damast: Creation of reproducible data processing pipelines
A brief presentation (10min) on (a) the challenges encountered when trying to reuse an existing machine learning project and (b) a developed library/software engineering approach to improve the situation.
Rounding up a machine-learning project to be FAIR - or how software engineering in practice can benefit research projects and researchers
damask source code repository for creating of reproducible data processing pipelines.
The damast documentation contains basic information for using damast python package as well as information on damast API.
Data-centric Research Object aggregating known AIS public datasets that can be used for instance with damast to create a data pipeline.
This work has been derived from work that is part of the T-SAR project (https://www.simula.no/research/projects/t-sar). The TSAR project aims at demonstrating that recent advances in Artificial Intelligence (AI) can be leveraged in the automatic detection of False Data Injection Attacks (FDIA) in transport infrastructures. Some derived work is mainly part of the specific data processing for the 'maritime' domain but could be applied in different domains such as air traffic control, and connected cars.
Roehr, Thomas, Jørgen Schartum Dokken, Anne Fouilloux, Dusica Marijan, and Pierre Bernabé. "damast: Creation of reproducible data processing pipelines." ROHub. Oct 04 ,2022. https://w3id.org/ro-id/42613c9d-9bea-4bc9-b475-1ac886a05d57.
The main objective of Simula is to create knowledge about fundamental scientific challenges that are of genuine value for society.
Economy, business and finance/Economic sector/Manufacturing and engineering/Automotive equipment
detection of False Data Injection Attacks
Economy, business and finance/Economic sector/Transport
Some derived work is mainly part of the specific data processing for the 'maritime' domain but could be applied in different domains such as air traffic control, and connected cars.
This work has been derived from work that is part of the T-SAR project (https://www.simula.no/research/projects/t-sar). The TSAR project aims at demonstrating that recent advances in Artificial Intelligence (AI) can be leveraged in the automatic detection of False Data Injection Attacks (FDIA) in transport infrastructures.
Economy, business and finance/Economic sector/Computing and information technology
Science and technology/Technology and engineering/IT-computer sciences
Economy, business and finance/Economic sector/Energy and resource/Oil and gas - upstream activities
damast: Creation of reproducible data processing pipelines.
Research Object aggregating resources corresponding to the PhD work of Pierre Barnabe at Simula Research Laboratory.
Sketch showing how damast tackles metadata information to improve the FAIRness of data pipelines.
Sketch showing how to improve data processing pipelines with damast.