Digital data on tangible and intangible cultural assets is an essential part of daily life, communication and experience. It has a lasting influence on the perception of cultural identity as well as on the interactions between research, the cultural economy and society. Throughout the last three decades, many cultural heritage institutions have contributed a wealth of digital representations of cultural assets (2D digital reproductions of paintings, sheet music, 3D digital models of sculptures, monuments, rooms, buildings), audio-visual data (music, film, stage performances), and procedural research data such as encoding and annotation formats. The long-term preservation and FAIR availability of research data from the cultural heritage domain is fundamentally important, not only for future academic success in the humanities but also for the cultural identity of individuals and society as a whole. Up to now, no coordinated effort for professional research data management on a national level exists in Germany. NFDI4Culture aims to fill this gap and create a user-centered, research-driven infrastructure that will cover a broad range of research domains from musicology, art history and architecture to performance, theatre, film, and media studies. The research landscape addressed by the consortium is characterized by strong institutional differentiation. Research units in the consortium's community of interest comprise university institutes, art colleges, academies, galleries, libraries, archives and museums. This diverse landscape is also characterized by an abundance of research objects, methodologies and a great potential for data-driven research. In a unique effort carried out by the applicant and co-applicants of this proposal and ten academic societies, this community is interconnected for the first time through a federated approach that is ideally suited to the needs of the participating researchers. To promote collaboration within the NFDI, to share knowledge and technology and to provide extensive support for its users have been the guiding principles of the consortium from the beginning and will be at the heart of all workflows and decision-making processes. Thanks to these principles, NFDI4Culture has gathered strong support ranging from individual researchers to high-level cultural heritage organizations such as the UNESCO, the International Council of Museums, the Open Knowledge Foundation and Wikimedia. On this basis, NFDI4Culture will take innovative measures that promote a cultural change towards a more reflective and sustainable handling of research data and at the same time boost qualification and professionalization in data-driven research in the domain of cultural heritage. This will create a long-lasting impact on science, cultural economy and society as a whole.

Rapid growth of today's video archives along with sparsely available editorial metadata and too few capacities of libraries and archives for manual annotation demand for efficient approaches of automated metadata extraction. In addition, editorial and non-authoritative metadata is usually not fine-grained enough to describe video on a segment level, which is often required for efficient pinpoint search and retrieval. We consider the use case of the AV Portal provided by the German National Library of Science and Technology -- a web based video search engine that offers access to educational video content from various areas of engineering and natural sciences. User studies that have been conducted during the conceptional design stage of the AV Portal have indicated a strong interest of potential users to search for specific visual concepts, like e.g. "landscape", "drawing", "animation", within videos of a particular domain. We present an approach that supports automatic content-based classification of video segments that is tailored to the special requirements of the AV Portal regarding its technology oriented content and academic users. We furthermore show that semantic analysis of the generated metadata not only allows for better retrieval goal definition but also offers explorative search within the archive using visual concepts.

This paper summarizes the results of a comprehensive statistical analysis on a corpus of open access articles and contained figures. It gives an insight into quantitative relationships between illustrations or types of illustrations, caption lengths, subjects, publishers, author affiliations, article citations and others.

This paper aims to provide a structured overview of four open, participatory formats that are particularly applicable in inquiry-based teaching and learning contexts: hackathons, book sprints, barcamps, and learning circles. Using examples, mostly from the work and experience context of the Open Science Lab at TIB Hannover, we address concrete processes, working methods, possible outcomes and challenges. The compilation offers an introduction to the topic and is intended to provide tools for testing in practice.

Delivered at the CRIS2014 Conference in Rome; published in Procedia Computer Science 33 (Jul 2014).Contains conference paper (8 pages) and presentation (12 slides).Research information, i.e., data about research projects, organisations, researchers or research outputs such as publications or patents, is spread across the web, usually residing on institutional and personal web pages or in semi-open databases and information systems. While there exists a wealth of unstructured information, the limited amounts of structured data often are exposed following proprietary or less-established schemas and interfaces. Therefore, a holistic view on research information across organisational and national boundaries is not feasible and information is inconsistent and incomplete. On the other hand, web crawling and information extraction techniques have matured throughout the last decade, allowing for automated approaches of harvesting, extracting and consolidating research information into a more coherent knowledge graph. In particular the Linked Data community has provided a range of techniques, schemas and vocabularies which allow to represent and interlink research information in a more coherent manner. In this work, we give an overview of the current state of the art in research information sharing on the web and present initial ideas towards a more holistic approach for boot-strapping research information from available web sources