Ontotext

DECEMBER 9, 2020

Stop wasting time building data access code manually, let the Ontotext Platform auto-generate a fast, flexible, and scalable GraphQL APIs over your RDF knowledge graph. Are you having difficulty joining your knowledge graph APIs with other data sources? This leads to lots of small data fetches to/from GraphDB over the network.

Modeling 130

Modeling Management Optimization Machine Learning 130

Ontotext

MARCH 24, 2021

For these reasons, publishing the data related to elections is obligatory for all EU member states under Directive 2003/98/EC on the re-use of public sector information and the Bulgarian Central Elections Committee (CEC) has released a complete export of every election database since 2011. The complexities of election data.

Statistics 142

Statistics Publishing Data Processing Metrics 142

Ontotext

SEPTEMBER 23, 2021

So, we started this series by introducing knowledge graphs & their application in data management and how to reason with big knowledge graphs & use graph analytics. Here, we want to talk about our flagship product GraphDB – an enterprise-ready RDF database optimized for the development and operations of knowledge graphs.

Optimization 97

Optimization Business Intelligence Data Collection Enterprise 97

Ontotext

NOVEMBER 18, 2021

You step onto the market, and if you don’t keep your data, there’s no knowing where you might be swept off to. [1]. Picture this – you start with the perfect use case for your data analytics product. Nowadays, data analytics doesn’t exist on its own. But would the surveyors write SPARQL? But with robots.

Visualization 98

Visualization Reporting Metadata Enterprise 98

Ontotext

NOVEMBER 25, 2021

In our previous blog post of the series, we covered how to ingest data from different sources into GraphDB , validate it and infer new knowledge from the extant facts. Today we’ll deal with the big issue of scaling, tackling it on two sides: what happens when you have more and faster sources of data? A bespoke program.

Visualization 98

Visualization Interactive Data-driven Data Science 98

Ontotext

MAY 23, 2024

As you might guess from its name, GraphDB stores data in a graph data structure, which is much more flexible than the rigid table structures used by relational database managers. Relational databases have been around for a long time, though, and vast amounts of data are stored in them.

Business Intelligence 69

Business Intelligence Management IT Technology 69

Ontotext

NOVEMBER 4, 2021

In the previous post, we talked about data virtualization and how Ontotext’s RDF database for knowledge graphs GraphDB provides the tools for the full journey from graphs to relational tables and back. On the other hand, LPGs lack many features that are an absolute must for enterprise data management, e.g., standard schema language.

Metadata 98

Metadata Visualization Modeling Enterprise 98

Ontotext

FEBRUARY 9, 2024

Natural Language Querying (NLQ) refers to the process of querying a database or an information system using natural language, such as English, instead of formal query languages such as Structured Query Language (SQL). NLQ allows users to interact with databases or systems in a more intuitive and user-friendly way.

Manufacturing 69

Manufacturing Modeling Interactive Business Intelligence 69

Ontotext

AUGUST 15, 2019

But it has enriched us in terms of identifying key needs for those looking to build a simple prototype in order to demonstrate the power of semantic technology, linked data and knowledge graphs. Some of that journey has been recorded in a previous blog post. This training will not make a SPARQL master out of anyone.

Knowledge Discovery 70

Knowledge Discovery Technology Metadata Interactive 70

Ontotext

NOVEMBER 7, 2019

Rebel GraphQL developers strike from a hidden base and have won their first victory against the evil SPARQL empire. During the battle, however, it is discovered that Ontotext has secret plans to allow both GraphQL and SPARQL to co-exist, and flourish together, building the ultimate weapon, the ONTOTEXT PLATFORM ! Species subClass).

Visualization 78

Visualization Modeling Technology Optimization 78

Ontotext

DECEMBER 30, 2019

In 2019 we have published many engaging blog posts on various topics and now, at the end of this exciting year, we have analyzed your interest in them and would like to present the top 5 most fascinating blog posts for 2019. Telling Stories with an RDF Database. Artificial Intelligence and the Knowledge Graph.

Knowledge Discovery 52

Knowledge Discovery Publishing Technology Enterprise 52

AWS Big Data

SEPTEMBER 12, 2024

In this blog post, we will highlight how ZS Associates used multiple AWS services to build a highly scalable, highly performant, clinical document search platform. We use leading-edge analytics, data, and science to help clients make intelligent decisions. Overview of solution The solution was designed in layers.

Unstructured Data 111

Unstructured Data Metadata Machine Learning Consulting 111

Ontotext

DECEMBER 20, 2023

Nose-first data: the project Odeuropa preserving the smells heritage of Europe No doubt our olfactory perception contributes and enriches our understanding and experiencing of the world. The question is how we can use data and cutting-edge technology to learn about the smell experiences and the perception of different smells in the past.

Visualization 78

Visualization Data Processing Data mining Interactive 78

Ontotext

NOVEMBER 16, 2023

In the first part of this series of technological posts, we talked about what SHACL is and how you can set up validation for your data. Tacking the data quality issue — bit by bit or incrementally There are two main approaches to validating your data, which would be dependent on the specific implementation.

Data Quality 69

Data Quality Reporting Testing Technology 69

Ontotext

FEBRUARY 18, 2021

The beauty and power of knowledge graphs is their abstraction away from the fiddly implementation details of our data. The data and information is organized in a way human-users understand it regardless of the physical location of the data, the format and other low-level technical details. Firstly, There’s Federation.

Cost-Benefit 59

Cost-Benefit Business Intelligence Technology Optimization 59

Ontotext

NOVEMBER 9, 2023

It is common nowadays to see environments where various actors have access to the same database and can write their own data. While everyone may subscribe to the same design decisions and agree on an ontology, there may be differences in the data quality. In such situations, data must be validated.

Data Quality 64

Data Quality Testing Reporting Metadata 64

Ontotext

JANUARY 20, 2022

So far we have covered the capabilities and business applications of knowledge graphs as well as some of the major benefits of our RDF database – GraphDB. They focus on business-specific information needs and how to properly source the needed data rather than analyze preexisting application models.

Enterprise 52

Enterprise Unstructured Data Visualization Modeling 52

Ontotext

NOVEMBER 23, 2023

Bulk validation is great when data comes together nicely as one big package. The data only becomes problematic when it’s joined together with the rest of the dragon data. However, to do that, we had to perform bulk validation on the whole database. Then, validation happens on the data within that context only.

Data Quality 69

Data Quality Reporting Metadata Big Data 69

Ontotext

APRIL 2, 2020

Over the years, Ontotext’s leading semantic graph database GraphDB has helped organizations in a variety of industries with their data and knowledge management challenges. Experts in linked data, semantic technology and triplestores are testing GraphDB’s capabilities and performance, and applying it in various technical use cases.

Visualization 52

Visualization Testing Manufacturing Data Architecture 52

Ontotext

AUGUST 24, 2023

The update is to drop and re-import the same graph data into a single atomic transaction. The simplified SPARQL query below describes how to delete the old data and insert the new one. The biggest advantage of the approach is that the user can query the database at any given past timestamp.

Data Integration 52

Data Integration Modeling Business Objectives Optimization 52

Ontotext

OCTOBER 7, 2020

Knowledge of the subject domain is always helpful, but rarely sufficient as there are many choices to be made in representing domain knowledge as data in a graph. The Financial Industry Business Ontology (FIBO) is a conceptual model of the financial industry that has been developed by the Enterprise Data Management Council (EDMC).

Finance 59

Finance Visualization Modeling Metadata 59

Ontotext

NOVEMBER 22, 2022

ONTOTEXT ANSWER: The dreaded answer to this question is “it depends” JSON data is really pervasive. However, it doesn’t make the cut when it comes to RDF databases. JSON can easily be treated as subject-predicate-object data. JSON supports fewer data types than RDF. JSON has become an industry standard.

Optimization 52

Optimization IT 52

Ontotext

DECEMBER 3, 2021

ONTOTEXT ANSWER: Query optimization can be quite problematic. Inference vs querying. As a forward-chaining database , GraphDB materializes triples at load time. If you know you have a complex statement pattern that you will be querying often, why not precompute it with inference? Limiting data sizes.

Optimization 52

Optimization Measurement IT 52

Ontotext

FEBRUARY 21, 2024

Ontotext GraphDB stands out as a high-performing and scalable graph database, boasting robust RDF and SPARQL capabilities. GraphDB Cluster The GraphDB cluster ensures high availability through data replication among its nodes. The leader can execute both read and write queries. The followers can execute only read queries.

Strategy 72

Strategy IT Technology 72

Ontotext

JUNE 24, 2020

This provides a unified interface for querying all of your data sources in context and allows clients to fetch data from any number of data sources simultaneously, without needing to know which data comes from which source. Our friends from the GraphQL Federation have pledged their support. Trade Federation.

Modeling 64

Modeling Technology IT Management 64

Ontotext

JANUARY 6, 2021

. ‘Don’t Reinvent the Wheel’ Data analysis is an example where time and effort are being spent over and over only for the data and development to be chucked into the ocean after the work is done. This is particularly true for the initial data preparation stage of any analysis work.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Ontotext

FEBRUARY 28, 2023

Or, there may even be a requirement that your data is compartmentalized so one attack only compromises some of your data. Logical separation – GraphDB (or any graph database, really) has a way to achieve this, using named graphs – also known as contexts. That roughly maps to a table/database concept from SQL.

Experimentation 52

Experimentation Enterprise Management IT 52

Ontotext

AUGUST 16, 2019

But it has enriched us in terms of identifying key needs for those looking to build a simple prototype in order to demonstrate the power of semantic technology, linked data and knowledge graphs. Some of that journey has been recorded in a previous blog post. This training will not make a SPARQL master out of anyone.

Knowledge Discovery 40

Knowledge Discovery Technology Metadata Interactive 40

Ontotext

NOVEMBER 6, 2019

of Ontotext’s GraphDB has lots of new bells and whistles that will ensure that it remains the market leader for semantic databases. This new version sees the release of essential plug-ins: data virtualization, a sophisticated ranking of semantic search results, new types of indexing and advanced graph analytics. Version 9.0

Experimentation 45

Experimentation Deep Learning Software Modeling 45

Ontotext

JUNE 27, 2019

Ontotext’s GraphDB is an enterprise-ready semantic graph database (also called RDF triplestore as it stores data in RDF triples). It provides the core infrastructure for solutions where modeling agility, data integration, relationship exploration, cross-enterprise data publishing and consumption are critical.

Metadata 40

Metadata Management Enterprise Publishing 40

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The many data warehouse systems designed in the last 30 years present significant difficulties in that respect.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Ontotext

JANUARY 21, 2021

The Financial Industry Business Ontology (FIBO) is a standard that is being developed and published by the Enterprise Data Management Council that attempts to capture business domain knowledge using sophisticated knowledge representation techniques and linked open data technologies. In this way, FIBO can give meaning to any data (e.g.,

Modeling 72

Modeling Finance Technology Publishing 72

Ontotext

JUNE 27, 2019

This is a really exciting feature as it increases the write scalability of RDF solutions when dealing with document-centric data. It allows us to store some of our data outside of GraphDB, but still query it from GraphDB’s SPARQL editor. Often, the data stored in an enterprise knowledge graph has two shape types.

Metadata 40

Metadata Management Optimization Enterprise 40

Ontotext

JULY 15, 2024

The generation, transmission, distribution and sale of electrical power generates a lot of data needed across a variety of roles to address reporting requirements, changing regulations, advancing technology, rapid responses to extreme weather events and more. What are knowledge graphs and how can they help?

Contextual Data 52

Contextual Data Metadata Data Quality Publishing 52

Ontotext

SEPTEMBER 11, 2024

In this edition of GraphDB In Action, we present to you the work of three bright researchers who have set out to find solutions that allow meaningful analysis and interpretation of data, supported by Ontotext GraphDB. It was used with SPARQL in GraphDB to maintain semantic interoperability with external RDF namespaces.

Machine Learning 52

Machine Learning Software Data Integration Modeling 52

Ontotext

JANUARY 6, 2022

We looked at the major challenges of electrical grids, the main standards guiding electricity data exchange and how these challenges could be addressed by applying Linked Data principles and knowledge graph (KG) technology to electricity data. Simply put, AI without data is like a human surviving without oxygen.

Marketing 52

Marketing Data Quality Dashboards Visualization 52

Ontotext

JULY 11, 2019

Ontotext’s GraphDB is an enterprise-ready semantic graph database (also called RDF triplestore because it stores data in RDF triples). It provides the core infrastructure for solutions where modelling agility, data integration, relationship exploration, cross-enterprise data publishing and consumption are critical. .

Statistics 40

Statistics Modeling Metadata Enterprise 40