20 RemoteNEPS: data dissemination in a collaborative workspace

Abstract

The German National Educational Panel Study has been set up to collect longitudinal data for educational research. About 60,000 target persons will be questioned and tested within six starting cohorts. This will generate a very large amount of data. Accordingly, one of the most important challenges is to provide comfortable and user-friendly data access that simultaneously allows a high level of data protection. A better infrastructure for research data has been under construction in Germany since the 1990s. Research Data Centers offer a broad range of ways to access data. The National Educational Panel Study is not only matching these common access ways but also developing a remote access solution, called RemoteNEPS. This Secure Data Access will enable users to work with the data from their own computer via a terminal server solution. The data itself will not leave the National Educational Panel Study secure environment. This setting gives the opportunity to provide detailed data to researchers while guaranteeing a high level of data security. As well as providing data security, the concept of RemoteNEPS can be expanded to higher levels of data utility. A community for educational research can be set up to support good scientific practice. Additionally, RemoteNEPS has the capability to handle the structure of the National Educational Panel Study data even after multiple waves or when matching new data from different sources.

OSSDIP: Open Source Secure Data Infrastructure and Processes Supporting Data Visiting

“…The National Education Panel Study (NEPS) hosts a secure data infrastructure capable of handling 50 user simultaneously at a machine cluster consisting of 72 physical cores and 1.344 TB random access memory. Their technical approach is to use a web browser with Java 2 plugin as client software to connect with the secure data infrastructure through a remote desktop server and allows no Internet access within the desktop session (Barkow et al, 2011). They extend conventional approaches like remote execution or job-submission systems e.g.…”

The Research Data Centre for Education (FDZ Bildung): Qualitative Data in the Context of a Social Science Triangulation of Methods

“…Bearing the highest possible use beyond individual requirements in mind, developments are directed toward a universal tool framework. The framework reflects different phases of the data management cycle and it can be immediately implemented, either within operative research processes or their documentation (see Barkow et al, 2011).…”

Cybersecurity risk assessment of VDR

“…Big Data and the Internet of Things (IoT) are being rapidly adopted by the shipping industry to transform many aspects of shipping operations, not only for safety-critical applications and data-driven decision making, but also for real-time monitoring and reducing pollution. New VDR regulations may enhance safe navigation and optimisation, given the large range of ship operating data (Barkow et al., 2011; Danelec, 2021). While the VDR's main purpose is to store information, for compliance with the industry regulations, remote navigational assessments and audits can provide an effective way of navigational safety decision support, rapid analysis following an incident, and lower audit expenses or, more significantly, increase audit frequency (OCIMF, 2020).…”