Industry & Engineering

Industry

How Semantics even can improve a market leading digital product and optimize it's production workflow!

How a software integrator can ease the editorial process, optimize production and deliver outstanding user experience by utilising technologies like MarkLogic and semantics.

Industry

Technical Documentation in the age of Industrie 4.0

Based on the technological concepts of cyber-physical systems, the Internet of Things and the Internet of Services, the vision of smart factories is summarized as “Industrie 4.0”. The goal: a smart factory that works adaptable and resource-efficient, integrating customers and partners into the business and value-added processes. Cyber-physical systems combine software technical components with mechanical and electronic parts.

Semantic technologies are seen as a key to the realization of such systems semantic technologies. They are able to integrate all product and production process relevant data and build a layer of connected information within one single model.
However, technical documentation for machinery and equipment actually still describes traditionally closed technical systems with clearly defined functions and components. The documentation for the manufactured products is also based on a fixed, predetermined product. Instead, documentation in the Age of Industrie 4.0 has to use flexible and topic oriented approaches to cover the adaptive and individualized products and services they are describing. Furthermore they also must support applications such as the operation and maintenance of the parts.

LODFlow – a Workflow Management System for Linked Data Processing

The extraction and maintenance of Linked Data datasets is a cumbersome, time-consuming and resource-intensive activity. The cost for producing Linked Data can be reduced by a workflow management system, which describes plans to systematically support the lifecycle of RDF datasets. We present the LODFlow Linked Data Workflow Management System, which provides an environment for planning, executing, reusing, and documenting Linked Data workflows.The LODFlow approach is based on a comprehensive knowledge model for describing the workflows and a workflow execution engine supporting systematic workflow execution, reporting, and exception handling. The environment was evaluated in a large-scale real-world use case. As result, LODFlow supports Linked Data engineers to systematically plan, execute and assess Linked Data production and maintenance workflows, thus improving efficiency, ease-of-use, reproducibility, reuseability and provenance.