ViViReq - Assessing the Potential of Interactive Vision Videos for Requirements Engineering

Applicant:

Prof. Dr. Kurt Schneider

Funding:

Deutsche Forschungsgemeinschaft (DFG)

Duration:

2017 - 2020

The goal of this project is to investigate the potential of (interactive) vision videos in requirements engineering. The aim is to develop an approach to integrate vision videos into requirements engineering practice in such a way that software professionals can easily produce and use them. A special focus is to lower the inhibition threshold of software professionals towards the application, i.e., the production and use of videos. In total, three concepts for the integration of vision videos into requirements engineering are analyzed and evaluated:

  1. Avoid common mistakes when dealing with (vision) videos by means of a guideline that includes recommendations on areas such as data protection, film design, and requirements engineering.
  2. Reduce effort by integrating (vision) video production and use into existing requirements engineering practices.
  3. Use (vision) videos as an interactive medium. Interactively changeable (vision) videos allow requirements changes to be presented, alternatives to be compared, and evolving requirements to be accompanied and analyzed.

Through these concepts, interactive vision videos are intended to support the imagination and decision-making of all participants in order to develop a shared vision of the future system, which is essential for the success of a project. The focus is on making the use of vision videos feasible and affordable even for normal software projects, so that no advanced knowledge of video technology, dramaturgy or law is required. This in turn reduces the preparation and evaluation efforts. This constraint of simplicity in terms of knowledge and skills is radically different from other research approaches, and thus makes this approach attractive to smaller companies.

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ORKG - Open Research Knowledge Graph

Applicant:

Prof. Dr. Sören Auer

Funding:

1. TIB - Leibniz Information Centre for Science and Technology

2. European Research Council (ERC) Consolidator Grant

Duration:

Since 2018

Document-based workflows in science have reached (or already exceeded) the limits of adequacy, as demonstrated, for example, by recent discussions about the proliferation of scientific literature and the reproducibility crisis. Although digital access to scientific publications has greatly improved in recent decades, even now that the papers are digitized, they remain document-based, making it difficult to communicate the knowledge they contain. This first step towards digitalization, however, makes it possible to rethink the dominant paradigm of document-centric knowledge sharing and transform it into knowledge-based information flows by expressing these papers through more flexible, fine-grained, semantic, interlinked, and context-sensitive representations in the form of knowledge graphs. The Open Research Knowledge Graph (ORKG) is one concrete research infrastructure that uses a knowledge graph as the underlying data structure to acquire, curate, publish, and process scholarly contributions from scientific papers in a structured and semantic form.

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NFDI4Ing - National Research Data Infrastructure for Engineering Sciences

Co-Applicant:

TIB - Leibniz Information Centre for Science and Technology

Funding:

Deutsche Forschungsgemeinschaft (DFG)

Duration:

Since 2020

Engineering sciences play a key role in developing solutions for the technical, environmental, and economic challenges imposed by the demands of our modern society. The associated research processes and the solutions themselves will only be sustainable if being accompanied by a proper research data management (RDM) that implements the FAIR data principles: data has to be findable, accessible, interoperable, and re-usable. NFDI4Ing brings together the engineering communities to work towards that goal. As part of the German National Research Data Infrastructure (NFDI), the consortium aims to develop, disseminate, standardize and provide methods and services to make engineering research data FAIR. As one of the first consortia funded as part of the NFDI, NFDI4Ing has actively engaged engineers across all engineering research areas as well as experienced infrastructure providers since 2017. It now has more than 50 active members and participants and continues to grow.

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TA ELLEN - Task Area ELLEN

A key characteristic of computational sciences are their enormous data requirements. Information from many heterogeneous disciplines has to be compiled. The satisfaction of information needs usually take up significant amounts of time and has to be repeated in regular intervals. Often, the required information is not available at all in sufficient spatial, temporal or content resolution, has diverging references regarding the object of investigation or is simply outdated. The more of the required data is not available, the more often scientists are forced to resort to inexact estimates and assumptions, which limit the reliability and legitimacy of their research outcomes.

The aim of this task area is to support engineers in their search for data by facilitating established research methodologies as potential data sources, raising their level of integration and reducing the amount of time required for their application. To this end, in the case of unavailable data sets, scientifically recognized methodological concepts and their software implementations will be made available to generate the missing data. Since neither journal articles nor software codes are suitable to be used as a guide to the implementation of a methodology, conceptual and machine-interpretable workflow descriptions will serve this purpose within the research data landscape.

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FAIR-DS - FAIR Data Spaces

Co-Applicant:

Prof. Dr. Sören Auer

Funding:

Bundesministerium für Bildung und Forschung (BMBF)

Duration:

Since 2021

Innovation in Germany and beyond requires a better transfer of knowledge between science and industry. The first basic initiatives for this are already underway. On the one hand, the National Research Data Infrastructure (NFDI) networks research data and makes them more usable across all scientific disciplines. Second, GAIA-X is creating a secure and federated data infrastructure for Europe.

FAIR Data Spaces aims to build a common cloud-based data space by merging the two initiatives GAIA-X and NFDI while adhering to the FAIR principles. FAIR stands for the guiding principles for the responsible management of research data, which should be Findable, Accessible, Interoperable, and Reusable. The project creates the roadmap for collaboration between the two initiatives, clarifies ethical and legal frameworks for data sharing between academia and industry, develops common technical principles, and demonstrates the use of Gaia-X technologies for making research data available and usable along FAIR principles in various scientific disciplines and industries. Technically, the FAIR Data Spaces project is about generalizing and harnessing the services of individual NFDI consortia for use beyond NFDI. The use of such services in business-related scenarios will be demonstrated in particular by providing them with Gaia-X-compliant interfaces and thus making them interoperable with the Gaia-X Federation Services for Identity & Trust, Federated Catalog, Sovereign Data Exchange and Compliance, which form the core of any data space based on Gaia-X technology.

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