Merging DEL and ETL

Merging Frameworks for Interaction

A variety of logical frameworks have been developed to study rational agents interacting over time. This paper takes a closer look at one particular interface, between two systems that both address the dynamics of knowledge and information flow. The first is Epistemic Temporal Logic (ETL) which uses linear or branching time models with added epistemic structure induced by agents’ different capa...

Merging ETL Processes

Automatic Generation of Data Merging Program Codes

Data merging is an essential part of ETL (Extract-Transform-Load) processes to build a data warehouse system. To avoid rewheeling merging techniques, we propose a Data Merging Meta-model (DMM) and its transformation into executable program codes in the manner of model driven engineering. DMM allows defining relationships of different model entities and their merging types in conceptual level. O...

Systematic ETL management - Experiences with high-level operators

Large organizations load much of their data into data warehouses for subsequent querying, analysis, and data mining. Extract-Transform-Load (ETL) workflows populate those data warehouses with data from various data sources by specifying and executing a set of transformations forming a directed acyclic transformation graph (DAG). Over time, hundreds of individual ETL workflows evolve as new sour...

ETL, DEL, and Past Operators

[8] merges the semantic frameworks of Dynamic Epistemic Logic DEL ([1, 3]) and Epistemic Temporal Logic ETL ([2, 6]). We consider the logic TDEL on the merged semantic framework and its extension with the labeled past-operator “P!” (“The event ! has happened before which...”). To axiomatize the extension, we introduce a method to transform a given model into a normal form in a suitable sense. T...