• Blog
  • Informational

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

Deep and rich search results are paramount for thorough and accurate analysis across enterprise information systems. In this article you will read why and how SPARQL queries make for a better search and are of immense help when it comes to accessing all the independently designed and maintained datasets across an organization (and outside it) in an integrated way.

April 26, 2019 5 mins. read Teodora Petkova

Data, Databases and Deeds A SPARQL Query to the Rescue

In a world of 2.5 quintillion bytes of data created each day, the bar for enterprise knowledge and information systems, and especially for their search functions and capabilities, is raised high. New ways of using legacy databases are put to work to bring integrated information at the fingertips of knowledge workers and to empower deeper discovery of data patterns and richer analysis of information grids.

One such way towards better search (and better-informed actions) is the SPARQL query.

Read our White Paper: The Truth About Triplestores!

What is a SPARQL query and Why Does It Matter to Us, the Knowledge Seekers?

The SPARQL query is a way to search, access and retrieve structured data by pulling together information from diverse data sources.

SPARQL is an abbreviation for Simple Protocol and RDF (Resource Description Framework) Query Language. The SPARQL query language, designed and endorsed by the W3C, is the standard for querying data, stored in RDF or mapped to RDF. In more technical detail, a SPARQL query is a set of triple patterns where each element (subject, predicate and object) can be a variable. Searching with a SPARQL query is actually matching patterns in the query to patterns in the dataset.

From a searcher’s perspective, such queries allow users to navigate multiple information sources with higher level of accuracy and at a greater speed, not necessarily knowing what exactly they are looking for. For example, one can construct a SPARQL query and search across databases for paintings by Italian artists from the 16th century that contain elements of a certain art movement.

To see why this is so important, especially within an enterprise context, let’s widen the lense a little bit. Think of all the databases an organization is operating with. A database with records about clients, a database with records of finances, one with suppliers, another with locations, several domain-specific public databases, etc.

Accessing all these independently designed and maintained datasets in different databases one by one and further integrating the results is cumbersome, if not impossible, and/or extremely expensive. Arguably, this cannot be the 360-degree view we all seek, at least not an effective one.   When it comes to finding actionable information , we need to think where to search, how to search (as to comply with the schema of the database, rather then the opposite), how to further analyze all the different results we get (or very often don’t get), etc.

In such cases, the reason a single point of entry to information is so crucial is one: easy search, access and retrieval.

And this is where SPARQL queries come to the rescue. Constructed well, such queries allow us to focus on what we would like to know instead of how a database is organized.

The Heavy-Lifting Before the Magic

While SPARQL is a wonderful way of querying diverse data from a single source, without knowing the schemata of the different sources, it is also true that before the SPARQL magic, we need to do some heavy lifting such as:

  • Mapping the schemata of multiple sources to a single unified ontology
  • Mapping across identifiers of entities, nomenclatures and taxonomies across multiple sources
  • Normalizing data values (if needed)

In other words, an efficient and rewarding SPARQL requires doing one’s homework with data integration and entity linking. While, integrating multiple data sources in a knowledge graph doesn’t come without effort, this approach is recognized to be much more efficient than the traditional datawarehousing.

When constructed right, a SPARQL query gives us:

  • Less costly queries (less computational resources)
  • Higher level of accuracy
  • Greater speed

Putting Federated SPARQL Queries to Work for the Enterprise

SPARQL queries are not constrained to working within one database. Through the so-called federated queries one can access multiple datasets. In other words, the SPARQL query has a smart relative – the federated SPARQL query.

Federated SPARQL queries, being an extension to the SPARQL query syntax (see SPARQL 1.1 Federation) are an even more exciting way to better search and navigate data distributed across the Web and within the enterprise’s multiple datasets.

Translated into benefits for the knowledge seeker and everyone who wants to turn data into actions, a single federated SPARQL query allows us to juggle heterogeneous datasets to find relevant results, navigate data architectures in an interconnected way and, most importantly, get a uniform view of an otherwise fragmented information across the Web and internal silos.

And all this – without the need to directly write SPARQL queries. Most semantic graph databases, GraphDB included, have intuitive SPARQL editors with autocomplete, explorer and many other features to facilitate the construction of SPARQL queries.

Epilogue: What Am I Looking for?

What makes SPARQL such a powerful way of finding information is the ability it provides for constructing a search that has multiple “unknowns” in it. It can help us search databases for books in Italian from any author who is born in Rome, or for news mentioning the first 5 people from the list of the top 10 billionaires in the world which are working in companies in the financial sector.

No matter how we wish to query the databases we are trying to elicit information and knowledge from, SPARQL lets us focus on what we need to know. Share on XIt lets us access multiple data containers from one single place and retrieve and manage non-uniform data to ultimately arrive at the point of better decision-making based on broader and deeper access to our information.

Want to experience the power of federated SPARQL queries?

White Paper: The Truth About Triplestores

Download Now

Article's content

Marketing Expert 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. From 2022 on, Teodora helps with the creation and curation of the Ontotext knowledge graph to foster information ecology out of marketing content that will enable relevant user experiences across Ontotext's universe.

GraphDB in Action: Smells Like Semantics Spirit

Read about a project called Odeuropa and a number of exciting applications delivered by it with our RDF graph database humming behind them

KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Read about this year’s Knowledge Graph Forum – a space where Ontotext and partners presented smart and linked ways to tame and thrive on complexity, rather than be drowned by it

Do Large Language Models Dream of Knowledge Graphs – Impressions from Day 2 At SEMANTiCS 2023

Read our report from Day 2 of SEMANTiCS 2023 to find out if ChatGPT is the killer app for the Semantic Web, how do we tame the genie of LLMs for Healthcare and more

Can LLMs Become Knowledgeable – Impressions from Day 1 At SEMANTiCS 2023

Read about the interplay between LLMs & KGs and how business and academia tackle them in our report from Day 1 at SEMANTiCS 2023

It’s Time We Give Each Other More Data Spaces: Impressions from the Pre-conference Day at SEMANTiCS 2023

Read about SEMANTiCS pre-conference day, which covered the topics of interoperability, ESG data, knowledge engineering, scholarly communication, and academia & industry collaboration.

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.