FAQs

1. Why are biological images so important?
The biological images are essential for visualizing, understanding, and communicating life at every scale — from molecules to ecosystems. These are now central to breakthroughs across multiple fields, including:

• Early disease diagnosis and treatment planning.
• Cellular and molecular research (e.g., drug response, cell behavior).
• Crop yield estimation, plant health monitoring, pathogens identification, etc.
• Drug discovery and development (high-content screening, image-based assays).
• Monitoring developmental processes in animals and plants.
• Education and scientific communication (in teaching anatomy, physiology, and microbiology).
• Developing AI tools that analyze medical images for faster and more accurate results.

2. What is the utility of IBIA?
The IBIA is an online, comprehensive, scalable, and user-centric digital platform developed to:

• Capture, organize, and store biological images.
• Ensure data standardization (e.g., REMBI guidelines).
• Promote collaboration between the scientific community through data sharing.
• Provide benchmark datasets for training, validation and comparing AI/ML models.
• Facilitate the discovery and reuse of image data across domains.
• Ensure persistent availability of biological images data at a central portal (for open or controlled access).

3. What type of images are accepted through IBIA?
Almost all types of biological images can be accepted at IBIA. From clinical, veterinary studies to agricultural innovation, IBIA is designed to support a wide spectrum of disciplines and imaging modalities, including but not limited to:

• Visible light photography
• Digital X-ray
• Histopathology
• Microscopy
• CT, PET, and MRI Scans
• Ultrasound, ECHO, ECG, EEG
• Mammography, Endoscopy
• Multispectral and hyperspectral Imaging
• Ophthalmic Imaging
• Unmanned Aerial Vehicle (UAV) images for agriculture

4. Who can contribute to the development of IBIA?
The development of IBIA is inherently interdisciplinary and requires contributions from a diverse group of stakeholders. Here's a breakdown of who can contribute and how they can be involved:

• Life Science Researchers & Biologists: Upload biological images (e.g., microscopy, histology, plant pathology), provide metadata and experimental context.
• Clinicians & Medical Institutions: Source of real-world medical image data, can share anonymized clinical imaging datasets (e.g., X-rays, CT scans, MRIs).
• Agriculture and Environmental Scientists: Submit images of crops, diseases, pests, soil conditions, etc. upload drone/UAV-based or satellite imagery.
• Data Scientists & AI/ML Developers: Platform enhancers and image-data consumers, help validate and benchmark AI models using archive data.
• Database Architects & Metadata Specialists: Ensure data is structured, findable, and interoperable.
• Microscopy & Imaging Specialists: Advise on standardization for imaging protocols, train users in high-resolution or specialized imaging techniques.
• Academia & Educational Institutions: Contributors and users of open image data, use datasets for teaching and curriculum development.
• Policy Makers & Funding Agencies: Fund infrastructure and capacity building, mandate open-access data policies, promote ethical data sharing and privacy compliance.

5. How IBIA is transforming life science data?
The image datasets from IBIA are routinely used to derive innovations in various sectors of the life sciences, including healthcare, agriculture, etc. Recently, an image dataset containing “histopathological images of thyroid lesions” (available from the IBIA with Study ID: HISTOS_1000000014; https://ibdc.dbtindia.gov.in/ibia/studybrowse/), was used to develop a novel deep learning (DL)-based, three-stage diagnostic pipeline for distinguishing non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) from a wide spectrum of thyroid lesions, including benign and malignant mimics. For more details about the developed pipeline, you may like to read the published article at https://link.springer.com/article/10.1007/s12022-025-09865-0.

6. What are the policies for sharing/accessing the data at IBIA?
IBIA follows the Department of Biotechnology (DBT), Govt. of India's Framework for Exchange of Data (FeED) Protocols guidelines for data sharing/accessing. You like to read the FeED Protocols guidelines at this clickable link.

7. How to cite the datasets used from IBIA?
If you are using any of the image dataset(s) from IBIA in your study or work, please cite us in the format given below and inform us at ibiasupport@ibdc.rcb.res.in.
Citation format: The data is available at the Indian Biological Images Archive (IBIA) of Indian Biological Data Centre (IBDC) https://ibdc.dbtindia.gov.in/ibia/ with IBIA Project accession no. IBIAP_xxxxxxxxxx and Study accession no. #S_xxxxxxxxxx.
Note: # represents the IBIA imaging type abbreviation.
Tip: Replace the placeholder accession numbers with the actual accession numbers assigned to your dataset when preparing manuscripts or supplementary materials.