Ideas = Products, = Platforms/Protocols
Developers have been building ideas behind centralized, closed walls.
Open-Source development opens the development process to the public, for a collaborative effort.
In web3, with blockchain’s decentralized and transparent nature, its activities and engagement data are open to the public, for analysts to analyze for actionable intelligence.
This digital renaissance era is quite interesting.
Open-Source for Developers = Open-Data for Analysts
💡 Ideas = Products = Platforms, now Protocols
In the past, in web1, developers with HTML and JSS technical know-how built websites for corporations, and themselves.
In web2, with additional Javascript knowledge, the developers added interactivity to websites and brought about interaction, engagement, and discourse on websites leading to platforms ideas like FaceBook (now Meta, for social media), Google (Search), Amazon (internet commerce), TikTok (video), etc.
Developers create/develop, then rely on analysts to make sense of the data for actionable business insights and intelligence. It has always been so, but as we’d soon see, the paradigm is fast changing.
However, all these idea and platform development was happening behind centralized, closed doors. To combat this, Open-source development is a growing trend in the software development industry.
🔓 What is Open-Source Development?
Open source development is a software development methodology where the source code of a software project is made available to the public, typically within certain boundaries/parameters as described in its open source license. This allows anyone to review, modify, and redistribute the software. Open source development has a number of benefits, including:
Transparency: The software is typically released under an open source license implying the source code is available to anyone, so anyone can see how the software works and modify it under certain boundaries. This helps to build trust in the software and ensures that it is not malicious. The license defines the terms under which the software can be used, modified, and redistributed.
Collaboration: Open source development is often community-driven meaning that software is developed by a community of contributors, rather than by a single company or organization. Anyone can contribute to an open source project, regardless of their skill level. This can lead to faster development and better software.
Innovation: Open source projects are often more innovative than closed source projects. This is because there is a larger pool of contributors who can bring new ideas to the table.
In web3, however, there is a paradigm change. Something quite important is happening. With blockchain technology’s nature of being decentralized and transparent, it means its data is open and publicly available. It means anyone, and I really mean anyone, on any computer, in any locale, can have access to the data at any time of the day. This is Open-Data!
🤔 ❓ What is Open-Data Analytics?
Open data is data that is freely available to anyone to use, to analyze for insights & intelligence. Like open source for developers, It is data openly powered by a community of analyst collaborators.
In web3, with blockchain’s nature of being decentralized and transparent, it means its data is open and publicly available. It means anyone, and really anyone, on any computer, in any locale, can have access to the data at any time of the day. It means the actions, activities, and engagement happening on protocols hosted on blockchain networks like Ethereum are open for public access.
In web3, anyone with data analytics (primarily SQL), dashboarding and storytelling skills, and maybe a bit of writing, can analyze blockchain data, and tell a story with his findings. He could derive insights and intelligence he could act upon, mainly for
Value Investment opportunities
Passive Income Opportunities
General Insights & Intelligence, depending on Depth of Analytics skills and Domain Knowledge
What kind of Data is Open?
High-level, product point-of-contact data is open to the public. That layer where the product interacts with the user base is open to the public. This covers data like transactions volume, value, 0x address, token swapped in or out, token borrowed and lent out, etc.
Now that we know how data is opened in web3, what happens if we combine these two concepts of open-source development and open-data analytics?
When Open-Source 🤝 Open-Data
Understanding that great product ideas are a combination of great development, delightful CX (UI/UX), and customer data intelligence, we can have a depiction of what happens when open development meets great data intelligence.
A developer could use open data about traffic patterns to create a new navigation app. Open data can also be used to improve existing software applications. For example, a developer could use open data about weather patterns to improve the accuracy of a weather forecasting app. There are a number of benefits to using open data in the context of open source.
First, it can help to improve the quality of software applications. When developers have access to open data, they can use it to make their applications more accurate, reliable, and useful.
Second, it can help to reduce the cost of software development. Developers can use open data to avoid having to collect and clean their own data.
Third, it can help to promote innovation. When developers have access to open data, they can use it to create new and innovative applications.
This section “when open source meets open data” still looks at idea development from the perspective of develop first, analyst second. What happens if it is analyst first, and development second? To grasp this, lets combine open data with nocode.
When Open-Data 🤝 NoCode
Here, the view is analysts first, development second.
👎 Limitations to Open-Data
Because the data is open to all, it implies anyone can access and analyze it. This is a good thing, but it invariable brings up the issue of assurance of competency. Without deep knowledge of how blockchain data is stored, how (for example) ethereum data is parsed, what events are emitted, what functions are called, even how the tables are structured, the flow of it all, it is easy for a newbie web3 data analyst to assume/believe that his SQL query is optimized, whereas omitting a variable could throw off the analysis, and hence the insight found. Domain knowledge is needed — on the peculiarities of each blockchain network, and protocols.
The data is open, but the graphical presentations and visualizations could be improved. Bubblemaps seems to be attempting to solve this problem.