This file was created by the TYPO3 extension
bib
--- Timezone: UTC
Creation date: 2025-01-15
Creation time: 18-46-28
--- Number of references
5
inproceedings
2020_gleim_factdag_provenance
Expressing FactDAG Provenance with PROV-O
2020
11
1
2821
53-58
To foster data sharing and reuse across organizational boundaries, provenance tracking is of vital importance for the establishment of trust and accountability, especially in industrial applications, but often neglected due to associated overhead. The abstract FactDAG data interoperability model strives to address this challenge by simplifying the creation of provenance-linked knowledge graphs of revisioned (and thus immutable) resources. However, to date, it lacks a practical provenance implementation.
In this work, we present a concrete alignment of all roles and relations in the FactDAG model to the W3C PROV provenance standard, allowing future software implementations to directly produce standard-compliant provenance information. Maintaining compatibility with existing PROV tooling, an implementation of this mapping will pave the way for practical FactDAG implementations and deployments, improving trust and accountability for Open Data through simplified provenance management.
Provenance; Data Lineage; Open Data; Semantic Web Technologies; Ontology Alignment; PROV; RDF; Industry 4.0; Internet of Production; IIoT
internet-of-production
https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-gleim-factdag-provenance.pdf
CEUR Workshop Proceedings
Proceedings of the 6th Workshop on Managing the Evolution and Preservation of the Data Web (MEPDaW '20), co-located with the 19th International Semantic Web Conference (ISWC '20), November 1-6, 2020, Athens, Greece,
Athens, Greece
November 1-6, 2020
1613-0073
1
LarsGleim
LiamTirpitz
JanPennekamp
StefanDecker
inproceedings
2020-kirchhof-wowmom-ccncps
Improving MAC Protocols for Wireless Industrial Networks via Packet Prioritization and Cooperation
2020
8
31
internet-of-production, reflexes
https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-kirchhof-wireless-mac-improvements.pdf
IEEE Computer Society
online
International Symposium on a World of Wireless, Mobile and Multimedia Networks: Workshop on Communication, Computing, and Networking in Cyber Physical Systems (WoWMoM-CCNCPS'2020), August 31 - September 3, 2020, Cork, Ireland
Cork, Ireland
August 31 - September 3, 2020
10.1109/WoWMoM49955.2020.00068
1
Jörg ChristianKirchhof
MartinSerror
RenéGlebke
KlausWehrle
inproceedings
2020-serror-networking-qwin
QWIN: Facilitating QoS in Wireless Industrial Networks Through
Cooperation
2020
6
21
consent
https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-serror-qwin.pdf
https://ieeexplore.ieee.org/abstract/document/9142792
IFIP
online
Proceedings of the 19th IFIP Networking 2020 Conference (NETWORKING '20), June 22-26, 2020, Paris, France
Paris, France
IFIP NETWORKING Conference
June 22-26, 2020
978-3-903176-28-7
1
MartinSerror
EricWagner
RenéGlebke
KlausWehrle
inproceedings
2020-mann-ur-weldseamstudy
Study on weld seam geometry control for connected gas metal arc welding systems
2020
6
https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-mann-weld-seam-geometry-control.pdf
Proceedings of the 2020 Internal Conference on Ubiquitous Robots
Internal Conference on Ubiquitous Robots
June 22-26, 2020
10.1109/UR49135.2020.9144839
1
SamuelMann
RenéGlebke
IkeKunze
DominikScheurenberg
RahulSharma
UweReisgen
KlausWehrle
DirkAbel
article
2020_gleim_factDAG
FactDAG: Formalizing Data Interoperability in an Internet of Production
IEEE Internet of Things Journal
2020
4
14
7
4
3243-3253
In the production industry, the volume, variety and velocity of data as well as the number of deployed protocols increase exponentially due to the influences of IoT advances. While hundreds of isolated solutions exist to utilize this data, e.g., optimizing processes or monitoring machine conditions, the lack of a unified data handling and exchange mechanism hinders the implementation of approaches to improve the quality of decisions and processes in such an interconnected environment.
The vision of an Internet of Production promises the establishment of a Worldwide Lab, where data from every process in the network can be utilized, even interorganizational and across domains. While numerous existing approaches consider interoperability from an interface and communication system perspective, fundamental questions of data and information interoperability remain insufficiently addressed.
In this paper, we identify ten key issues, derived from three distinctive real-world use cases, that hinder large-scale data interoperability for industrial processes. Based on these issues we derive a set of five key requirements for future (IoT) data layers, building upon the FAIR data principles. We propose to address them by creating FactDAG, a conceptual data layer model for maintaining a provenance-based, directed acyclic graph of facts, inspired by successful distributed version-control and collaboration systems. Eventually, such a standardization should greatly shape the future of interoperability in an interconnected production industry.
Data Management; Data Versioning; Interoperability; Industrial Internet of Things; Worldwide Lab
internet-of-production
https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-gleim-iotj-iop-interoperability.pdf
IEEE
2327-4662
10.1109/JIOT.2020.2966402
1
LarsGleim
JanPennekamp
MartinLiebenberg
MelanieBuchsbaum
PhilippNiemietz
SimonKnape
AlexanderEpple
SimonStorms
DanielTrauth
ThomasBergs
ChristianBrecher
StefanDecker
GerhardLakemeyer
KlausWehrle