More and more websites have started to embed structured data describing products, people, organizations, places, and events into their HTML pages using markup standards such as Microdata, JSON-LD, RDFa, and Microformats. The Web Data Commons project extracts this data from several billion web pages. So far the project provides 12 different data set releases extracted from the Common Crawls 2010 to 2023. The project provides the extracted data for download and publishes statistics about the deployment of the different formats.
Common Crawl - Open Repository of Web Crawl Data
We build and maintain an open repository of web crawl data that can be accessed and analyzed by anyone.
Microformats – building blocks for data-rich web pages
A (very) belated follow up to Getting Started with Microformats 2, covering the basics of consuming and using microformats 2 data. Originally posted on waterpigs.co.uk.
All The Places
A growing set of web scrapers designed to output consistent geodata about as many places of business in the world as possible.
GoodRelations - W3C Wiki
GoodRelations is a lightweight ontology for exchanging e-commerce information, namely data about products, offers, points of sale, prices, terms and conditions, on the Web. It can be used in all RDF syntaxes (like RDF/XML, Turtle, RDFa, JSON-LD, ...), Microdata, and basically any syntax that supports an Entitity-Attribute-Value pattern.
DASL — Data-Addressed Structures & Links
A small set of simple, standard primitives to work on content-addressed data.
DASL — Data-Addressed Structures & Links
A small set of simple, standard primitives to work on content-addressed data.
Research Object Crate (RO-Crate)
RO-Crate is a community effort to establish a lightweight approach to packaging research data with their metadata. It is based on schema.org annotations in JSON-LD, and aims to make best-practice in formal metadata description accessible and practical for use in a wider variety of situations, from an individual researcher working with a folder of data, to large data-intensive computational research environments.
Haystack: A Platform for Authoring End User Semantic Web Applications
The Semantic Web promises to open innumerable opportunities for automation and information retrieval by standardizing the protocols for metadata exchange. However, just as the success of the World Wide Web can be attributed to the ease of use and ubiquity of Web browsers, we believe that the unfolding of the Semantic Web vision depends on users getting powerful but easy-to-use tools for managing their information. But unlike HTML, which can be easily edited in any text editor, RDF is more complicated to author and does not have an obvious presentation mechanism. Previous work has concentrated on the ideas of generic RDF graph visualization and RDF Schema-based form generation. In this paper, we present a comprehensive platform for constructing end user applications that create, manipulate, and visualize arbitrary RDF-encoded information, adding another layer to the abstraction cake. We discuss a programming environment specifically designed for manipulating RDF and introduce user interface concepts on top that allow the developer to quickly assemble applications that are based on RDF data models. Also, because user interface specifications and program logic are themselves describable in RDF, applications built upon our framework enjoy properties such as network updatability, extensibility, and end user customizability – all desirable characteristics in the spirit of the Semantic Web.
Semantic Web
The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable.
Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus
Large language models have led to remarkable progress on many NLP tasks, and researchers are turning to ever-larger text corpora to train them. Some of the largest corpora available are made by scraping significant portions of the internet, and are frequently introduced with only minimal documentation. In this work we provide some of the first documentation for the Colossal Clean Crawled Corpus (C4; Raffel et al., 2020), a dataset created by applying a set of filters to a single snapshot of Common Crawl. We begin by investigating where the data came from, and find a significant amount of text from unexpected sources like patents and US military websites. Then we explore the content of the text itself, and find machine-generated text (e.g., from machine translation systems) and evaluation examples from other benchmark NLP datasets. To understand the impact of the filters applied to create this dataset, we evaluate the text that was removed, and show that blocklist filtering disproportionately removes text from and about minority individuals. Finally, we conclude with some recommendations for how to created and document web-scale datasets from a scrape of the internet.
Dremel: interactive analysis of web-scale datasets: Proceedings of the VLDB Endowment: Vol 3, No 1-2
Dremel is a scalable, interactive ad-hoc query system for analysis of read-only nested data. By combining multi-level execution trees and columnar data layout, it is capable of running aggregation queries over trillion-row tables in seconds. The system ...
This approach to a data commons could extend to so many typically shared things. For businesses to easily and authoritatively publish things like open hours or product catalogs, discographies, every kind of -ography... creative appmakers could do so much with all that
JB Hutch
Testing an idea that I've had for a while, but I think is even better suited for atproto Internet, meet plts.at
