Frequently Asked Questions

General

General

timbr is a platform that enables the creation of virtual SQL Knowledge Graphs over any data engine, used as intelligent enterprise data fabric and data catalog.

Category: General

Timbr is named after Tim Berners Lee who, together with timbr.io’s advisor Jim Hendler, pioneered the Semantic Web.

Category: General

A SQL Knowledge Graph is the implementation of ontologies and graph theory in standard SQL. It has two components: (i) a virtual SQL ontology of connected, context-enriched concepts with inference capabilities and graph analytics features and, (ii) a mapping of the virtual SQL ontologies to existing databases accessible in SQL. The SQL Knowledge Graph closes the gap between knowledge representation and enterprise databases/legacy systems/data warehouses/data lakes, to conveniently enable smart, semantic data fabrics and digital twins without need to change DBMS infrastructure.

Category: General

timbr offers a fast, easy and no-risk implementation of the semantic graph. The main reasons are that there’s no need to move data or learn any new proprietary query languages to work with the Knowledge Graph.

Modeling a SQL ontology can be done either manually or automatically from an ERD, OWL ontologies, or from data catalogs.

The mapping of the data to the Knowledge Graph is also done either manually or semi-automatically.

Category: General

Conceptual modeling is a representation of the real world. It is the first step of data modeling, a method developed to help with the design of databases and defining a formal vocabulary for the organization.

The process leading to the actual modeling and creation of databases leaves out information that is key to understanding and using data effectively. To make up for this information left behind, enterprises require coding complex queries in complex applications.

Ontologies are an effective means to re-create the information left behind, giving back business meaning to the data, simplifying data access and delivering unique analytical capabilities.

Category: General

An ontology defines a common vocabulary for an organization that needs to share information in a domain.
This includes machine-interpretable definitions of basic concepts in the domain and relations among them.

An ontology is structured as a graph, where every node on the graph represents a “concept.”
A concept could be anything: Person, Place, Customer, Car, Country, Product, Event etc.

Category: General

SQL ontologies are ontologies that implement the Semantic Web in SQL (what is an ontology?) and are designed to provide common business meaning to data distributed in varied sources and enable them as concepts with inference and graph traversal capabilities to facilitate discovery, use and access to data.
With timbr you can model and explore your ontology visually or in standard SQL. The SQL Ontology is exposed to the SQL user as a virtual schema with virtual tables (concepts) using any SQL client with JDBC/ODBC.

Category: General

See here:

Category: General

Graph Data Exploration is timbr’s module that allows users to visualize and navigate the virtual Knowledge Graph. Data consumers, business analysts and domain experts can visually explore and discover relationships, quickly finding answers to their questions.

Category: General

Semantic SQL is SQL used for querying SQL ontologies instead of directly querying the underlying data. By querying the ontology’s concepts, users benefit from graph traversals and semantic reasoning features, so SQL queries become significantly less complex and query size is reduced significantly.

Category: General

A semantic data catalog is an intelligent catalog/inventory of data assets that automatizes sharing common meanings of data across data silos and provides a means to define hierarchies and relationships featuring semantic reasoning. It serves as a queryable, AI-enabled knowledge encyclopedia of the organization. timbr enables the fastest and most convenient implementation of semantic data catalogs connected to your databases and business intelligence tools. Contact us to schedule a demo.

Category: General

The semantic data fabric is a flexible, reusable layer and set of data services used as the single source providing universal meaning and context to data for the entire organization. The data fabric integrates on-premise and cloud data sources in use by the organization, handing them semantic capabilities to provide answers to complex queries and to facilitate understanding and use of data. It provides consistent capabilities across on-premises and multiple cloud environments to accelerate digital transformation. timbr enables the fastest and most convenient implementation of semantic data fabric connected to your cloud and on-premise databases and business intelligence tools. Contact us to schedule a demo.

Category: General

A digital twin refers to a digital replica of potential and actual physical assets, processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how an Internet of things (IoT) device operates and lives throughout its life cycle.
Digital twins have two important characteristics.
1. each definition emphasizes the connection between the physical model and the corresponding virtual model or virtual counterpart.
2. this connection is established by generating real-time data using sensors.
timbr helps enterprises create digital twins by enabling the definition of the virtual model using SQL ontologies and by connecting the virtual model to data lakes that contain the sensor’s data. Contact us to schedule a demo to see why timbr facilitates the fastest and most convenient implementation of digital twins.

Category: General

The Semantic Web is a project devised by Tim Berners Lee and James Hendler (et al), and adopted by the W3C (the manager of the Internet). The Semantic Web implements ontologies so that machines connected to the Web “understand” each other by sharing common meaning of data using a set of standards. The standards developed by the W3C define among others, an ontology modeling language (OWL) and a query language (SPARQL).

timbr implements the principles of the Semantic Web in standard SQL, meaning that both the ontology modeling and the queries are done in SQL.

Category: General

Creating a SQL Knowledge Graph is a simple process:

1. Connect your databases to the virtual layer using JDBC connectors.

2. Model the SQL ontology visually or using timbr SQL DDL statements, or import from other sources (data catalogs, OWL ontologies, ERD tools).

3. Map the ontology concepts to the data.

That’s it, your SQL Knowledge Graph is ready for use and can start delivering unique insights via SQL queries, graph data exploration, your BI tools, or using timbr’s embedded charts and dashboard module.

Category: General

No, you just need a database, timbr will guide you through the rest of the simple process.

Category: General

The SQL Knowledge Graph serves as a virtual graph for all the enterprise data engines. Organizations use it to integrate, analyze and explore their data sources and silos of information without the need to move or transform data. Data consumers benefit from a 360° access to data to get fast answers to key business questions. By querying concepts instead of the tables, SQL queries are reduced in length and complexity significantly. The SQL Knowledge Graph seamlessly integrates with popular business intelligence tools so business analysts can focus on the business questions and derive deeper insights.

Category: General

timbr is not a database. timbr is a platform used for creating virtual SQL Knowledge Graphs that enable semantic (ontology-based) graph capabilities on existing data engines (data warehouses and data lakes). The SQL Knowledge Graphs integrate data sources into a semantic data fabric queryable in SQL. timbr does not require to copy or transform data (no ETL operations), no new DBMS infrastructure and no new skills as required by graph databases.

Category: General

No, it is not possible. Property graphs use proprietary query languages lacking in semantics (unlike Knowledge Graphs which are based on RDF, SPARQL and OWL). Currently, timbr works with data engines that support SQL (mainly data warehouses and data lakes).

Category: General

Exploring relationships is done by using timbr’s Graph Data Exploration module.

Category: General

There’s no community version of timbr, but any organization with a use-case in mind can contact us asking for credentials to test drive timbr free of cost.

Category: General

If your database is HIPAA complaint then timbr is as well.

Category: General

If your database is GDPR complaint then timbr is as well.

Category: General

A knowledge graph is a knowledge base that uses a graph-structured data model or topology to integrate data. Knowledge graphs are often used to store interlinked descriptions of objects, events or concepts with free-form semantics. Knowledge graphs use ontologies to put data in context via linking and semantic metadata and this way provide a framework for data integration, unification, analytics and sharing.

They are also prominently associated with and used by Google, Bing, and Yahoo, and with question-answering services such as Google Assistant, Siri and Alexa. All these examples were developed with proprietary tools.

For organizations that look to benefit from knowledge graphs, the available solutions in the market require significant changes in their IT departments. This is due to the fact that most data in the world is stored in formats that are not compatible with the format in which data is stored in knowledge graphs, so data needs to be extracted from its current DBMS, transformed to a new format and loaded into a separate, suitable DBMS. Another reason being is that to use knowledge graphs, data engineers and consumers need to acquire news skills to model in OWL and query in SPARQL.

Different from most other solutions, the timbr SQL Knowledge Graph platform creates a virtual layer that works in standard SQL to seamlessly connect to existing databases and is implemented without requiring new skills.
Contact us to learn how timbr can help your organization join the knowledge revolution.

Category: General

Load More

Connectivity

General

timbr is a platform that enables the creation of virtual SQL Knowledge Graphs over any data engine, used as intelligent enterprise data fabric and data catalog.

Category: General

Timbr is named after Tim Berners Lee who, together with timbr.io’s advisor Jim Hendler, pioneered the Semantic Web.

Category: General

A SQL Knowledge Graph is the implementation of ontologies and graph theory in standard SQL. It has two components: (i) a virtual SQL ontology of connected, context-enriched concepts with inference capabilities and graph analytics features and, (ii) a mapping of the virtual SQL ontologies to existing databases accessible in SQL. The SQL Knowledge Graph closes the gap between knowledge representation and enterprise databases/legacy systems/data warehouses/data lakes, to conveniently enable smart, semantic data fabrics and digital twins without need to change DBMS infrastructure.

Category: General

timbr offers a fast, easy and no-risk implementation of the semantic graph. The main reasons are that there’s no need to move data or learn any new proprietary query languages to work with the Knowledge Graph.

Modeling a SQL ontology can be done either manually or automatically from an ERD, OWL ontologies, or from data catalogs.

The mapping of the data to the Knowledge Graph is also done either manually or semi-automatically.

Category: General

Conceptual modeling is a representation of the real world. It is the first step of data modeling, a method developed to help with the design of databases and defining a formal vocabulary for the organization.

The process leading to the actual modeling and creation of databases leaves out information that is key to understanding and using data effectively. To make up for this information left behind, enterprises require coding complex queries in complex applications.

Ontologies are an effective means to re-create the information left behind, giving back business meaning to the data, simplifying data access and delivering unique analytical capabilities.

Category: General

An ontology defines a common vocabulary for an organization that needs to share information in a domain.
This includes machine-interpretable definitions of basic concepts in the domain and relations among them.

An ontology is structured as a graph, where every node on the graph represents a “concept.”
A concept could be anything: Person, Place, Customer, Car, Country, Product, Event etc.

Category: General

SQL ontologies are ontologies that implement the Semantic Web in SQL (what is an ontology?) and are designed to provide common business meaning to data distributed in varied sources and enable them as concepts with inference and graph traversal capabilities to facilitate discovery, use and access to data.
With timbr you can model and explore your ontology visually or in standard SQL. The SQL Ontology is exposed to the SQL user as a virtual schema with virtual tables (concepts) using any SQL client with JDBC/ODBC.

Category: General

See here:

Category: General

Graph Data Exploration is timbr’s module that allows users to visualize and navigate the virtual Knowledge Graph. Data consumers, business analysts and domain experts can visually explore and discover relationships, quickly finding answers to their questions.

Category: General

Semantic SQL is SQL used for querying SQL ontologies instead of directly querying the underlying data. By querying the ontology’s concepts, users benefit from graph traversals and semantic reasoning features, so SQL queries become significantly less complex and query size is reduced significantly.

Category: General

A semantic data catalog is an intelligent catalog/inventory of data assets that automatizes sharing common meanings of data across data silos and provides a means to define hierarchies and relationships featuring semantic reasoning. It serves as a queryable, AI-enabled knowledge encyclopedia of the organization. timbr enables the fastest and most convenient implementation of semantic data catalogs connected to your databases and business intelligence tools. Contact us to schedule a demo.

Category: General

The semantic data fabric is a flexible, reusable layer and set of data services used as the single source providing universal meaning and context to data for the entire organization. The data fabric integrates on-premise and cloud data sources in use by the organization, handing them semantic capabilities to provide answers to complex queries and to facilitate understanding and use of data. It provides consistent capabilities across on-premises and multiple cloud environments to accelerate digital transformation. timbr enables the fastest and most convenient implementation of semantic data fabric connected to your cloud and on-premise databases and business intelligence tools. Contact us to schedule a demo.

Category: General

A digital twin refers to a digital replica of potential and actual physical assets, processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how an Internet of things (IoT) device operates and lives throughout its life cycle.
Digital twins have two important characteristics.
1. each definition emphasizes the connection between the physical model and the corresponding virtual model or virtual counterpart.
2. this connection is established by generating real-time data using sensors.
timbr helps enterprises create digital twins by enabling the definition of the virtual model using SQL ontologies and by connecting the virtual model to data lakes that contain the sensor’s data. Contact us to schedule a demo to see why timbr facilitates the fastest and most convenient implementation of digital twins.

Category: General

The Semantic Web is a project devised by Tim Berners Lee and James Hendler (et al), and adopted by the W3C (the manager of the Internet). The Semantic Web implements ontologies so that machines connected to the Web “understand” each other by sharing common meaning of data using a set of standards. The standards developed by the W3C define among others, an ontology modeling language (OWL) and a query language (SPARQL).

timbr implements the principles of the Semantic Web in standard SQL, meaning that both the ontology modeling and the queries are done in SQL.

Category: General

Creating a SQL Knowledge Graph is a simple process:

1. Connect your databases to the virtual layer using JDBC connectors.

2. Model the SQL ontology visually or using timbr SQL DDL statements, or import from other sources (data catalogs, OWL ontologies, ERD tools).

3. Map the ontology concepts to the data.

That’s it, your SQL Knowledge Graph is ready for use and can start delivering unique insights via SQL queries, graph data exploration, your BI tools, or using timbr’s embedded charts and dashboard module.

Category: General

No, you just need a database, timbr will guide you through the rest of the simple process.

Category: General

The SQL Knowledge Graph serves as a virtual graph for all the enterprise data engines. Organizations use it to integrate, analyze and explore their data sources and silos of information without the need to move or transform data. Data consumers benefit from a 360° access to data to get fast answers to key business questions. By querying concepts instead of the tables, SQL queries are reduced in length and complexity significantly. The SQL Knowledge Graph seamlessly integrates with popular business intelligence tools so business analysts can focus on the business questions and derive deeper insights.

Category: General

timbr is not a database. timbr is a platform used for creating virtual SQL Knowledge Graphs that enable semantic (ontology-based) graph capabilities on existing data engines (data warehouses and data lakes). The SQL Knowledge Graphs integrate data sources into a semantic data fabric queryable in SQL. timbr does not require to copy or transform data (no ETL operations), no new DBMS infrastructure and no new skills as required by graph databases.

Category: General

No, it is not possible. Property graphs use proprietary query languages lacking in semantics (unlike Knowledge Graphs which are based on RDF, SPARQL and OWL). Currently, timbr works with data engines that support SQL (mainly data warehouses and data lakes).

Category: General

Exploring relationships is done by using timbr’s Graph Data Exploration module.

Category: General

There’s no community version of timbr, but any organization with a use-case in mind can contact us asking for credentials to test drive timbr free of cost.

Category: General

If your database is HIPAA complaint then timbr is as well.

Category: General

If your database is GDPR complaint then timbr is as well.

Category: General

A knowledge graph is a knowledge base that uses a graph-structured data model or topology to integrate data. Knowledge graphs are often used to store interlinked descriptions of objects, events or concepts with free-form semantics. Knowledge graphs use ontologies to put data in context via linking and semantic metadata and this way provide a framework for data integration, unification, analytics and sharing.

They are also prominently associated with and used by Google, Bing, and Yahoo, and with question-answering services such as Google Assistant, Siri and Alexa. All these examples were developed with proprietary tools.

For organizations that look to benefit from knowledge graphs, the available solutions in the market require significant changes in their IT departments. This is due to the fact that most data in the world is stored in formats that are not compatible with the format in which data is stored in knowledge graphs, so data needs to be extracted from its current DBMS, transformed to a new format and loaded into a separate, suitable DBMS. Another reason being is that to use knowledge graphs, data engineers and consumers need to acquire news skills to model in OWL and query in SPARQL.

Different from most other solutions, the timbr SQL Knowledge Graph platform creates a virtual layer that works in standard SQL to seamlessly connect to existing databases and is implemented without requiring new skills.
Contact us to learn how timbr can help your organization join the knowledge revolution.

Category: General

Load More

Ontology Implementation

General

timbr is a platform that enables the creation of virtual SQL Knowledge Graphs over any data engine, used as intelligent enterprise data fabric and data catalog.

Category: General

Timbr is named after Tim Berners Lee who, together with timbr.io’s advisor Jim Hendler, pioneered the Semantic Web.

Category: General

A SQL Knowledge Graph is the implementation of ontologies and graph theory in standard SQL. It has two components: (i) a virtual SQL ontology of connected, context-enriched concepts with inference capabilities and graph analytics features and, (ii) a mapping of the virtual SQL ontologies to existing databases accessible in SQL. The SQL Knowledge Graph closes the gap between knowledge representation and enterprise databases/legacy systems/data warehouses/data lakes, to conveniently enable smart, semantic data fabrics and digital twins without need to change DBMS infrastructure.

Category: General

timbr offers a fast, easy and no-risk implementation of the semantic graph. The main reasons are that there’s no need to move data or learn any new proprietary query languages to work with the Knowledge Graph.

Modeling a SQL ontology can be done either manually or automatically from an ERD, OWL ontologies, or from data catalogs.

The mapping of the data to the Knowledge Graph is also done either manually or semi-automatically.

Category: General

Conceptual modeling is a representation of the real world. It is the first step of data modeling, a method developed to help with the design of databases and defining a formal vocabulary for the organization.

The process leading to the actual modeling and creation of databases leaves out information that is key to understanding and using data effectively. To make up for this information left behind, enterprises require coding complex queries in complex applications.

Ontologies are an effective means to re-create the information left behind, giving back business meaning to the data, simplifying data access and delivering unique analytical capabilities.

Category: General

An ontology defines a common vocabulary for an organization that needs to share information in a domain.
This includes machine-interpretable definitions of basic concepts in the domain and relations among them.

An ontology is structured as a graph, where every node on the graph represents a “concept.”
A concept could be anything: Person, Place, Customer, Car, Country, Product, Event etc.

Category: General

SQL ontologies are ontologies that implement the Semantic Web in SQL (what is an ontology?) and are designed to provide common business meaning to data distributed in varied sources and enable them as concepts with inference and graph traversal capabilities to facilitate discovery, use and access to data.
With timbr you can model and explore your ontology visually or in standard SQL. The SQL Ontology is exposed to the SQL user as a virtual schema with virtual tables (concepts) using any SQL client with JDBC/ODBC.

Category: General

See here:

Category: General

Graph Data Exploration is timbr’s module that allows users to visualize and navigate the virtual Knowledge Graph. Data consumers, business analysts and domain experts can visually explore and discover relationships, quickly finding answers to their questions.

Category: General

Semantic SQL is SQL used for querying SQL ontologies instead of directly querying the underlying data. By querying the ontology’s concepts, users benefit from graph traversals and semantic reasoning features, so SQL queries become significantly less complex and query size is reduced significantly.

Category: General

A semantic data catalog is an intelligent catalog/inventory of data assets that automatizes sharing common meanings of data across data silos and provides a means to define hierarchies and relationships featuring semantic reasoning. It serves as a queryable, AI-enabled knowledge encyclopedia of the organization. timbr enables the fastest and most convenient implementation of semantic data catalogs connected to your databases and business intelligence tools. Contact us to schedule a demo.

Category: General

The semantic data fabric is a flexible, reusable layer and set of data services used as the single source providing universal meaning and context to data for the entire organization. The data fabric integrates on-premise and cloud data sources in use by the organization, handing them semantic capabilities to provide answers to complex queries and to facilitate understanding and use of data. It provides consistent capabilities across on-premises and multiple cloud environments to accelerate digital transformation. timbr enables the fastest and most convenient implementation of semantic data fabric connected to your cloud and on-premise databases and business intelligence tools. Contact us to schedule a demo.

Category: General

A digital twin refers to a digital replica of potential and actual physical assets, processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how an Internet of things (IoT) device operates and lives throughout its life cycle.
Digital twins have two important characteristics.
1. each definition emphasizes the connection between the physical model and the corresponding virtual model or virtual counterpart.
2. this connection is established by generating real-time data using sensors.
timbr helps enterprises create digital twins by enabling the definition of the virtual model using SQL ontologies and by connecting the virtual model to data lakes that contain the sensor’s data. Contact us to schedule a demo to see why timbr facilitates the fastest and most convenient implementation of digital twins.

Category: General

The Semantic Web is a project devised by Tim Berners Lee and James Hendler (et al), and adopted by the W3C (the manager of the Internet). The Semantic Web implements ontologies so that machines connected to the Web “understand” each other by sharing common meaning of data using a set of standards. The standards developed by the W3C define among others, an ontology modeling language (OWL) and a query language (SPARQL).

timbr implements the principles of the Semantic Web in standard SQL, meaning that both the ontology modeling and the queries are done in SQL.

Category: General

Creating a SQL Knowledge Graph is a simple process:

1. Connect your databases to the virtual layer using JDBC connectors.

2. Model the SQL ontology visually or using timbr SQL DDL statements, or import from other sources (data catalogs, OWL ontologies, ERD tools).

3. Map the ontology concepts to the data.

That’s it, your SQL Knowledge Graph is ready for use and can start delivering unique insights via SQL queries, graph data exploration, your BI tools, or using timbr’s embedded charts and dashboard module.

Category: General

No, you just need a database, timbr will guide you through the rest of the simple process.

Category: General

The SQL Knowledge Graph serves as a virtual graph for all the enterprise data engines. Organizations use it to integrate, analyze and explore their data sources and silos of information without the need to move or transform data. Data consumers benefit from a 360° access to data to get fast answers to key business questions. By querying concepts instead of the tables, SQL queries are reduced in length and complexity significantly. The SQL Knowledge Graph seamlessly integrates with popular business intelligence tools so business analysts can focus on the business questions and derive deeper insights.

Category: General

timbr is not a database. timbr is a platform used for creating virtual SQL Knowledge Graphs that enable semantic (ontology-based) graph capabilities on existing data engines (data warehouses and data lakes). The SQL Knowledge Graphs integrate data sources into a semantic data fabric queryable in SQL. timbr does not require to copy or transform data (no ETL operations), no new DBMS infrastructure and no new skills as required by graph databases.

Category: General

No, it is not possible. Property graphs use proprietary query languages lacking in semantics (unlike Knowledge Graphs which are based on RDF, SPARQL and OWL). Currently, timbr works with data engines that support SQL (mainly data warehouses and data lakes).

Category: General

Exploring relationships is done by using timbr’s Graph Data Exploration module.

Category: General

There’s no community version of timbr, but any organization with a use-case in mind can contact us asking for credentials to test drive timbr free of cost.

Category: General

If your database is HIPAA complaint then timbr is as well.

Category: General

If your database is GDPR complaint then timbr is as well.

Category: General

A knowledge graph is a knowledge base that uses a graph-structured data model or topology to integrate data. Knowledge graphs are often used to store interlinked descriptions of objects, events or concepts with free-form semantics. Knowledge graphs use ontologies to put data in context via linking and semantic metadata and this way provide a framework for data integration, unification, analytics and sharing.

They are also prominently associated with and used by Google, Bing, and Yahoo, and with question-answering services such as Google Assistant, Siri and Alexa. All these examples were developed with proprietary tools.

For organizations that look to benefit from knowledge graphs, the available solutions in the market require significant changes in their IT departments. This is due to the fact that most data in the world is stored in formats that are not compatible with the format in which data is stored in knowledge graphs, so data needs to be extracted from its current DBMS, transformed to a new format and loaded into a separate, suitable DBMS. Another reason being is that to use knowledge graphs, data engineers and consumers need to acquire news skills to model in OWL and query in SPARQL.

Different from most other solutions, the timbr SQL Knowledge Graph platform creates a virtual layer that works in standard SQL to seamlessly connect to existing databases and is implemented without requiring new skills.
Contact us to learn how timbr can help your organization join the knowledge revolution.

Category: General

Load More

Performance

General

timbr is a platform that enables the creation of virtual SQL Knowledge Graphs over any data engine, used as intelligent enterprise data fabric and data catalog.

Category: General

Timbr is named after Tim Berners Lee who, together with timbr.io’s advisor Jim Hendler, pioneered the Semantic Web.

Category: General

A SQL Knowledge Graph is the implementation of ontologies and graph theory in standard SQL. It has two components: (i) a virtual SQL ontology of connected, context-enriched concepts with inference capabilities and graph analytics features and, (ii) a mapping of the virtual SQL ontologies to existing databases accessible in SQL. The SQL Knowledge Graph closes the gap between knowledge representation and enterprise databases/legacy systems/data warehouses/data lakes, to conveniently enable smart, semantic data fabrics and digital twins without need to change DBMS infrastructure.

Category: General

timbr offers a fast, easy and no-risk implementation of the semantic graph. The main reasons are that there’s no need to move data or learn any new proprietary query languages to work with the Knowledge Graph.

Modeling a SQL ontology can be done either manually or automatically from an ERD, OWL ontologies, or from data catalogs.

The mapping of the data to the Knowledge Graph is also done either manually or semi-automatically.

Category: General

Conceptual modeling is a representation of the real world. It is the first step of data modeling, a method developed to help with the design of databases and defining a formal vocabulary for the organization.

The process leading to the actual modeling and creation of databases leaves out information that is key to understanding and using data effectively. To make up for this information left behind, enterprises require coding complex queries in complex applications.

Ontologies are an effective means to re-create the information left behind, giving back business meaning to the data, simplifying data access and delivering unique analytical capabilities.

Category: General

An ontology defines a common vocabulary for an organization that needs to share information in a domain.
This includes machine-interpretable definitions of basic concepts in the domain and relations among them.

An ontology is structured as a graph, where every node on the graph represents a “concept.”
A concept could be anything: Person, Place, Customer, Car, Country, Product, Event etc.

Category: General

SQL ontologies are ontologies that implement the Semantic Web in SQL (what is an ontology?) and are designed to provide common business meaning to data distributed in varied sources and enable them as concepts with inference and graph traversal capabilities to facilitate discovery, use and access to data.
With timbr you can model and explore your ontology visually or in standard SQL. The SQL Ontology is exposed to the SQL user as a virtual schema with virtual tables (concepts) using any SQL client with JDBC/ODBC.

Category: General

See here:

Category: General

Graph Data Exploration is timbr’s module that allows users to visualize and navigate the virtual Knowledge Graph. Data consumers, business analysts and domain experts can visually explore and discover relationships, quickly finding answers to their questions.

Category: General

Semantic SQL is SQL used for querying SQL ontologies instead of directly querying the underlying data. By querying the ontology’s concepts, users benefit from graph traversals and semantic reasoning features, so SQL queries become significantly less complex and query size is reduced significantly.

Category: General

A semantic data catalog is an intelligent catalog/inventory of data assets that automatizes sharing common meanings of data across data silos and provides a means to define hierarchies and relationships featuring semantic reasoning. It serves as a queryable, AI-enabled knowledge encyclopedia of the organization. timbr enables the fastest and most convenient implementation of semantic data catalogs connected to your databases and business intelligence tools. Contact us to schedule a demo.

Category: General

The semantic data fabric is a flexible, reusable layer and set of data services used as the single source providing universal meaning and context to data for the entire organization. The data fabric integrates on-premise and cloud data sources in use by the organization, handing them semantic capabilities to provide answers to complex queries and to facilitate understanding and use of data. It provides consistent capabilities across on-premises and multiple cloud environments to accelerate digital transformation. timbr enables the fastest and most convenient implementation of semantic data fabric connected to your cloud and on-premise databases and business intelligence tools. Contact us to schedule a demo.

Category: General

A digital twin refers to a digital replica of potential and actual physical assets, processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how an Internet of things (IoT) device operates and lives throughout its life cycle.
Digital twins have two important characteristics.
1. each definition emphasizes the connection between the physical model and the corresponding virtual model or virtual counterpart.
2. this connection is established by generating real-time data using sensors.
timbr helps enterprises create digital twins by enabling the definition of the virtual model using SQL ontologies and by connecting the virtual model to data lakes that contain the sensor’s data. Contact us to schedule a demo to see why timbr facilitates the fastest and most convenient implementation of digital twins.

Category: General

The Semantic Web is a project devised by Tim Berners Lee and James Hendler (et al), and adopted by the W3C (the manager of the Internet). The Semantic Web implements ontologies so that machines connected to the Web “understand” each other by sharing common meaning of data using a set of standards. The standards developed by the W3C define among others, an ontology modeling language (OWL) and a query language (SPARQL).

timbr implements the principles of the Semantic Web in standard SQL, meaning that both the ontology modeling and the queries are done in SQL.

Category: General

Creating a SQL Knowledge Graph is a simple process:

1. Connect your databases to the virtual layer using JDBC connectors.

2. Model the SQL ontology visually or using timbr SQL DDL statements, or import from other sources (data catalogs, OWL ontologies, ERD tools).

3. Map the ontology concepts to the data.

That’s it, your SQL Knowledge Graph is ready for use and can start delivering unique insights via SQL queries, graph data exploration, your BI tools, or using timbr’s embedded charts and dashboard module.

Category: General

No, you just need a database, timbr will guide you through the rest of the simple process.

Category: General

The SQL Knowledge Graph serves as a virtual graph for all the enterprise data engines. Organizations use it to integrate, analyze and explore their data sources and silos of information without the need to move or transform data. Data consumers benefit from a 360° access to data to get fast answers to key business questions. By querying concepts instead of the tables, SQL queries are reduced in length and complexity significantly. The SQL Knowledge Graph seamlessly integrates with popular business intelligence tools so business analysts can focus on the business questions and derive deeper insights.

Category: General

timbr is not a database. timbr is a platform used for creating virtual SQL Knowledge Graphs that enable semantic (ontology-based) graph capabilities on existing data engines (data warehouses and data lakes). The SQL Knowledge Graphs integrate data sources into a semantic data fabric queryable in SQL. timbr does not require to copy or transform data (no ETL operations), no new DBMS infrastructure and no new skills as required by graph databases.

Category: General

No, it is not possible. Property graphs use proprietary query languages lacking in semantics (unlike Knowledge Graphs which are based on RDF, SPARQL and OWL). Currently, timbr works with data engines that support SQL (mainly data warehouses and data lakes).

Category: General

Exploring relationships is done by using timbr’s Graph Data Exploration module.

Category: General

There’s no community version of timbr, but any organization with a use-case in mind can contact us asking for credentials to test drive timbr free of cost.

Category: General

If your database is HIPAA complaint then timbr is as well.

Category: General

If your database is GDPR complaint then timbr is as well.

Category: General

A knowledge graph is a knowledge base that uses a graph-structured data model or topology to integrate data. Knowledge graphs are often used to store interlinked descriptions of objects, events or concepts with free-form semantics. Knowledge graphs use ontologies to put data in context via linking and semantic metadata and this way provide a framework for data integration, unification, analytics and sharing.

They are also prominently associated with and used by Google, Bing, and Yahoo, and with question-answering services such as Google Assistant, Siri and Alexa. All these examples were developed with proprietary tools.

For organizations that look to benefit from knowledge graphs, the available solutions in the market require significant changes in their IT departments. This is due to the fact that most data in the world is stored in formats that are not compatible with the format in which data is stored in knowledge graphs, so data needs to be extracted from its current DBMS, transformed to a new format and loaded into a separate, suitable DBMS. Another reason being is that to use knowledge graphs, data engineers and consumers need to acquire news skills to model in OWL and query in SPARQL.

Different from most other solutions, the timbr SQL Knowledge Graph platform creates a virtual layer that works in standard SQL to seamlessly connect to existing databases and is implemented without requiring new skills.
Contact us to learn how timbr can help your organization join the knowledge revolution.

Category: General

Load More

General

timbr is a platform that enables the creation of virtual SQL Knowledge Graphs over any data engine, used as intelligent enterprise data fabric and data catalog.

Category: General

Timbr is named after Tim Berners Lee who, together with timbr.io’s advisor Jim Hendler, pioneered the Semantic Web.

Category: General

A SQL Knowledge Graph is the implementation of ontologies and graph theory in standard SQL. It has two components: (i) a virtual SQL ontology of connected, context-enriched concepts with inference capabilities and graph analytics features and, (ii) a mapping of the virtual SQL ontologies to existing databases accessible in SQL. The SQL Knowledge Graph closes the gap between knowledge representation and enterprise databases/legacy systems/data warehouses/data lakes, to conveniently enable smart, semantic data fabrics and digital twins without need to change DBMS infrastructure.

Category: General

timbr offers a fast, easy and no-risk implementation of the semantic graph. The main reasons are that there’s no need to move data or learn any new proprietary query languages to work with the Knowledge Graph.

Modeling a SQL ontology can be done either manually or automatically from an ERD, OWL ontologies, or from data catalogs.

The mapping of the data to the Knowledge Graph is also done either manually or semi-automatically.

Category: General

Conceptual modeling is a representation of the real world. It is the first step of data modeling, a method developed to help with the design of databases and defining a formal vocabulary for the organization.

The process leading to the actual modeling and creation of databases leaves out information that is key to understanding and using data effectively. To make up for this information left behind, enterprises require coding complex queries in complex applications.

Ontologies are an effective means to re-create the information left behind, giving back business meaning to the data, simplifying data access and delivering unique analytical capabilities.

Category: General

An ontology defines a common vocabulary for an organization that needs to share information in a domain.
This includes machine-interpretable definitions of basic concepts in the domain and relations among them.

An ontology is structured as a graph, where every node on the graph represents a “concept.”
A concept could be anything: Person, Place, Customer, Car, Country, Product, Event etc.

Category: General

SQL ontologies are ontologies that implement the Semantic Web in SQL (what is an ontology?) and are designed to provide common business meaning to data distributed in varied sources and enable them as concepts with inference and graph traversal capabilities to facilitate discovery, use and access to data.
With timbr you can model and explore your ontology visually or in standard SQL. The SQL Ontology is exposed to the SQL user as a virtual schema with virtual tables (concepts) using any SQL client with JDBC/ODBC.

Category: General

See here:

Category: General

Graph Data Exploration is timbr’s module that allows users to visualize and navigate the virtual Knowledge Graph. Data consumers, business analysts and domain experts can visually explore and discover relationships, quickly finding answers to their questions.

Category: General

Semantic SQL is SQL used for querying SQL ontologies instead of directly querying the underlying data. By querying the ontology’s concepts, users benefit from graph traversals and semantic reasoning features, so SQL queries become significantly less complex and query size is reduced significantly.

Category: General

A semantic data catalog is an intelligent catalog/inventory of data assets that automatizes sharing common meanings of data across data silos and provides a means to define hierarchies and relationships featuring semantic reasoning. It serves as a queryable, AI-enabled knowledge encyclopedia of the organization. timbr enables the fastest and most convenient implementation of semantic data catalogs connected to your databases and business intelligence tools. Contact us to schedule a demo.

Category: General

The semantic data fabric is a flexible, reusable layer and set of data services used as the single source providing universal meaning and context to data for the entire organization. The data fabric integrates on-premise and cloud data sources in use by the organization, handing them semantic capabilities to provide answers to complex queries and to facilitate understanding and use of data. It provides consistent capabilities across on-premises and multiple cloud environments to accelerate digital transformation. timbr enables the fastest and most convenient implementation of semantic data fabric connected to your cloud and on-premise databases and business intelligence tools. Contact us to schedule a demo.

Category: General

A digital twin refers to a digital replica of potential and actual physical assets, processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how an Internet of things (IoT) device operates and lives throughout its life cycle.
Digital twins have two important characteristics.
1. each definition emphasizes the connection between the physical model and the corresponding virtual model or virtual counterpart.
2. this connection is established by generating real-time data using sensors.
timbr helps enterprises create digital twins by enabling the definition of the virtual model using SQL ontologies and by connecting the virtual model to data lakes that contain the sensor’s data. Contact us to schedule a demo to see why timbr facilitates the fastest and most convenient implementation of digital twins.

Category: General

The Semantic Web is a project devised by Tim Berners Lee and James Hendler (et al), and adopted by the W3C (the manager of the Internet). The Semantic Web implements ontologies so that machines connected to the Web “understand” each other by sharing common meaning of data using a set of standards. The standards developed by the W3C define among others, an ontology modeling language (OWL) and a query language (SPARQL).

timbr implements the principles of the Semantic Web in standard SQL, meaning that both the ontology modeling and the queries are done in SQL.

Category: General

Creating a SQL Knowledge Graph is a simple process:

1. Connect your databases to the virtual layer using JDBC connectors.

2. Model the SQL ontology visually or using timbr SQL DDL statements, or import from other sources (data catalogs, OWL ontologies, ERD tools).

3. Map the ontology concepts to the data.

That’s it, your SQL Knowledge Graph is ready for use and can start delivering unique insights via SQL queries, graph data exploration, your BI tools, or using timbr’s embedded charts and dashboard module.

Category: General

No, you just need a database, timbr will guide you through the rest of the simple process.

Category: General

The SQL Knowledge Graph serves as a virtual graph for all the enterprise data engines. Organizations use it to integrate, analyze and explore their data sources and silos of information without the need to move or transform data. Data consumers benefit from a 360° access to data to get fast answers to key business questions. By querying concepts instead of the tables, SQL queries are reduced in length and complexity significantly. The SQL Knowledge Graph seamlessly integrates with popular business intelligence tools so business analysts can focus on the business questions and derive deeper insights.

Category: General

timbr is not a database. timbr is a platform used for creating virtual SQL Knowledge Graphs that enable semantic (ontology-based) graph capabilities on existing data engines (data warehouses and data lakes). The SQL Knowledge Graphs integrate data sources into a semantic data fabric queryable in SQL. timbr does not require to copy or transform data (no ETL operations), no new DBMS infrastructure and no new skills as required by graph databases.

Category: General

No, it is not possible. Property graphs use proprietary query languages lacking in semantics (unlike Knowledge Graphs which are based on RDF, SPARQL and OWL). Currently, timbr works with data engines that support SQL (mainly data warehouses and data lakes).

Category: General

Exploring relationships is done by using timbr’s Graph Data Exploration module.

Category: General

There’s no community version of timbr, but any organization with a use-case in mind can contact us asking for credentials to test drive timbr free of cost.

Category: General

If your database is HIPAA complaint then timbr is as well.

Category: General

If your database is GDPR complaint then timbr is as well.

Category: General

A knowledge graph is a knowledge base that uses a graph-structured data model or topology to integrate data. Knowledge graphs are often used to store interlinked descriptions of objects, events or concepts with free-form semantics. Knowledge graphs use ontologies to put data in context via linking and semantic metadata and this way provide a framework for data integration, unification, analytics and sharing.

They are also prominently associated with and used by Google, Bing, and Yahoo, and with question-answering services such as Google Assistant, Siri and Alexa. All these examples were developed with proprietary tools.

For organizations that look to benefit from knowledge graphs, the available solutions in the market require significant changes in their IT departments. This is due to the fact that most data in the world is stored in formats that are not compatible with the format in which data is stored in knowledge graphs, so data needs to be extracted from its current DBMS, transformed to a new format and loaded into a separate, suitable DBMS. Another reason being is that to use knowledge graphs, data engineers and consumers need to acquire news skills to model in OWL and query in SPARQL.

Different from most other solutions, the timbr SQL Knowledge Graph platform creates a virtual layer that works in standard SQL to seamlessly connect to existing databases and is implemented without requiring new skills.
Contact us to learn how timbr can help your organization join the knowledge revolution.

Category: General

Load More