Data collaboration is a common need in many research fields, but in the real world, it faces many development and deployment challenges. We introduce CoLink, which is a simple, secure, and flexible decentralized programming abstraction, and introduce CoLearn, which is a platform on top of CoLink for decentralized data science. We motivate our design with our experience in building real-world decentralized data collaboration applications. We give details about our construction and explain how it simplifies and accelerates the development of cryptographic and distributed protocols. We also provide examples of coding in CoLink. With a unified interface that increases potential data and coding contributors, we hope to reduce data collaboration solution building time from months to seconds and enable larger-scale decentralized data collaboration solutions to unlock the true value of data.