Publications

A Generic Research Data Infrastructure for Long Tail Research Data Management

Download publication: A Generic Research Data Infrastructure for Long Tail Research Data Management

The advent of data intensive science has fueled the generation of digital scientific data. Undoubtedly, digital research data plays a pivotal role in transparency and re-producibility of scientific results as well as in steering the innovation in a research process. However, the main challenges for science policy and infrastructure projects are to develop practices and solutions for research data management which in compliance with good scientific standards make the research data discoverable, citeble and accessible for society potential reuse. GeRDI – the Generic Research Data (RD) Infrastructure – is such a research data management initiative which targets long tail content that stems from research communities belonging to different domain and research practices. It provides a generic and open software which connects research data infrastructures of communities to enable the investigation of multidisciplinary research questions.

Download Paper: http://doi.org/10.5334/dsj-2019-017

Author: A. Latif, F. Limani, K. Tochtermann

Publication Year: 2019

Publication: Data Science Journal

Integrated search and analysis of multidisciplinary marine data with GeRDI

Publication: Integrated search and analysis of multidisciplinary marine data with GeRDIAbstract
The GeRDI project focuses on the development of a sustainable Generic Research Data Infrastructure. Its goal is to enable scientists to search, use and re-use external research data. In the current pilot phase, the software development is driven by research questions. These questions originate from participating communities in various research disciplines – marine sciences, but also digital humanities, bioinformatics, and others. An exemplary research question is “How marine fisheries impact on global food security up to 2050”.

Download Paper: Integrated search and analysis of multidisciplinary marine data with GeRDI

Author: I. Thomsen, W. Hasselbring, J. Schmidt, M. Quaas

Publication Year: 2018

Publication: International Conference on Marine Data and Information Systems

Skalierbare datenflussbasierte Architektur – Alles im Fluss

Publication: Research Data Management for Long Tail Research Data Abstract
Skalierbare Software sollte nicht nur elastisch sein, sondern auch mit deren Funktionsumfang und ihrer Entwicklung skalieren. Dies kann bereits im Entwurf der Architektur berücksichtigt werden – aber wie? Damit Entwickler sich der benötigten Funktionen bewusst werden, können diese auf bereits bekannte Konzepte zurückgreifen, wie Datenflussdiagramme. Dieser Beitrag zeigt anhand eines Fallbeispiels, wie diese genutzt werden können, um eine skalierbare Architektur zu entwerfen.

Download Paper: Skalierbare datenflussbasierte Architektur

Author: N. Tavares de Sousa, W. Hasselbring

Publication Year: 2018

Journal: OBJEKTspektrum

Research Data Management for Long Tail Research Data – A Generic Research Data Infrastructure Approach

Publication: Research Data Management for Long Tail Research DataAbstract
[accepted CODATA submission + invitation for extended paper]
Data-enabled research, as a 4th research paradigm, is driving the dissemination of research data (RD) as independent, publishable research artifacts. Many scientific disciplines are producing a lot of RD during or as an end goal of research projects; as a result, RD has now emerged as a 1st class research citizen, breaking away from the “confines” of research publications, with enough traction, added value and its own management ecosystem (metadata description, curation, licensing issues, etc.). The incentives that fuel this growth vary; the research visibility, RD reuse in validation efforts, or scenarios of it being used in novel ways, are just some of the typical drivers for this practice. Read full submission  

Author: A. Latif, F. Limani, K. Tochtermann

Publication Year: 2018

Designing a Generic Research Data Infrastructure Architecture with Continuous Software Engineering

Download Publication: Designing a Generic Research Data Infrastructure Architecture with Continuous Software EngineeringAbstract
Long-living software systems undergo a continuous development including adaptions due to altering requirements or the addition of new features. This is an even greater challenge if neither all users nor requirements are known at an initial design phase. In such a context, complex restructuring activities are much more probable, if the challenges are not taken into account from the beginning. We introduce a combination of the concepts of domain-driven design and self-contained systems to meet these challenges within the system’s architecture design. We show the merits of this approach by designing an architecture for a generic research data infrastructure, a use case where the mentioned challenges can be found. Embedding this approach within continuous software engineering, allows to implement and integrate changes continuously, without neglecting other crucial properties such as maintainability and scalability.

Download Paper: Designing a Generic Research Data Infrastructure Architecture with Continuous Software Engineering

Author: N. Tavares de Sousa, W. Hasselbring, T. Weber, D. Kranzlmüller

Publication Year: 2018

Journal: 3rd Work-shop on Continuous Software Engineering (March 6, 2018, Ulm, Germany), CEUR Workshop Proceedings Vol-2066. pp. 85-88.

Challenges in Creating a Sustainable Generic Research Data Infrastructure

Download Publication: Challenges in Creating a Sustainable Generic Research Data InfrastructureAbstract
Research data management is of the utmost importance in a world where research data is created with an ever increasing amount and rate and with a high variety across all scientifc disciplines. This paper especially discusses software engineering challenges stemming from creating a long-living software system. It aims at providing a reference implementation for a
federated research data infrastructure including interconnected individual repositories for communities and an overarching search based on metadata. The challenges involve a high variety of evolving requirements, the management and development of the distributed and federated infrastructure that are based on existing components, the piloting within the use cases, the efficient training of users, and how to enable the future sustainable operation.

Download Paper: Challenges in Creating a Sustainable Generic Research Data Infrastructure

Author:
R. Grunzke*, R. Muller-Pfefferkorn, W. Nagel
Technische Universitat Dresden, Germany

T. Adolph, C. Biardzki, A. Frank, A. Bode
Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities, Germany

A. Kazakova, F. Limani, A. Latif, A. Busch, T. Borst, K. Tochtermann
ZBW – Leibniz Information Centre for Economics, Germany

M. Neumann, N. Tavares de Sousa, I. Thomsen, W. Hasselbring
Christian-Albrechts-Universitat zu Kiel, Germany

J. Tendel, H.-J. Bungartz, C. Grimm
Verein zur Forderung eines Deutschen Forschungsnetzes e.V., Germany

*corresponding author, richard.grunzke@tu-dresden.de

Publication Year: 2017

Journal: Softwaretechnik-Trends (STT)