Real-life Semantic Web Technology-based Information Sharing via Linked Data Concepts – Metreeca Tools
My last post was the fourth in a series of “spotlight posts” I am using to illuminate practical examples of Real-life Semantic Web Technology-based Information Sharing via Linked Data Concepts. All of these examples support my proposed Enhanced Linked Data Architecture and its current incarnation as the Enhanced Linkeddata Architecture for Persistent Sharing Environments (ELAPSE)™.
My fifth post in this series is focused on Metreeca Tools:
“Metreeca provides your organization with an agile roadmap for kick-starting and leveraging semantic and linked data projects, applying our know-how to resolve current practical problems in a way that will pay back now and in the future.
Metreeca assists data owners and users in developing organization-wide or application-specific knowledge bases that allow data to be shared and reused across application, department and enterprise boundaries .”1
To provided these capabilities, Metreeca’s current toolset includes:
Metreeca Graph Rover
Metreeca Graph Rover is a self‑service search and analysis platform natively designed for W3C-compliant semantic knowledge bases. It enables non-technical users to visually interact with complex data graphs, shielding them from RDF and SPARQL technicalities.
There is a user-friendly search and navigation tool providing an interactive canvas for exploring complex data graphs and for summarizing relevant features as tabular datasets supporting:
– Faceted semantic search, linked data navigation, and set‑based pivoting
– Dynamic user interface, automatically adapting to endpoint contents
– Compatibility with any CORS-enabled SPARQL 1.1 endpoint
UPDATE: Metreeca Graph Rover public beta new 0.37 version is out with the first working examples on DBpedia! Graph Rover is a self service search and analysis platform for SPARQL graph databases that enables business users, with no technical skills, to perform advanced searches and analyses on complex data graphs.
Metreeca Path Finder
Metreeca Path Finder is a causal issue analysis and lightweight dashboarding tool based on the Current Reality Tree (CRT) Thinking Process from Eliyahu M. Goldratt’s Theory of Constraints (TOC). It enables your team to quickly identify core problems and to contextually link them to a coherent and intuitive set of operational key performance indicators (KPIs).
There is a user-friendly modelling tool providing an interactive whiteboard for building real-world causal models and enriching them with a coherent set of operational KPIs and:
– Streamlined user interface with multiple task-focused views
– Automatic real-time highlighting of critical model features
– Contextual specification of operational metrics and KPIs
A lightweight dashboarding tool presents KPIs in the context of causal models, enabling them to be related to each other through causal connections between the underlying entities along with:
– Agile and secure integration with local data sources
– Contextual monitoring and causal analysis of KPI deviations
– Tight integration with self-service semantic data analysis tools
Metreeca Path Finder causal model review
Metreeca states that business data is a unique asset that lives and grows within and outside your organization–and, that achieving your goals depends on sharing, integrating, and analyzing available data. Semantic and linked data technologies were born to provide a common, web-scale framework that makes people and programs more effective at these tasks.
Their tools focus on client needs by developing a shared business vocabulary that: defines how to exchange and interpret data in a coherent way; enables agile data integration from distributed sources; and, enforces data consistency. This “integrated knowledge base” may power a wide range of value-added applications and services, even beyond its initial planned scope, taking advantage of standardized data exchange protocols and formats, such as:
Semantic search, data exploration, and analysis; integrated performance management; and, integrated risk and compliance management
On-the-fly mashup with external, third-party, statistical and reference
Data for marketing and strategic analysis
Publishing of semantic-enriched content and commercial offers
Highly visible to search engines
Business-to-business (B2B) integration with suppliers, customers, and other business partners
Machine-to-machine (M2M) integration and support for IoT applications
– A very informative 4-minute introduction to semantic knowledge management by Metreeca is available here.
– A free to use Solo Edition of the Metreeca Tools is available here. This edition supports the creation of real-world TOC models and KPI systems.
When focused on open source and open standards, the Metreeca tools do implement a number of the same components of my Enhanced Linkeddata Architecture for Persistent Sharing Environments (ELAPSE)™, including:
W3C-compliant semantic knowledge bases
CORS-enabled SPARQL 1.1 endpoints
RDF
SPARQL
My next post will discuss a sixth practical example of Real-life Semantic Web Technology-based Information Sharing via Linked Data Concepts.
=david.l.woolfenden
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