⛓️datachain
datachain is a community run project of the cloutcoin protocol. Its main feature will be to mine valuable data locked in legacy internet, social media, and web 2.0 infrastructure. Once the data has been mined by participants, it will become publicly available in the research center. Miners will be incentivized to participate by receiving protocol rewards.
INDEX
Features & Methods
Network Analysis
Network analysis (NA) is a set of integrated techniques to depict relations among actors and to analyze the social structures that emerge from the recurrence of these relations.
Network analysis is a set of techniques derived from network theory, which has evolved from computer science to demonstrate the power of social network influences. Using network analysis in domain analysis can add another layer of methodological triangulation by providing a different way to read and interpret the same data. The use of network analysis in knowledge organization domain analysis is recent and is just evolving. The visualization technique involves mapping relationships among entities based on the symmetry or asymmetry of their relative proximity. For example, the network map in Figure 4.35 was developed using Gephi, an open source network visualization platform (http://gephi.github.io/). This network visualization is based on an author cocitation matrix from research that cites famed Indian scientist S.R. Ranganathan. The map appeared in Smiraglia (2013, p. 715). The visualization was developed using the Force Atlas 2 algorithm in Gephi 0.8.2. The technique involves changing the original matrix into a network file, and then using Gephi to enhance the visualization.
The complexity of the network map helps us visualize the degree of interconnectedness among the thematic clusters represented by cocited authors. Instead of clusters we see network pathways, as though in a street map. We can see, for example, that although everyone is connected in some way in this map, some are only barely connected while others are closely interconnected. The different densities of the connecting edges help us visualize the relative strength of the associations.
Richard P. Smiraglia, in Domain Analysis for Knowledge Organization, 2015
Blockchain Oracle
A blockchain oracle is a third-party service that connects smart contracts with the outside world, primarily to feed information in from the world, but also the reverse. Information from the world encapsulates multiple sources so that decentralised knowledge is obtained. Information to the world includes making payments and notifying parties. The oracle is the layer that queries, verifies, and authenticates external data sources, usually via trusted APIs, proprietary corporate data feeds and internet of things feeds and then relays that information.
Examples
Many Ethereum applications use oracles. For example, prediction market Augur would use election data to settle corresponding bets. Projects like Chainlink provide decentralized oracle network services to many different blockchains.
Examples of data transmitted by oracles to smart contracts include price information, the successful completion of a payment, the temperature measured by a sensor, election outcomes etc. Data can be supplied by other software (databases, servers, or essentially any online data source), or by hardware (sensors, barcode scanners etc.). A hardware oracle can be seen as relaying real-world events into digital values that can be understood by smart contracts. Both types are inbound oracles. Human oracles are individuals with specialized knowledge who can verify the authenticity of information before relaying it to smart contracts,[1] and who prove their identity cryptographically.
Outbound oracles send information from smart contracts to the external world. For example, a smart contract receiving a payment could send information through an outbound oracle to a mechanism that unlocks a smart lock.
Data Scraping
Data scraping is a technique where a computer program extracts data from human-readable output coming from another program.
Web scraping[edit]
Web pages are built using text-based mark-up languages (HTML and XHTML), and frequently contain a wealth of useful data in text form. However, most web pages are designed for human end-users and not for ease of automated use. Because of this, tool kits that scrape web content were created. A web scraper is an API or tool to extract data from a web site. Companies like Amazon AWS and Google provide web scraping tools, services, and public data available free of cost to end-users. Newer forms of web scraping involve listening to data feeds from web servers. For example, JSON is commonly used as a transport storage mechanism between the client and the webserver.
Recently, companies have developed web scraping systems that rely on using techniques in DOM parsing, computer vision and natural language processing to simulate the human processing that occurs when viewing a webpage to automatically extract useful information.[5][6]
Large websites usually use defensive algorithms to protect their data from web scrapers and to limit the number of requests an IP or IP network may send. This has caused an ongoing battle between website developers and scraping developers.[7]
Peer-to-peer (P2P)
Peer-to-peer (P2P) computing or networking is a distributed application architecture that partitions tasks or workloads between peers. Peers are equally privileged, equipotent participants in the application. They are said to form a peer-to-peer network of nodes.[1]
Peers make a portion of their resources, such as processing power, disk storage or network bandwidth, directly available to other network participants, without the need for central coordination by servers or stable hosts.[2] Peers are both suppliers and consumers of resources, in contrast to the traditional client–server model in which the consumption and supply of resources is divided.[3]
While P2P systems had previously been used in many application domains,[4] the architecture was popularized by the file sharing system Napster, originally released in 1999.[5] The concept has inspired new structures and philosophies in many areas of human interaction. In such social contexts, peer-to-peer as a meme refers to the egalitarian social networking that has emerged throughout society, enabled by Internet technologies in general.
IPFS (InterPlanetary File System)
IPFS is a distributed system for storing and accessing files, websites, applications, and data.
What does that mean, exactly? Let's say you're doing some research on aardvarks. (Just roll with it; aardvarks are cool! Did you know they can tunnel 3 feet in only 5 minutes?) You might start by visiting the Wikipedia page on aardvarks at:
When you put that URL in your browser's address bar, your computer asks one of Wikipedia's computers, which might be somewhere on the other side of the country (or even the planet), for the aardvark page.
However, that's not the only option for meeting your aardvark needs! There's a mirror of Wikipedia stored on IPFS, and you could use that instead. If you use IPFS, your computer asks to get the aardvark page like this:
The easiest way to view the above link is by opening it in your browser through an IPFS Gateway. Simply add https://ipfs.io to the start of the above link and you'll be able to view the page →(opens new window)
IPFS knows how to find that sweet, sweet aardvark information by its contents, not its location (more on that, which is called content addressing, below). The IPFS-ified version of the aardvark info is represented by that string of numbers in the middle of the URL (QmXo…), and instead of asking one of Wikipedia's computers for the page, your computer uses IPFS to ask lots of computers around the world to share the page with you. It can get your aardvark info from anyone who has it, not just Wikipedia.
And, when you use IPFS, you don't just download files from someone else — your computer also helps distribute them. When your friend a few blocks away needs the same Wikipedia page, they might be as likely to get it from you as they would from your neighbor or anyone else using IPFS.
IPFS makes this possible for not only web pages but also any kind of file a computer might store, whether it's a document, an email, or even a database record.
Decentralization
Making it possible to download a file from many locations that aren't managed by one organization:
Supports a resilient internet. If someone attacks Wikipedia's web servers or an engineer at Wikipedia makes a big mistake that causes their servers to catch fire, you can still get the same webpages from somewhere else.
Makes it harder to censor content. Because files on IPFS can come from many places, it's harder for anyone (whether they're states, corporations, or someone else) to block things. We hope IPFS can help provide ways to circumvent actions like these when they happen.
Can speed up the web when you're far away or disconnected. If you can retrieve a file from someone nearby instead of hundreds or thousands of miles away, you can often get it faster. This is especially valuable if your community is networked locally but doesn't have a good connection to the wider internet. (Well-funded organizations with technical expertise do this today by using multiple data centers or CDNs — content distribution networks (opens new window). IPFS hopes to make this possible for everyone.)
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