scholarly journals Data Value Chain in Europe

Author(s):  
Márta Nagy-Rothengass
Keyword(s):  
2020 ◽  
Vol 15 (2) ◽  
pp. 113-122 ◽  
Author(s):  
Shashi Kant Shankar ◽  
Maria Jesus Rodriguez-Triana ◽  
Adolfo Ruiz-Calleja ◽  
Luis P. Prieto ◽  
Pankaj Chejara ◽  
...  

2020 ◽  
Vol 175 ◽  
pp. 737-744
Author(s):  
Abou Zakaria Faroukhi ◽  
Imane El Alaoui ◽  
Youssef Gahi ◽  
Aouatif Amine

2019 ◽  
Vol 304 ◽  
pp. 04002
Author(s):  
Fenareti Lampathaki’ ◽  
Michele Sesana ◽  
Dimitrios Alexandrou

Today, digital transformation has drifted all industries with its proven capacity to improve operations and boost revenues while building a value chain ecosystem. The aeronautics ecosystem is almost unanimously invested in some way into a digital transformation strategy in which data typically plays an instrumental role. However, despite the vast quantity of data across myriad parameters that never stop flowing across the aircraft-passengers-luggage-cargo journeys, the aviation-related stakeholders are still at a relative disadvantage in terms of data gathering and sharing, especially since the eternal questions of “who owns the aircraft” and “who owns the passenger” remain open. In this contact, the present paper focuses on the design and delivery of the ICARUS data and intelligence platform that aims to enable trusted and fair data sharing and insightful data analytics in an end-to-end secure manner. The methodology followed during the implementation of the ICARUS platform is defined, the aviation data value chain is elaborated, the ICARUS Minimum Viable Product is outlined and the theoretical foundations of the ICARUS data management and value enrichment methods are introduced, giving way to a brief reference to the ICARUS unique selling points and platform implementation.


Author(s):  
Rim Louati ◽  
Sonia Mekadmi

The generation of digital devices such as web 2.0, smartphones, social media and sensors has led to a growing rate of data creation. The volume of data available today for organizations is big. Data are produced extensively every day in many forms and from many different sources. Accordingly, firms in several industries are increasingly interested in how to leverage on these “big data” to draw valuable insights from the various kinds of data and to create business value. The aim of this chapter is to provide an integrated view of big data management. A conceptualization of big data value chain is proposed as a research model to help firms understand how to cope with challenges, risks and benefits of big data. The suggested big data value chain recognizes the interdependence between processes, from business problem identification and data capture to generation of valuable insights and decision making. This framework could provide some guidance to business executives and IT practitioners who are going to conduct big data projects in the near future.


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