Guides: Metadata & Discovery @ Pitt: Linked Data and the Semantic Web (2024)

FAQs

What is the relationship between linked data and the Semantic Web? ›

Linked Data is one of the core pillars of the Semantic Web, also known as the Web of Data. The Semantic Web is about making links between datasets that are understandable not only to humans, but also to machines, and Linked Data provides the best practices for making these links possible.

In summary, semantic metadata is the description of the meanings of values and of the names of data components, at least for human reference and possibly for programmatic use as well.

Metadata Discovery is the process of automatically identifying, extracting, and organizing metadata from various data sources. Metadata refers to data that describes other data, providing context, and information about the data's structure, content, relationships, and lineage.

Examples of large linked open data sets include DBpedia and Wikidata. A suite of semantic web standards developed by the Worldwide Web Consortium (W3C). These standards create a structure for making simple statements about resources so that machines can interpret relationships.

Linked data represent a radical shift in the way structured data can be created to express information about resources. Instead of a record-based model governed by a schema, it focuses on smaller chunks of meaningful metadata that can be linked and queried.

You get information when data is processed, organized, interpreted, and structured. The comprehensible output derived from raw data helps inform decisions, strategies, and actions. Information is essentially data made valuable and accessible—an integral component of decision-making.

Metadata makes finding and working with data easier – allowing the user to sort or locate specific documents. Some examples of basic metadata are author, date created, date modified, and file size. Metadata is also used for unstructured data such as images, video, web pages, spreadsheets, etc.

The table row and column headers in a spreadsheet are examples of metadata as they offer context to the data. Other metadata examples include: Number of rows and columns. Source descriptions and relationships.

Metadata means "data about data". Metadata is defined as the data providing information about one or more aspects of the data; it is used to summarize basic information about data that can make tracking and working with specific data easier. Some examples include: Means of creation of the data. Purpose of the data.

It enhances the usefulness of your data or information by providing context—the who, what, when, where, why, and how that helps to discover, identify, interpret, and interact with content. Metadata allows users to: Find or identify a resource. Know who created the resource or contributed to the creation of the resource.

What is the difference between data and metadata? ›

Data is a set of raw facts that help identify useful information when they are cleaned, processed, and organized. Metadata, on the other hand, is data about data. If data is the new oil, metadata is the refinery. Without metadata, there is no way to understand or use the data in hand.

There are three main types of metadata: descriptive, administrative, and structural. Descriptive metadata enables discovery, identification, and selection of resources. It can include elements such as title, author, and subjects. Administrative metadata facilities the management of resources.

The Semantic Web is a vision about an extension of the existing World Wide Web, which provides software programs with machine-interpretable metadata of the published information and data. In other words, we add further data descriptors to otherwise existing content and data on the Web.

Linked Data builds upon standard Web technologies such as HTTP and URIs, but rather than using them to serve web pages for human readers, it extends them to share information in a way that can be read automatically by computers. This enables data from different sources to be connected and queried.

Therefore, semantic mapping (linking of data concepts with ontology classes) not only helps machines to interpret the heterogeneous big data to comprehend the corresponding context but can also help to detect big data anomalies and complete the missing information.

Semantics is related to etymology, which studies how words and their meanings changed in the course of history. Another connected field is hermeneutics, which is the art or science of interpretation and is concerned with the right methodology of interpreting text in general and scripture in particular.

The Semantic Web is a vision for linking data across webpages, applications and files. Some people consider it part of the natural evolution of the web, in which Web 1.0 was about linked webpages, Web 2.0 was about linked apps and Web 3.0 is about linked data.

The role of ontologies in Semantic Web is to facilitate data organization and integration [14]. This integrated data (known as Linked Data) which can be used for reasoning or simply querying is the main strength of the Semantic Web.