(The Decentralized Platform for Heavy Research Data Management - Storage and Sharing)

Chapter 1: Introduction - Blockchain in Research Data Sharing

The volume of research data being generated is exploding exponentially. Studies estimate a 48% annual growth rate as technologies like DNA sequencing, telescopes, particle colliders, and complex simulations produce oceans of data. Meanwhile, funders and publishers are mandating open data sharing for transparency and reproducibility. This poses major challenges around storing, managing, disseminating, and extracting value from massive heterogeneous datasets. There is an urgent need for secure, scalable, and cost-effective solutions that give researchers control over their data.

Sia offers a uniquely compelling answer to this need through decentralized cloud storage built on blockchain. By adopting Sia, researchers can achieve reliable and affordable data storage with fine-grained control over sharing and dissemination. This proposal outlines our plan to drive Sia's adoption as the go-to platform for revolutionizing how researchers across disciplines manage, collaborate on, and extract insights from data.

Chapter 2: The Technical Plan / Roadmap:

Background on Research Data Management Challenges:

The exponential growth in data combined with open science mandates has created pressing needs that legacy solutions fail to address adequately:

1. Data Volumes: Large Hadron Collider experiments generate 15 petabytes annually. Genomics datasets exceed an exabyte. These massive amounts require highly scalable and affordable infrastructure.
2. Privacy Protection: Human subject studies require strong safeguards around personal information with granular access controls and auditing.
3. Selective Sharing: Researchers need to share data while preventing full public downloads in order to protect unpublished intellectual property.
4. Regulatory Compliance: Regulations like HIPAA govern sensitive health data. Requirements include encryption, access controls, consent management, and data residency.
5. Rising Costs: Storing terabytes in the cloud carries substantial costs, straining research budgets and restricting data collecting and sharing.
6. Disjointed Tools: Managing research data requires stitching together many fragmented point solutions rather than one cohesive platform. This hinders productivity.
7. Data Reuse and Integration: Maximizing the value of research data requires interoperable formats and rich metadata for discovery and integration across datasets.

These systemic problems significantly impede scientific progress, collaboration, validation, and knowledge discovery. Existing solutions only address subsets of the challenges and no unified platform yet exists.

How Sia Addresses Research Data Management Needs:

Sia offers a unique combination of capabilities highly suited to addressing research data challenges:

1. Decentralized Storage: Data redundancy across many hosts ensures resilience without single points of failure.