• Blog
  • Informational

A Web of People and Machines: W3C Semantic Web Standards

March 24, 2016 9 mins. read Teodora Petkova

Weaving the web

It’s 1989. We are at CERN, the European Organization for Nuclear Research. Physicists and engineers from all over the world have gathered to seek answers to particle physics, bringing a variety of computers, file formats, software and procedures to the site.

The inventor of the World Wide Web, Sir Tim Berners-Lee is also there for a brief consulting job, working on a way to end the mess, caused by the incompatibility of formats, networks and systems.

He is thinking how he can implement his long-thought idea of a software program and design a system that will ease the process of interlinking and organizing information at CERN, by finding a way for computers to communicate indirectly over a network.

As Tim Berners-Lee will later write in his book “Weaving the Web”:

Suppose all the information stored on computers everywhere were linked, I thought. Suppose I could program my computer to create a space in which anything could be linked to anything. All the bits of information in every computer at CERN, and on the planet would be available to me and to anyone else. There would be a single , global information space.

It was that same desire of linking anything to anything that grew into a proposal, issued to CERN in 1990: Information Management: A Proposal and was the conceptual basis that further gave rise to the World Wide Web.

Sir Tim Berners-Lee

A World Wide Web later

Fast forward a quarter of a century later. The World Wide Web is already a powerful means for collaboration, connecting people from all over the world, letting everyone publish, share, access use and reuse documents and files with of all conceivable formats. Cooperation between people is made easy and so is the transfer of all kinds of content. What Sir Tim Berners-Lee envisioned has come true. Partly, though.

Now that the cooperation between people has become effortless in many ways, it is the communication of computer systems capable of understanding the mountains of data put on the Web that will truly unfold the potential of the Web. Click To Tweet

As far as data are concerned, however, the same daunting task of managing, sharing, reusing and automatic processing is before us. Only this time it has to do with bringing collaboration to the next level and linking anything to anything on data level.

For that to happen, data on the Web are to be put in an understandable and processable by machines form and not locked into siloed, proprietary data formats that impede knowledge storage, access and retrieval.

But what is the road to integration and interoperability of data? What will make for a common framework that will facilitate the sharing and reuse of data by computers, the way the common language HTML allowed them to share and represent hypertext?

HTML

A Web of People and Machines: The Semantic Web Vision

Only when we have this extra level of semantics will we be able to use computer power to help us exploit the information to a greater extent than our own reading.

cit. Plenary at WWW Geneva 94 

The inventor of the Web saw it not only as a Web of People, the ultimate goal of which is to “support and improve our weblike existence in the world”, but also as a Web of Machines, where human collaboration is extended through computers. What Tim Berners-Lee envisioned was a global information space in which computers become capable of carrying out sophisticated tasks through analyzing content, links, transactions between people and machines and. This space he called the Semantic Web.

A layer in the fabric of the Web as we know it, only woven of machine-readable data, the Semantic Web is to become a highly interconnected network where the huge amount of heterogeneous data is be given well-defined meaning.

Ultimately, just like we have a web of documents, we will have a web of data that will be processed on our behalf by autonomous agents aware of the context and the meaning of data pieces and able to interpret the relationships among them. Click To Tweet

In order for that vision of the Semantic Web to be fully realized, there need to be formal standards for representing and interpreting data.

Building Bridges Through Global Agreement: W3C and the Semantic Web Standards

The data web, not unlike the document web, involves standards. W3C (The World Wide Web Consortium) is the international community that represents developers, researchers, organizations and users and where Web standards that make the World Wide Web work are being developed.

It is important to mention that the process of the standardization of Web technologies is based on community consensus, that is standards are agreed upon discussions, close collaboration and general agreement between W3C Members, W3C Team and working groups of experts.

In addition to specifications for the “Web of documents”, W3C is dedicated to the development of an ecosystem of standards to support a “Web of data”, i.e. the Semantic Web stack. At the end of 2013, W3C Semantic Web Activity (launched in 2001 “to lead the use of the Web as an exchange medium for data as well as documents”) became part of an initiative with a broader scope, namely W3C Data Activity.

W3C

All We Need is Linked Data

Central to the concept of the Semantic Web is Linked Data. In order for the Semantic Web to function, that is for applications and tools to be able to manage and process data on our behalf, it is important that data pieces are available in a standard format.

Just like there’s lingua franca for representing documents on the Web and that is the Hypertext Markup Language (HTML), a common format for data to be represented and shared exists and it is called Resource Description Framework (RDF). A standard model for data interchange on the Web, RDF, is among the main building blocks of the Semantic Web Stack, together with other Semantic Web technologies, such as OWL, SKOS, SPARQL, etc.

URI, RDF, SPARQL at a glance

Semantic Web technologies have the immense potential to address the need for connected, discoverable and understandable by humans and machines data and empower Linked Data. And Linked Data – together with the precious Linked Open Data, which is a vast subject in its own right – is what makes for more effective discovery, automation, integration and reuse of information.

In the paragraphs below, you will find a short introduction to three of the essential technologies, part of the Semantic Web architecture: URI, RDF and SPARQL.

Naming things (URI)

URI stands for Uniform Resource identifier and it is used to address everything – from documents and digital contents available on the Web to real objects and abstract concepts. Think of it as naming. In order to describe anything or to refer to anything, you need to name it. So, on the Semantic Web things are named with an URI. Also, on the Semantic Web anyone can name anything, just like in real life. One thing can have different names (URIs) that people are referring to it with. URIs are the building element of RDF.

Making statements, forming sentences (RDF)

RDF stands for Resource Description Framework. It is used for describing resources on the web. When you already have an URI, you can use RDF to say things about things, that is to create statements. Think of this as building sentences. RDF statements consist of Subject, Predicate and Object, the same way our sentences consist of these three.

For example, the sentence “This article is about Semantic Web standards“ can be stored in an RDF statement containing a relationship between the subject of this sentence (this article) and the object (Semantic Web Standards). “Is about” is the predicate indicating the type of relationships existing between the subject and the object.

All the parts of the RDF statement can enter multiple relationships between other parts. Thus, data can be stored in these triples and further easily interchanged.

Querying Data and Discovering Relationships (SPARQL)

SPARQL is short for SPARQL Protocol and RDF Query Language and is a language used for querying, retrieving and manipulating data stored in RDF format. Think of it as a query language that allows users to search the Web of Data (or any database) and discover relationships. It is a powerful language that goes way beyond keyword search.

Using the Semantic Web Standards to Model Data

The most important technical challenge today in managing big data is variety (heterogeneity of data and diversity of data sources). The only effective way to handle heterogeneity is a semantic approach: develop some form of vocabulary, knowledge base or ontology, and use semantic information extraction and annotate heterogeneous data to improve interoperability and integration.

cit. Amit Sheth of Knoesis
Web vs. Semantic Web

The technology standards of the Semantic Web enable more and more enterprises, application builders and information retrieval systems to handle data in cost-effective and agile manner. Companies in the fields of media and publishing, financial services, life sciences, healthcare, where effective data management is vital, have been among the early adopters of these technologies.

In today’s data-driven world, flexibility and interoperability for data modeling are critical for everyone who wants to stay in business. This is why Semantic Technology is finding its way among a broader range of industries.

The robustness of these standards for enterprise solutions for easy and quick retrieval of data, actionable knowledge management and business intelligence is what makes the number of organizations turning to semantics grow.

Using Semantic Web Standards for modeling data might still seem a considerable investment of time and money, yet these are a small price to pay for a powerful technology for representing relationships, in all their richness and diversity, within any domain of knowledge.

 

          New call-to-action

Article's content

Content Writer at Ontotext

Teodora is a philologist fascinated by the metamorphoses of text on the Web. Curious about our networked lives, she explores how the Semantic Web vision unfolds, transforming the possibilities of the written word.

GraphDB in Action: Navigating Knowledge About Living Spaces, Cyber-physical Environments and Skies 

Read about three inspiring GraphDB-powered use cases of connecting data in a meaningful way to enable smart buildings, interoperable design engineering and ontology-based air-traffic control

Your Knowledge Graph Journey In Three Simple Steps

A bird’s eye view on where to start in building a knowledge graph solution to help your business excel in a data-driven market

GraphDB in Action: Putting the Most Reliable RDF Database to Work for Better Human-machine Interaction

Read about the world of academia research projects that use GraphDB to meet the challenges of heterogeneous data across various domains

Knowledge Graphs for Retail – Connecting People, Products and Platforms

Read about how knowledge graphs can serve the retail industry’s growing need to connect, manage and utilize data efficiently, aligning it in a collaborative data ecosystem

Data Wants To Be Truly Sovereign: Designing Data Spaces with Linked Data Principles In Mind

Read about what data spaces are and how semantic technologies and Linked Data can make them a stronger and safer mechanism for commercial data exchange

GraphDB in Action: Powering State-of-the-Art Research

Read about how academia research projects use GraphDB to power innovative solutions to challenges in the fields of Accounting, Healthcare and Cultural Heritage

KGF22: Knowledge Graphs and The Not So Quiet Cognitive Revolution

Read about Ontotext’s KGF22 days dedicated to stories about knowledge graphs in the domains of Industry, Healthcare & Life Sciences and Financial Services

KGF22: Wittgenstein, Developers Empathy and Other Semantic Data Considerations

Read about our event report from Ontotext’s Knowledge Graph Forum 2022, highlighting expert insight on building knowledge graphs and designing enterprise-grade solutions with semantic technologies.

A Little SEMANTiCS Goes A Long Way

Take a sneak peek at some of the keynote speeches and tutorials throughout SEMANTiCS 2022

It Takes A Village To Raise An Enterprise Knowledge Graph

Read about the design processes behind crafting knowledge-graph enabled solutions and explore some of the stories of our partners.

Smart Buildings Are Built of Smart Data: Knowledge Graphs for Building Automation Systems

Read about how knowledge graphs offer a sustainable solution for harnessing and making sense of heterogeneous data in the building automation industry.

Metadata Moves: Knowledge Graph Technology for Logistics

Read about how the world of metadata humming behind the logistics and other supply chain processes can benefit from using knowledge graph technology.

Electrical Standards, Smart Grids and Your Air Conditioner

Read about how applying Linked Data principles and semantic technology to electricity data can make for a more efficient, reliable and sustainable electricity market.

The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Read about how the Semantic Web vision reincarnated in thousands of Linked Open Data datasets and millions of Schema.org tagged webpages. And how it enables knowledge graphs to smarten up enterprises data.

Metadata is Like Packaging: Seeing Beyond the Library Card Metaphor

Read about what metadata is, why it is important and how it can enhance the ways information flows across the enterprise.

From Fragmented Data to a Comprehensive Knowledge Graph: The Case for Building an R&D Repository

Read about how enterprise knowledge graphs can unlock meaning and thus create a smart future-proof living repository of scientific data and its relationships.

Texts Without Pages: Advancing Text Analytics with Content Enrichment

Read about how text analytics can be brought forward with content enrichment processes for better text authoring, delivery and navigation.

A Shield Built of Connected Data: Knowledge Graphs Meet Cybersecurity

Read about how a knowledge graph can help organizations stay vigilant of the increasing number of cyber threats, keeping malicious attacks at bay with the help of semantics.

Digital Twins: If It Sounds Like Cyberpunk, It’s Because It Is

Read about what digital twins are, what makes them attractive to companies and how digital twins relate to semantic technology and enable organizations to design, simulate and validate various scenarios virtually.

Eating the Knowledge Soup, Literally

Read about the fluid essence of knowledge and the capability of knowledge graphs to power an information-rich platform of diverse facts about anything, a broccoli soup included.

If Curiosity Cabinets Were Knowledge Graphs

Read about why and how knowledge graph technology can help build networks of interwoven digital objects in the world of cultural heritage.

On the Hunt for Patterns: from Hippocrates to Supercomputers

Read about the ExaMode project that will help medical professional use the power of supercomputers and knowledge graphs for more efficient patient care through data-driven diagnoses.

Crafting a Knowledge Graph: The Semantic Data Modeling Way

Read about how to build a knowledge graph the semantic data modeling way in 10 steps, provided by our knowledge graph technology experts.

A Graphful of Investment Opportunities

Read about the story of an algorithm that mines data to narrow down opportunities for investing.

Okay, You Got a Knowledge Graph Built with Semantic Technology… And Now What?

Read about how knowledge management can be made smarter using a knowledge graph built with semantic technology.

If Johnny Mnemonic Smuggled Linked Data

Read about how semantic technology and Linked Data can help enterprises benefit from smart data management and retrieval practices.

Data, Databases and Deeds: A SPARQL Query to the Rescue

Read about why and how SPARQL queries make for a better search in diverse datasets across an organization in an integrated way.

Semantic Technology and the Way We See the World

Read about how semantic technology can help you set the wheels for many processes related to еfficient data management and governance.

Telling Stories with an RDF Database

Read about the opportunities for authoring and publishing workflows opened by an RDF triplestore.

The Power of URI or Why Odysseus Called Himself Nobody

Read about URI and its power to enable the sharing and reuse of machine-readable data with minimum integration costs.

From Cultivating Nature to Cultivating Data: Semantic Technology and Viticulture

Learn how the potential that Big Data streams bring to grape and wine production can be harnessed with the right kind of technology.

The Knowledge Graph and the Enterprise

Read about the knowledge graph and about how many enterprises are already embracing the idea of benefiting from it.

It Don’t Mean a Thing If It Ain’t Got Semantics

Learn how you can turn data pieces into actionable knowledge and data-driven decisions with an RDF database.

The Bounties of Semantic Data Integration for the Enterprise

Learn about the potential semantic data integration carries for piecing massive amounts of data together.

Here’s a Graph, Go Figure! Coupling Text Analytics with a Knowledge Graph

Learn why and how a Knowledge Graph boosts significantly Text Analytics processes and practices and makes text work for us in a more meaningful way.

Cognitive Computing: Let’s Play an Awareness Game

Read about the new breed of computing is emerging before our eyes – cognitive computing and join us in our Awareness Game.

Machine Learning and Our (Insatiable) Penchant for Making Things Smarter

Read about how machines can be of great help with many tasks where fast and error-free computation over big amounts of data are required.

Staying In the Vanguard of Digital Transformation with Open Data

Learn about Open Data and its potential to be part of smart solutions to data problems and innovative products and services.

Whose Meaning? Which Ontology?

Read about how ontologies open up opportunities for a new class of tools to power information consumption and knowledge management.

Shiny Happy Data: A Praise for RDF

Learn how to choose the right solution for working with your data the conceptual framework of “happy connected people”.

Enterprise Metadata Matters: From Having Data to Acting Upon Them

Learn more about the importance of being metadata-driven today in our latest SlideShare presentation.

Data Daiquiri: The Power of Mixing Data

Learn how companies can tap into the power of the data coming their way by integrating the huge data flows with their proprietary data.

Migrating to GraphDB: Your Why and How in 20 slides

Learn about the steps you need to migrate your data to GraphDB to use it as a smart brain on top of your legacy systems.

Got meaning? Or Why an RDF Graph Database Is Good for Making Sense of Your Data

Read about how you can create systems capable of discovering relationships and detecting patterns within all kinds of data.

Brains Armored with Smart Data

Read our thoughts rising from questions such as “Will Giant Brains Rule the World?” and “Can a mechanical brain replace you?”

One Step Closer to Intertwingularity: Semantic Metadata

Learn about how semantic metadata allows us to add granularity to an object, interlink it to other objects and make it easy to search.

Exceptional User Experiences with Meaningful Content NOW

Content enrichment and semantic web technologies are key to efficient content management. Learn why and see these technologies in action.

Semantic Information Extraction: From Data Bits to Knowledge Bytes

Learn about semantic information extraction and how it pulls out meaningful data from textual sources, ready to be leveraged for insights, decisions and actions.

Weaving Data Into Texts: The Value of Semantic Annotation

Read about how semantic annotation links certain words to context and references that can be processed by an algorithm.

Exploring Linked Open Data with FactForge

Learn about FactForge and how you can turn the opportunities that data flows on the web can pour into our business into a real experience.

What is GraphDB and how can it help you run a smart data-driven business?

Learn about GraphDB in a simple and easy to understand way and see what Ontotext’s semantic graph database has to do with pasta making.

Linked Data for Libraries: Our New Librarians

Learn how semantic technologies can bring audiences back to libraries and make library archives and collections visible and accessible.

Working with Data Just Got Easier: Converting Tabular Data into RDF Within GraphDB

Read about OntoRefine – a new tool that allows you to do many ETL (extract, transform and load) tasks over tabular data.

GraphDB: Answers for Kids of All Ages

Read about how GraphDB can help you clean up messes of data (just like your room) – whether you are a kid or not.

The Knowledge Discovery Quest

Learn how by joining the dots, semantic search enhances the way we look for clues and compare correlations on our knowledge discovery quest.

Connectivity, Open Data and A Bag of Chips

Learn how LOD’s connectivity allows data to be shared seamlessly, used and reused freely. As simple as a bag of chips.

Data Integration: Joining the Data Pieces of Your Business Puzzle

Learn how to use information interconnectedness to integrate, interpret and ultimately make sense of data.

Cooking Up the Semantic Web

Read about the Semantic Web and what it takes to reach its potential and evolve from a Web of Documents to a Web of Data.

Semantic Search: The Paradigm Shift from Results to Relationships

Read about semantic search and how it takes information retrieval to the next level and puts information at our fingertips.

A Web of People and Machines: W3C Semantic Web Standards

Learn how and why Semantic Web Standards are to serve the Web of Data for better collaboration between people through computers.

Thinking Outside the Table

Learn how to manage highly connected data, working with complex queries and having readily available relationships, without the need to express them explicitly.

Our Networked Lives, Publishing and Semantic Technologies

Read about how semantic technology helps publishing handle data in an interconnected way, attaching machine-processable and readable meaning to them.

Why Graph Databases Make a Better Home for Interconnected Data Than the Relational Databases?

Read about how you can turn data into a resource, easily accessed and effectively used across the organization with a graph database.

Text, Data and the Roman Roads: Semantic Enrichment

Read about semantic enrichment and the unique opportunity it offers for interconnecting objects to facilitate knowledge discovery.

4 Things NOW Lets You Do With Content

Go beyond conventional publishing with Ontotext’s News On the Web and get the feel of how you can discover and consume content with semantic technology.