Data-Centric and Model-Centric AI: Twin Drivers of Compact and Robust Industry 4.0 Solutions

Data - centric , without data model

alizing large 3D data sets from scientific or medical applications. Transfer functions are particularly important to the quality of direct volume-rendered images. A transfer function assigns optical properties, such as color and opacity, to original values of the data set being visualized. Unfortunately, finding good transfer functions proves difficult. Pat Hanrahan called it one of the top 10 ...

Observation Centric Sensor Data Model

Management of sensor data requires metadata to understand the semantics of observations. While e-science researchers have high demands on metadata, they are selective in entering metadata. The claim in this paper is to focus on the essentials, i.e., the actual observations being described by location, time, owner, instrument, and measurement. The applicability of this approach is demonstrated i...

Automatic Discovery of Data-Centric and Artifact-Centric Processes

Process discovery is a technique that allows for automatically discovering a process model from recorded executions of a process as it happens in reality. This technique has successfully been applied for classical processes where one process execution is constituted by a single case with a unique case identifier. Data-centric and artifact-centric systems such as ERP systems violate this assumpt...

From Process-Centric to Data Centric Replication

Activity-Centric and Artifact-Centric Process Model Roundtrip

Currently, two major process modeling paradigms exist: activitycentric and artifact-centric. They focus on different first class modeling constructs and therefore, they are eligible for different scenarios. Nevertheless, both paradigms compete for users raising the own capabilities over the other’s ones neglecting that both paradigms are compatible to each other such that one can transform one ...