Blockchain Value

Transforming Business Models, Society, and Communities

Olga V. Mack

• Publisher: Business Expert Press
• Year: 2020
• ISBN:
  9781952538254
• Topic: Business
• Subtopic: Entrepreneurship
• Index: Business

This book focuses on the values of blockchain across industries.

If you think that blockchain is everything you don't understand about technology, finance, and law mixed together, then this book will help you appreciate its value more clearly. While it is a complex technology that is still largely experimental today, it will be transformative in the future.

This book focuses on the values of blockchain across industries. Among other things, it explores how blockchain technology adds value to data management, security, and sharing as well as ownership, property, collaboration, and trust. It also explores the possibilities of the Blockchain-as-a-Service (BaaS), digital goods or dGoods, and the transformative power of small acts and micropayments.

CHAPTER 1

Stumbling upon Digital Gold: Tapping into Data’s Potential for Management, Security, and Sharing

DADA Collective: Otro Captore, Chile / Massel Quispe, Peru., collaboratively created using blockchain technology, a visual conversation.

The Internet is currently a gold mine of data waiting to be discovered, and transformed into a usable form. The modern economy is data driven because data is valuable to employers and business leaders—it empowers them to make decisions based on facts, not guesses. Marketing departments use market segmentation data to identify new, eager customers. Human resources professionals gather data to recruit the best talent and verify their qualifications. Business executives examine macro trends to make sure that their products and services are relevant—and rely on aggregations to do so. The returns and savings on data usage are unprecedented and worth pursuing.

You’ve probably heard the term “big data” recently. It’s mostly an imaginary category. There’s no threshold that makes data “big.” But the term is helpful because it represents the increasing volumes and the varied types of data that are gathered, as well as data’s importance in our lives.

In the world of “big data,” there are two basic types of data: Human-readable data (also known as unstructured data) is information that only humans can interpret, whereas machine-readable data (or structured data) is information that a computer can process. Because computer processing is cheaper and much more efficient than human processing, structured data is especially valuable to scaling modern businesses.

Both structured and unstructured data fall into at least one of the following four categories:

• Personal data—it is specific to you and includes information like your demographics, your location, your e-mail address, and other identifying factors.

• Transactional data—it is anything that is created when you undertake some action—and leave a footprint behind. For example, when you click on an ad, or make a purchase, or even just visit a web page, you are creating transactional data.

• Web data—it refers to data that you could pull from the Internet, such as data on what your competitors are selling, published government data, or even basketball scores.

• Sensor data—it is data produced by objects such as thermostats or cars in interaction with their environment. These objects are often referred to as composing the Internet of Things (IoT).

Sifting through the data noise and getting relevant, not to mention accurate, information is not a simple task.

As you can imagine, there is a huge quantity of potential data out there. Sifting through the noise and getting relevant, not to mention accurate, information is not a simple task. Numerous professions, books, and conferences are dedicated to collecting, organizing, and interpreting data. Moreover, data collection, especially of personal data, is highly regulated in most countries. For example, the complexities of European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) are legendary.

Blockchain and data is a marriage made in heaven! They really complete each other.

It turns out that blockchain and data are a marriage made in heaven! They really complete each other. Blockchain can help data develop integrity and quality, secure in a more systematic way, track more easily, streamline sharing, generate trust, and analyze in real time.1 This chapter traces businesses on the intersection of blockchain and data, specifically, how they use blockchain technology to manage, secure, and share data.

Data Management: Good Data + Censors = Magic

Blockchain provides numerous advantages for data management. Blockchain’s key characteristics, including decentralized control; a secure and tamperproof infrastructure built on cryptography, transparency, durability, and robustness; and confidentiality, make it an ideal supplement to the existing tools for data management. It has what everyone in data management wants: data with complete provenance. It shows who did what, when, and how, and is verified by all participants.2 This is a timely trend, especially in the increasing reality and importance of artificial intelligence (AI) and IoT, both of which rely heavily on data.

Data to a More Sustainable Future

Meet Kat Leigh,3 the founder of SmallScaleOceanAction (SmallScaleOA), a circular economy for coastal data. Kat aims to use distributed ledger technology to incentivize traceable, transparent seafood, as well as inclusive, low-cost coastal research on a hyperlocalized scale.

According to Leigh, roughly half of the world’s seafood comes from the chronically overlooked small-scale sector, which employs around 90 percent of fishers worldwide. Roughly 85 percent of the world’s fishers and aquaculturists live in Asia. Indonesia, with its many islands and long coastline, is an especially critical supplier of seafood to the rest of the world.

Leigh says, “The seafood industry needs cheap, yet reliable information to monitor their operations, inform zonal management, provide evidence of compliance, and identify risk factors and associated mitigation/adaptation strategies.” Yet data is sorely lacking.

A fine example of a small-scale fishing boat in the Philippines.

SmallScaleOA hopes to completely transform coastal communities and the seafood industry. It can enhance fisheries and farm productivity and efficiency; zonal management and marine spatial planning; product transparency/traceability for government or business quality and safety programs, or certification schemes; and even provide access to insurance, capital, investment, and financial services.

Morning landing of tuna catches in the Philippines.

She noted,

The more I learned about the Southeast Asian seafood industry, the more I realized that it is really a global center of seafood production. Indonesia is the second-largest producer of wild-caught seafood and the third largest in aquaculture. The potential benefit that could be generated by doing work in that region is what attracted me in the first place and has kept me going since. If we want to make an impact, this is certainly where we need to take action.

Weighing and logging catch data.

Why is Leigh so persistent and eager? Why did she pursue blockchain learning despite the very high learning barriers? Simple—the problem is big, solving it will have a huge impact, and Leigh is passionate about the cause. She observes,

It’s also worth noting that 97 percent of our fishers are in developing countries. When you think about massive boats going out there and collecting huge tons of fish, that is not the lion’s share of seafood that’s being pulled out of the ocean. This has major socioeconomic implications. There are a lot of issues, too. One-third of the products are mislabeled. We have illegal unreported undocumented fishing (IUU) and human rights violations.

According to Leigh, most places don’t have catch data. Plus, there’s global warming’s evil twin: ocean acidification, the decline in oceans’ pH caused by carbon dioxide emissions. In the end, many of the ocean’s issues are due to the connections between our food system and the natural infrastructure. Of course, the ocean isn’t just getting more acidic; it’s also getting warmer. Leigh explains,

Even though the ocean has been absorbing some carbon dioxide, our planet is still warming up, and doing so at an alarming rate. It’s causing a change in sea surface temperature. The oceans have been heating 40 percent faster on average than a United Nations panel estimated 5 years ago. The rate is unprecedented.

What if we could link data on these phenomena to the decisions that our businesses, governments, and communities make? Leigh explains,

If we’re going to try to monitor all these crazy, scary changes, we need to fix the gaps in collecting this information and being able to act on it. Especially in the most severely impacted regions of the world. What are the obstacles to this? If you’re trying to measure ocean acidification, you don’t just measure pH; you need to measure two out of the six carbonate parameters. There are lots of different ones.

According to Leigh, “It is hard to scale this type of measurement. If you want to do it all around the world all the time, you’d have to have tons of people constantly taking samples.” Leigh jokes,

I don’t even think if you deployed every single grad student, you’d be able to exploit their labor enough to get those parameters. Autonomous sensors for things like pH and dissolved oxygen are new; and all are really expensive. There are a lot of obstacles to collecting this information, which is unfortunate because it’s so valuable.

Another problem is interoperability. The sensors that are used are often produced by private companies that custom develop products for specific research based on request. Leigh explains,

If you’re a PhD or a postdoc, you have your research question, you talk to a company, and they build a product for that one research study. Again, that doesn’t scale well. It’s extremely inefficient. These are also private companies that understandably seek to profit off their sensors. So they’re not sharing information, and it prevents technology from moving forward.

Leigh’s vision is simple, “What if we could break that silo down and actually allow these companies to share their information and move technology forward? What if we could combine different innovations together and allow them to be mass produced more cheaply?”

The goal...