This paper reports about preparatory work for future standardization that is carried out through an EU coordination and support action titled IM-SAFE. It focuses on applied digital technologies for monitoring and safety, including predictive maintenance of bridges and tunnels. Amidst the improved affordability of digitalization technologies and techniques, the biggest challenge in monitoring and maintenance of bridges and tunnels is no longer about collecting data as much as possible, but about obtaining and exploiting meaningful data throughout the lifecycle of the built assets. An effective and efficient data-driven approach is important to al-low both human experts and computers to make accurate diagnostics, predictions, and decisions. Further standardization is seen as an important part to reach that goal. The work in IM-SAFE related to ICT standardization focuses on the following topics: (1) the general requirements and preconditions for high quality and cost-effective acquisition, transmission, storage and processing of monitoring datasets to ensure the data is fully accessible and machine-interpretable; (2) the relations between the future standards in structural engineering with the open ICT standards for interoperability, especially on Internet of Things (IoT), Building Information Model (BIM), Geographical Information System (GIS), and Semantic Linked Data (LD); (3) a common design of IT platforms to manage monitoring and asset management data of transport infrastructures; (4) the ways to facilitate data analytics technologies, including AI, to be applied for monitoring and asset management of transport infrastructures, and to assess the added value of data-driven approach next to physics-based modelling. With regard to these topics, this paper reports the outcomes from the expert and stakeholder consultations that recently took place within the IM-SAFE pan-European Community of Practice.
For the ‘Rotterdam Project’, a large amount of historical data on patrons of Rotterdam’s main theatres during the ‘long’ 19th century (1773–1914)was collected, digitally registered and statistically analysed. The data was gathered from the theatre archives of the city of Rotterdam and included data on such specifics as ticket sales, repertoire and featured performers. The database holds prosopography information on over 16,000 patrons and almost 15,000registered ticket sales to these patrons. This dataset (https:// doi.org/doi:10.21943/auas.7381127) can be used to make comparisons to the datasets of similarly sized cities in other countries during the same period and for broader re- search on 19th-century cultural history. So far, the data has been mainly applied to empirically test the master narrative of theatre historiography on the social composi- tion of theatre audiences. The analyses based on the data show that this narrative must, for the most part, be rejected.
Data, the raw material from which information is derived, is stored, copied, moved and modified more easily than ever. This quantum leap reaches levels outside our imagination. Surrounded by sensors, recommendation systems, invisible algorithms, spreadsheets and blockchains, the ‘difference that makes a difference’ can no longer be identified. Big Data is a More Data ideology, driven by old school hypergrowth premisses. As Nathan Jurgenson once observed: “Big Data always stands in the shadow of the bigger data to come. The assumption is that there is more data today and there will necessarily be even more tomorrow, an expansion that will bring us ever closer to the inevitable pure ‘data totality.” (2) Nothing symbolizes the current hypergrowth obsession better than Big Data. Let’s investigate what happens when we apply degrowth to data and reserve datafication–as a decolonial project, a collective act of refusal, an ultimate sign of boredom. We’re done with you, data system, stand out of my light.
MULTIFILE
To reach the European Green Deal by 2050, the target for the road transport sector is set at 30% less CO2 emissions by 2030. Given the fact that heavy-duty commercial vehicles throughout Europe are driven nowadays almost exclusively on fossil fuels it is obvious that transition towards reduced emission targets needs to happen seamlessly by hybridization of the existing fleet, with a continuously increasing share of Zero Emission vehicle units. At present, trailing units such as semitrailers do not possess any form of powertrain, being a missed opportunity. By introduction of electrically driven axles into these units the fuel consumption as well as amount of emissions may be reduced substantially while part of the propulsion forces is being supplied on emission-free basis. Furthermore, the electrification of trailing units enables partial recuperation of kinetic energy while braking. Nevertheless, a number of challenges still exist preventing swift integration of these vehicles to daily operation. One of the dominating ones is the intelligent control of the e-axle so it delivers right amount of propulsion/braking power at the right time without receiving detailed information from the towing vehicle (such as e.g. driver control, engine speed, engine torque, or brake pressure, …etc.). This is required mainly to ensure interoperability of e-Trailers in the fleets, which is a must in the logistics nowadays. Therefore the main mission of CHANGE is to generate a chain of knowledge in developing and implementing data driven AI-based applications enabling SMEs of the Dutch trailer industry to contribute to seamless energetic transition towards zero emission road freight transport. In specific, CHANGE will employ e-Trailers (trailers with electrically driven axle(s) enabling energy recuperation) connected to conventional hauling units as well as trailers for high volume and extreme payload as focal platforms (demonstrators) for deployment of these applications.
