这是一系列介绍项目的文章的一部分，这些项目是在2020年谷歌代码之夏(GSoC)和Outreachy期间由创作共用指导的开源贡献者构建的。卡塔尔vs葡萄牙分析Subham Sahu是这些贡献者之一，我们非常感谢他在这个项目上所做的工作。
The CC Catalog data visualization—theLinked Commons 2.0—is a web application which aims to showcase and establish a relationship between the millions of data points of CC-licensed content using graphs. In this blog, I’ll discuss the motivation for this visualization and explore the latest features of the newest edition of the Linked Commons.
Motivation
The number of websites using CC-licensed content is enormous, and snowballing. TheCC Catalogcollects and stores these millions of data points, and eachnode(aunit in a data structure)contains information about the URL of the websites and the licenses used. It’s possible to do rigorous data analysis in order to understand fully how these are interconnected and to identify trends, but this would be exclusive to those with a technical background. However, by visualizing the data, it becomes easier to identify broad patterns and trends.
例如，通过识别链接到你的内容的其他网站，你可以尝试有一个特定的扩展计划或与他们合作。通过这种方式，从网络上数十亿的网页中，你可以非常有效地关注那些你更有可能看到增长的网页。
Latest Features
Let’s look at some of the new features in theLinked Commons 2.0.
- Filtering based on the node name
The Linked Commons 2.0 allows users to search for their favorite node and then explore all of that node’s neighbors across the thousands present in the database. We have color-coded the links connecting the neighbors to the root node, as well as the neighbors which are connected to the root node differently. This makes it immaculately easy for users to classify the neighbors into two categories.
- A sleek and revamped design
The Linked Commons 2.0 has a sleek design, with a clean and refreshing look along with both a light and dark theme.
- Tools for smooth interaction with the canvas
The Linked Commons 2.0 ships with a few tools that allow the user tozoom in,zoom out, andreset zoom只需轻轻一击。它对使用触控设备或触摸板的用户尤其有用。
- Autocomplete feature
The current database of the Linked Commons 2.0 contains around 240 thousand nodes and 4.14 million links. Unfortunately, some of the node names are uncommon and lengthy. To prevent users from the exhausting work of typing complete node names,this version ships with anautocomplete feature: for every keystroke, node names will appear that correspond with what the user might be looking for.
What’s next for the Linked Commons?
在当前版本中，有些节点的连接非常密集。例如，节点“Wikipedia”有大约89k个节点和102k个链接作为邻居。这个数字太大了，网页浏览器无法呈现。因此，我们需要配置一种方法来减少到一个更合理的数字。
During the preprocessing, we dropped a lot of the nodes and removed more than 3 million nodes which didn’t have CC license information. In general, the current version shows only those nodes which are soundly linked with other domains and their licenses information is available. However, to provide a more complete picture of the CC Catalog, the Linked Commons needs additional filtering methods and other tools. These potentially include:
- filtering based on Top-Level domain
- filtering based on the number of web links associated with a node
Contributing
我们计划继续在关联公地方面开展工作。You can follow the project development by visiting ourGitHub repo. We encourage you to contribute to the Linked Commons, by reporting bugs, suggesting features or by helping us write code. The new Linked Commons makes it easy for anyone to set up the development environment.
The project consists of a dedicated server which powers the filtering by node name and query autocompletion. The frontend is built using ReactJS, for smooth rendering performance. So, it doesn’t matter whether you’re a frontend developer, a backend developer, or a designer: there is some part of the Linked Commons that you can work on and improve. Welook forward to seeing you on board with sparkling ideas!
We are extremely proud and grateful for the work done by Subham Sahu throughout his 2020 Google Summer of Code internship. We look forward to his continued contributions to the Linked Commons as aproject core committerin the CC Open Source Community!
Please consider supporting Creative Commons’ open source work on GitHub Sponsors.
