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Understanding Blockchain and Data Science Today

March 1, 2022
Tyler Odenthal

The current world of data science and blockchain technology is a vast and highly complex realm that can seem intimidating to anyone not already “in the know” in 2022. So much so that many people probably think they’ll never be able to understand what’s going on, especially with the added complexity that’s hit the scene with the recent boom of decentralized finance, cryptocurrencies, and NFTs. There are so many different elements to keep track of and understand, so it’s easy to get lost and not know where to find answers. 

Thankfully, our team of specialized technology experts here at BirdBot has taken the time to compile some of the essential information you’ll want to know regarding the modern world of blockchain and data science. Please continue to learn the basics and consider exploring their collection of other educational resources to discover how BirdBot is working to power community science and promote a better future for the natural world.

Related: Green Blockchain Revolutionizes Conservation

What to Know About Blockchain

Blockchain can be a complex topic for non-tech-savvy individuals to understand, but we’ll do our best to help make this explanation as straightforward as possible. A blockchain is a kind of database shared along the nodes of a computer network- nodes are computers, servers, or other devices that form the framework of blockchain. Blockchain differs from other types of databases in that it collects and structures data in groups known as blocks, which have specific storage capacities. When filled, blocks are linked to previously filled blocks and form a data chain, thereby creating a blockchain. Blockchains often serve as ledgers to keep records of cryptocurrency transactions, though the technology is gaining other uses.

A computer and tablet showing different types of data.

What to Know About Data Science

Data science has no officially agreed-upon definition. However, in simple terms, it is the discipline of making data useful, which can be done through a variety of methods, including;

  • Statistical inferences: Making one or a few risk-controlled conclusions about the world that go beyond generalizing an analyzed dataset
  • Data mining and descriptive analysis: Exploratory analysis is meant to identify previously unknown data patterns in data and formulate different hypotheses about the underlying causes of those patterns
  • Machine learning and artificial intelligence (AI): Constructing “decision recipes” that technology can repeatedly use to make decisions in an automated fashion 

Small efforts can help shape a better future for our world, and furthering our understanding of human impacts on nature is critical to protecting the environment. The scientific experts here at BirdBot work diligently to help by using specialized technology to renew our connections with nature.

The Connection Between Data Science and Blockchain

An essential component you should keep in mind is that data science and blockchain technologies are made for each other, mainly because blockchains can act as significant sources of information to support data science efforts. Also, compared to other data sources, blockchain offers a range of several unique benefits to the realm of data science, such as; 

  • Traceability: Blockchain records store all information needed to track the origin and context of the data they contain, such as when a transaction was offered, the initiating address, the number of assets involved, and the address which received the assets. Additionally, most publicly available blockchains have explorer websites where anyone can examine these records, providing high levels of transparency and traceability. 
  • High data quality: All new records put onto blockchains must undergo rigorous, blockchain-specific validation testing processes before being approved. Once approved, the records become immutable and cannot be changed or modified for any reason, which helps ensure overall data quality. Blockchain data is well structured and well documented, making data scientists’ jobs much more straightforward.
  • Large data volumes: Various machine learning algorithms require massive amounts of data to develop highly-trained models. Regular data sources often struggle to provide this, but mature blockchains offer access to gigabytes worth of data for machines to learn from.
  • Built-in anonymity: Blockchains don’t require users to provide personal information, which is very important in a world where maintaining one’s privacy has become exceedingly difficult. This helps data scientists by allowing them to bypass the headaches connected to security regulations that require personal data to be made anonymous before processing.

Collecting data from blockchains can be a tricky process. However, data scientists are still able to do it effectively using a range of methods, such as using already prepared datasets, using blockchain-specific ETL or APL tools, or through other types of commercial solutions.

Related: Incentive Structures and Community Science

The Two Blockchain-Related Data Science Applications to Know

Data science applications related to the blockchain can generally be separated into two distinct categories; “in blockchain” and “for blockchain.” Applications that are “in blockchain” are, as the name implies, designed to be part of the blockchain itself. These are typically deployed as smart contracts, a piece of code that occupies its own address and executes a set of predetermined actions in response to contract-specific triggers. Applications that are “for blockchain” are slightly different, and are typically used to do something useful with on-chain (and sometimes off-chain) data. However, the application isn’t necessarily deployed onto the blockchain’s basic infrastructure.

Related: How To Educate and Promote Environmental Awareness in 2021

Two people looking over data displayed on a tablet.

Final Thoughts and Considerations to Keep in Mind

We sincerely hope this article has helped explain the basics of blockchain technology and its connection to the world of data science and that it’s encouraged you to seek out even more information to educate yourself on the topic further. To learn even more and find out how data scientists are using blockchain technology to help improve the world through new and advanced environmental conservation efforts, please consider exploring BirdBot today!

The future of environmental conservation and the evolution of advanced technologies are heavily intertwined, and our experts here at BirdBot are helping lead the way. Please explore our website to learn how we’re attempting to use the blockchain to empower better conservation efforts as you advance through 2022.