Data provenance tracking in analyses

Introduction

Data provenance tracking refers to the systematic recording of the origin, ownership, collection method, processing history, modification, and use of data throughout its lifecycle. It helps establish where information originated, who collected it, what changes were made, and how the final analytical results were produced.

In biotechnology, pharmaceutical research, healthcare, agricultural science, and genetic engineering, data provenance is particularly important because research conclusions may influence medical decisions, regulatory approvals, patents, and commercial products.

For example, when a laboratory analyses genetic information obtained from biological samples, provenance tracking can establish the source of the samples, consent conditions, laboratory procedures, software used, and modifications made to the resulting datasets. It therefore supports scientific reliability, legal accountability, and research transparency.

Legal framework governing data provenance

1. Digital Personal Data Protection Act, 2023

The DPDP Act establishes obligations concerning the lawful processing and protection of digital personal data in India. Section 8 requires Data Fiduciaries to comply with applicable statutory obligations and implement reasonable security safeguards.

Although the Act does not expressly establish a complete data provenance framework, maintaining records of data collection, processing, access, and disclosure can help organisations demonstrate accountability and compliance.

Its application must be considered alongside the relevant commencement notifications and applicable rules.

2. Information Technology Act, 2000

The Information Technology Act provides legal recognition to electronic records and addresses unauthorised access and misuse of computer systems.

Section 43 provides civil liability for specified unauthorised activities involving computer systems, while Section 66 addresses certain such activities when committed dishonestly or fraudulently. These provisions may become relevant where research datasets are manipulated, accessed without authority, or unlawfully altered.

3. Bharatiya Sakshya Adhiniyam, 2023

The Bharatiya Sakshya Adhiniyam, effective from 1 July 2024, recognises electronic and digital records as evidence. Sections 61–63 address their admissibility and evidentiary requirements.

Data provenance records, audit trails, timestamps, access logs, and digital verification records may help establish the authenticity and reliability of electronic evidence in legal proceedings.

4. General Data Protection Regulation (GDPR)

The GDPR establishes principles of accountability, transparency, accuracy, and data minimisation. Article 5 requires personal data to be processed fairly and accurately. Article 30 requires certain organisations to maintain records of processing activities, while Article 32 requires appropriate security measures.

These provisions support systematic documentation of personal-data processing.

Importance of data provenance tracking in biotechnology

Data provenance is essential in biotechnology because scientific research frequently involves multiple laboratories, institutions, databases, and technology providers.

For example, a clinical research project may collect patient information from hospitals, process samples in laboratories, and analyse results using artificial intelligence. Provenance tracking can identify:

The original source of biological samples and related information.

The consent and legal conditions governing data collection.

The researchers and institutions accessing the information.

The software, algorithms, and analytical methods used.

Any corrections, transformations, or modifications.

The final use of research results in publications or commercial applications.

This information helps prevent fabricated results, unauthorised alterations, duplication, and disputes regarding scientific ownership.

Methods of maintaining data provenance

1. Metadata documentation

Metadata records describe the source, format, collection date, creator, and relevant characteristics of a dataset. They help researchers understand the background and limitations of the information being analysed.

2. Audit trails

Audit trails maintain records of access, modifications, deletions, and transfers. They help identify who performed particular actions and when they occurred.

3. Blockchain-based records

Blockchain technology can create tamper-evident records of data transactions and transfers. However, blockchain does not automatically guarantee that the original information is accurate or lawfully obtained.

4. Digital signatures and timestamps

Digital signatures and trusted timestamps can help verify the integrity and origin of electronic records. They are particularly useful for research documentation and regulatory submissions.

5. Standardised research documentation

Institutions should maintain standard operating procedures, laboratory notebooks, sample identifiers, analytical protocols, and version histories. These records help reproduce experiments and verify research findings.

Relevant case laws

There are limited judicial decisions directly addressing data provenance tracking in scientific analyses. However, the following judgments provide relevant legal principles.

1. Anvar P.V. v. P.K. Basheer (2014)

The Supreme Court of India examined the admissibility of electronic records under Section 65B of the former Indian Evidence Act. The judgment established the importance of complying with statutory requirements when electronic records are produced as evidence. Its principles are relevant to preserving reliable digital research records, subject to the current Bharatiya Sakshya Adhiniyam framework.

2. Arjun Panditrao Khotkar v. Kailash Kushanrao Gorantyal (2020)

The Supreme Court clarified the requirements for admitting electronic evidence under the former Section 65B. The decision highlights the importance of authenticity, certification, and proper handling of electronic records. These principles are relevant to laboratory databases and digital audit trails.

3. Justice K.S. Puttaswamy v. Union of India (2017)

The Supreme Court recognised privacy as a fundamental right under Article 21. The judgment supports responsible handling of personal information and provides an important constitutional foundation for maintaining lawful records of data collection and processing.

4. Daubert v. Merrell Dow Pharmaceuticals, Inc. (1993)

The United States Supreme Court established standards for assessing the reliability and scientific relevance of expert evidence. The decision is relevant to scientific analyses because transparent methodologies, reliable procedures, and verifiable research processes strengthen the credibility of expert conclusions.

These judgments provide analogous principles; they do not directly establish a comprehensive legal duty to maintain data provenance records.

Legal challenges and compliance requirements

Data provenance tracking creates several legal and operational challenges. Organisations must protect confidential information while maintaining sufficient documentation to demonstrate the reliability of research.

Important compliance measures include:

Maintaining complete records of data collection and modification.

Recording consent and applicable restrictions on biological information.

Preserving secure and tamper-evident audit trails.

Establishing clear responsibilities among researchers and institutions.

Protecting sensitive personal and genetic information.

Maintaining documented analytical methods and software versions.

Establishing procedures for correcting inaccurate or incomplete datasets.

Conclusion

Data provenance tracking is an important component of scientific accountability and legal compliance. It establishes the origin, history, integrity, and authorised use of information throughout the analytical process. In biotechnology and healthcare research, it helps verify experimental findings, protect sensitive information, resolve ownership disputes, and support regulatory investigations. Although Indian law does not provide a single comprehensive statute specifically governing data provenance, data protection legislation, electronic evidence requirements, intellectual property law, and contractual obligations collectively provide an important regulatory foundation.