical datasets with standardized data schemas such as the Genomic Data Commons (GDC) and Proteomic Data Commons (PDC).
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**BDIViz** is model agnostic, meaning it can be used with any schema matching model. It is designed to work with the [BDI-Kit](https://github.com/VIDA-NYU/bdi-kit) module, which is a Python library that provides a set of tools for schema matching and value mapping tasks. The BDI-Kit module includes a variety of schema matching algorithms, including supervised and unsupervised methods, as well as tools for data preprocessing and feature extraction.
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## :gear: Features
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- 🔍 **Interactive Heatmap** for exploring source-target column match candidates
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- 📊 **Value Comparison Table** using fuzzy matching on raw values
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- 🤖 **LLM-Powered Agent Panel** for dynamic match explanations and feedback
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- ⏪ **Timeline View** to trace user actions (accept, reject, discard)
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- 🎯 **Control Panel** for adjusting similarity threshold and navigating source columns
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- 📤 **Export Curated Mappings** as JSON or CSV for downstream use
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## :camera: Demo
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Video demo:
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[![BDIViz Demo](https://img.youtube.com/vi/1eAbDicO0oXIbbVg56m3H8xdNDDsBGBLI/0.jpg)](https://drive.google.com/file/d/1RY3XjRmLIkBNjcZWkUZhG3vA-ZvPc6Ug/view?usp=drive_link)
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<!-- [BDIViz Demo](https://drive.google.com/file/d/1eAbDicO0oXIbbVg56m3H8xdNDDsBGBLI/view?usp=drive_link) -->
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Live Demo:
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https://bdiviz-dev.users.hsrn.nyu.edu/dashboard/
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<!-- ## :gear: Sequence Diagram
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```mermaid
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sequenceDiagram
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actor U as User
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box Lightyellow BDI-Viz
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participant B as React App
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participant S as Flask Server
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end
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U->>B: Input Source/Target csv
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B->>S: Request Schema Matching
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Note right of S: Default Model
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S->>B: Response Matching Candidates
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U->>B: Accept/Reject/Refine Matches
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B->>S: [Agent] Digest User Actions
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S->>B: [Agent] Possible Reasons
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Note left of B: Reason 1: Exact Match <br>Reason 2: Value Similarity <br>Reason 3: Prefix/Suffix Match <br>Reason 4: Synonym Match <br>Reason 5: etc.
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B->>U: What do you think is the best reason for this action?
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U->>B: Select Reason 3
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B->>S: [Agent] Update Model/Dataset
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Note right of S: FT Model 3
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S->>B: Response Matching Candidates
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``` -->

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