Organizations across industries increasingly rely on sharing data to drive collaboration, innovation, and business performance. However, securely and efficiently sharing live data across diverse platforms and adhering to varying governance requirements remains a significant challenge. Traditional approaches, such as FTP and proprietary in-data-warehouse solutions, often fail to meet the demands of interoperability, cost, scalability, and low overhead. This paper introduces Delta Sharing, an open protocol we developed in collaboration with industry partners, to overcome these limitations. Delta Sharing leverages open formats like Delta Lake and Apache Parquet alongside simple HTTP APIs to enable seamless, secure, and live data sharing across heterogeneous systems. Since its launch in 2021, Delta Sharing has been adopted by over 4000 enterprises and supported by hundreds of major software and data vendors. We discuss the key challenges in developing Delta Sharing and how our design addresses them. We also present, to our knowledge, the first large-scale study of production data sharing workloads offering insights into this emerging data platform capability.

Automated Production Systems (aPS) are highly complex, long-living mechatronic systems, which are usually programmed according to the standard IEC 61131-3. Control soft-ware development in aPS has to cope with challenges that sharply differ from classical high-level language programming, such as the assurance of maintainability for up to five decades or hard real-time requirements, e.g., to prevent damage to humans in case of a fault. In computer science, object-oriented programming is an established means to increase software reusability and maintainability. However, this approach is seldom used in IEC 61131-3-compliant control software, although the object-oriented extension of the standard (OO-IEC) has been available since 2013. Companies using OO-IEC generally benefit from a drastic reduction in the complexity of their control software. However, certain constellations of OO-IEC elements could lead to runtime problems, which is a crucial problem regarding the hard real-time requirements of aPS to guarantee safety. Therefore, this paper introduces two metrics to detect runtime-critical control software parts and optimization potentials without executing the code or performing time measurements. Using an industrial example, the metrics are evaluated with PLC experts of two companies, who confirmed the reliability and the advantages of the metrics.