Research Data

Management, Infrastructures and Moduls

 

In cooperation with ZIMT and the University Library, the INF subproject provides a sustainable research data infrastructure for researchers throughout the CRC 1187 and works towards appropriate solutions for research data management. The term research data management refers to all activities to be carried out in the context of research data, which result along the following data life cycle

(source: https://www.forschungsdaten.info/themen/planen-und-strukturieren/datenlebenszyklus/)

 

ZIMT is committed to providing sustainable and quality-assured research data, working on guidelines for research data management as well as the provision of services and advisory structures. ZIMT closely cooperates with partners that already offer infrastructures for user needs in the digital humanities and social sciences (e.g., DARIAH, RADAR, RDA, nestor)

Research Tech Lab

The Research Tech Lab, coordinated by INF and A05, is an open forum for exchange for all members of the SFB 1187. In the Research Tech Lab, we explore, discuss, and design digital research approaches, tools, and instruments. The basic assumption of the Research Tech Lab is that IT design takes place in everyday use and involves the continuous appropriation of (digital) methods, tools, instruments, and infrastructures. Design is an important part of daily research practices. The Research Tech Lab thus calls for participation of all subprojects. Based on a ‘Living Lab’ approach, the subprojects are given the opportunity to discuss, analyse, and reflect their experiences with research tools and infrastructures. Additional room for further exchange and discussion is provided online on the SFB Intranet.

Social Media Observatories

Social Media Observatories provide a platform for students and researchers from all disciplines interested in doing research with or on social media. Developed and maintained by INF, the Social Media Observatories support data collection and analysis of and within social media platforms, including Facebook, X (former Twitter), Instagram, YouTube, and Google+. Particular attention in the extension of the Social Media Observatories rests on supporting the collection not only of public data, but also of semi- and non-public social media data. As part of this effort, INF advices individual projects in assessing, selecting, applying, and extending existing tools and services for monitoring and analysing social media data.

Mobile Data Collection, Mobile Ethnography

To support studies of mobile usage behaviour in natural contexts, INF develops and offers various technical tools based on modern mobile devices (e.g., smart phones, tablets). Tools for mobile data collection enable the gathering of reliable data about contexts of use (e.g., through screenshots/screencasts, audio recordings, GPS information, touch events, motion and position sensors, information about used apps and duration of use). The further development of the tools is primarily aimed at being able to collect usage contexts across devices, which enables, e.g., to capture collocation relationships or to link mobile usage data with additional ethnographic material.

Modules and Platforms

To ensure and facilitate data sharing and reuse, the INF project works towards providing a long-term data storage infrastructure to enhance the overall research process making data more organized and accessible. Accordingly, a D-Space-based research data repository called FoDaSi (Forschungsdaten-Repositorium der Universität Siegen)is made available. This repository is accessible via the E-Science-Service and free of charge for all the researchers of the university. In addition, in collaboration with the E-Science-Service, the INF research data management team provides support and consultation in using new technological possibilities for the entire publication and research process phase.

 

 

As shown in the diagram above, the modules developed aim at bringing an integrated platform where different platforms and tools with different functionalities come together for a common goal of team communication, data sharing, collaborative work, and data archiving. The cloud storage platform, Sciebo, is used only for collaborative work and data sharing, but it is not suitable for long-term storage. Neither does it support the ability to describe research data. Thus, by using the social-media-like communication platform HumHub [named Research Hub], which provides the ability to develop and integrate new modules, researchers are able to see what has been shared in Sciebo – through the OnlineDrives module. Not only are researchers able to see what is shared with them on Sciebo, they are able to describe the data stored in Sciebo – through the Metadata module. The Metadata module is developed by extending the OnlineDrives module where researchers can add a description to their data. The data description helps the research data findable for reuse. The end goal of the integration is to facilitate the process of archiving research data in a repository because research data management by itself is an additional workload for researchers.

In FoDaSi, researchers can archive their invaluable research data items of any type (data set, recordings, articles, working papers, preprints, technical reports, conference papers, etc.) in various digital formats. It supports different subject-specific metadata for indexing the research data and the unique identification of the research items is realized through persistent identifier (DOI).

Data Story

Test cases

To understand the needs of the various disciplines and develop a module that suits the requirements of all the projects, we conducted intensive discussion with several subprojects, joint data session and collected a pilot test at the INF project for the usability of the modules, to collect further requirements and fix possible bugs.

Publications

Curdt, C., V. Hess, A. López, B. Magrean, D. Rudolph und J. Vompras. 2017. „Herausforderung Forschungsdatenmanagement – Unterstützung der Hochschulen durch eine einrichtungsübergreifende Kooperation in NRW“. E-Science-Tage 2017: Forschungsdaten managen. Heidelberg.