Knowledge Graph Building Blocks: An easy-to-use Framework for developing FAIREr Knowledge Graphs

Knowledge graphs and ontologies provide promising technical solutions for implementing the FAIR Principles for Findable, Accessible, Interoperable, and Reusable data and metadata. However, they also come with their own challenges. Nine such challenges are discussed and associated with the criterion of cognitive interoperability and specific FAIREr principles (FAIR + Explorability raised) that they fail to meet. We introduce an easy-to-use, open source knowledge graph framework that is based on knowledge graph building blocks (KGBBs). KGBBs are small information modules for knowledge-processing, each based on a specific type of semantic unit. By interrelating several KGBBs, one can specify a KGBB-driven FAIREr knowledge graph. Besides implementing semantic units, the KGBB Framework clearly distinguishes and decouples an internal in-memory data model from data storage, data display, and data access/export models. We argue that this decoupling is essential for solving many problems of knowledge management systems. We discuss the architecture of the KGBB Framework as we envision it, comprising (i) an openly accessible KGBB-Repository for different types of KGBBs, (ii) a KGBB-Engine for managing and operating FAIREr knowledge graphs (including automatic provenance tracking, editing changelog, and versioning of semantic units); (iii) a repository for KGBB-Functions; (iv) a low-code KGBB-Editor with which domain experts can create new KGBBs and specify their own FAIREr knowledge graph without having to think about semantic modelling. We conclude with discussing the nine challenges and how the KGBB Framework provides solutions for the issues they raise. While most of what we discuss here is entirely conceptual, we can point to two prototypes that demonstrate the principle feasibility of using semantic units and KGBBs to manage and structure knowledge graphs

A Scholarly Knowledge Graph-Powered Dashboard: Implementation and User Evaluation

Scholarly knowledge graphs provide researchers with a novel modality of information retrieval, and their wider use in academia is beneficial for the digitalization of published works and the development of scholarly communication. To increase the acceptance of scholarly knowledge graphs, we present a dashboard, which visualizes the research contributions on an educational science topic in the frame of the Open Research Knowledge Graph (ORKG). As dashboards are created at the intersection of computer science, graphic design, and human-technology interaction, we used these three perspectives to develop a multi-relational visualization tool aimed at improving the user experience. According to preliminary results of the user evaluation survey, the dashboard was perceived as more appealing than the baseline ORKG-powered interface. Our findings can be used for the development of scholarly knowledge graph-powered dashboards in different domains, thus facilitating acceptance of these novel instruments by research communities and increasing versatility in scholarly communication

A novel framework to investigate wind-driven snow redistribution over an Alpine glacier: combination of high-resolution terrestrial laser scans and large-eddy simulations

Wind-driven snow redistribution affects the glacier mass balance by eroding or depositing mass from or to different parts of the glacier’s surface. High-resolution observations are used to test the ability of large-eddy simulations as a tool for distributed mass balance modeling. We present a case study of observed and simulated snow redistribution over Hintereisferner glacier (Ötztal Alps, Austria) between 6 and 9 February 2021. Observations consist of three high-resolution digital elevation models (Δx=1 m) derived from terrestrial laser scans taken shortly before, directly after, and 15 h after snowfall. The scans are complemented by datasets from three on-site weather stations. After the snowfall event, we observed a snowpack decrease of 0.08 m on average over the glacier. The decrease in the snow depth can be attributed to post-snowfall compaction and the wind-driven redistribution of snow. Simulations were performed with the Weather Research and Forecasting (WRF) model at Δx=48 m with a newly implemented snow drift module. The spatial patterns of the simulated snow redistribution agree well with the observed generalized patterns. Snow redistribution contributed −0.026 m to the surface elevation decrease over the glacier surface on 8 February, resulting in a mass loss of −3.9 kg m−2, which is on the same order of magnitude as the observations. With the single case study we cannot yet extrapolate the impact of post-snowfall events on the seasonal glacier mass balance, but the study shows that the snow drift module in WRF is a powerful tool to improve knowledge on wind-driven snow redistribution patterns over glaciers.Austrian Science FundDeutsche ForschungsgemeinschaftPeer Reviewe

Improving Access to Scientific Literature with Knowledge Graphs

The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually document-based - formerly printed on paper as a classic essay and nowadays as PDF. With around 2.5 million new research contributions every year, researchers drown in a flood of pseudo-digitized PDF publications. As a result research is seriously weakened. In this article, we argue for representing scholarly contributions in a structured and semantic way as a knowledge graph. The advantage is that information represented in a knowledge graph is readable by machines and humans. As an example, we give an overview on the Open Research Knowledge Graph (ORKG), a service implementing this approach. For creating the knowledge graph representation, we rely on a mixture of manual (crowd/expert sourcing) and (semi-)automated techniques. Only with such a combination of human and machine intelligence, we can achieve the required quality of the representation to allow for novel exploration and assistance services for researchers. As a result, a scholarly knowledge graph such as the ORKG can be used to give a condensed overview on the state-of-the-art addressing a particular research quest, for example as a tabular comparison of contributions according to various characteristics of the approaches. Further possible intuitive access interfaces to such scholarly knowledge graphs include domain-specific (chart) visualizations or answering of natural language questions.Der Verbreitung wissenschaftlicher Erkenntnisse hat sich seit vielen hundert Jahren nicht grundlegend verändert: Er erfolgt in der Regel dokumentenbasiert - früher als klassischer Aufsatz auf Papier gedruckt und heute online als PDF. Mit rund 2,5 Millionen neuen Forschungsbeiträgen pro Jahr ertrinken Forscher in einer Flut von pseudo-digitalisierten PDF-Publikationen. Als Folge davon wird die Forschung stark geschwächt. In diesem Artikel plädieren wir dafür, wissenschaftliche Beiträge in strukturierter und semantischer Form als Wissensgraph zu repräsentieren. Der Vorteil ist, dass die in einem Wissensgraph dargestellten Informationen für Maschinen und Menschen lesbar sind. Als Beispiel geben wir einen Überblick über den Open Research Knowledge Graph (ORKG), einen Dienst, der diesen Ansatz umsetzt. Für die Erstellung des Wissensgraph setzen wir eine Mischung aus manuellen (crowd/expert sourcing) und (halb-)automatisierten Techniken ein. Nur mit einer solchen Kombination aus menschlicher und maschineller Intelligenz können wir die erforderliche Qualität der Darstellung erreichen, um neuartige Explorations- und Unterstützungsdienste für Forscher zu ermöglichen. Im Ergebnis kann ein Wissensgraph wie der ORKG verwendet werden, um einen komprimierten Überblick über den Stand der Technik in Bezug auf eine bestimmte Forschungsaufgabe zu geben, z.B. als tabellarischer Vergleich der Beiträge nach verschiedenen Merkmalen der Ansätze. Weitere mögliche intuitive Nutzungsschnittstellen zu solchen wissenschaftlichen Wissensgraphen sind domänenspezifische Visualisierungen oder die Beantwortung natürlichsprachlicher Fragen mittels Question Answering.Peer Reviewe

The European language technology landscape in 2020: Language-centric and human-centric AI for cross-cultural communication in multilingual Europe

Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality. However, language barriers impacting business, cross-lingual and cross-cultural communication are still omnipresent. Language Technologies (LTs) are a powerful means to break down these barriers. While the last decade has seen various initiatives that created a multitude of approaches and technologies tailored to Europe’s specific needs, there is still an immense level of fragmentation. At the same time, AI has become an increasingly important concept in the European Information and Communication Technology area. For a few years now, AI – including many opportunities, synergies but also misconceptions – has been overshadowing every other topic. We present an overview of the European LT landscape, describing funding programmes, activities, actions and challenges in the different countries with regard to LT, including the current state of play in industry and the LT market. We present a brief overview of the main LT-related activities on the EU level in the last ten years and develop strategic guidance with regard to four key dimensions.publishedVersio

TREM2-Transduced Myeloid Precursors Mediate Nervous Tissue Debris Clearance and Facilitate Recovery in an Animal Model of Multiple Sclerosis

BACKGROUND: In multiple sclerosis, inflammation can successfully be prevented, while promoting repair is still a major challenge. Microglial cells, the resident phagocytes of the central nervous system (CNS), are hematopoietic-derived myeloid cells and express the triggering receptor expressed on myeloid cells 2 (TREM2), an innate immune receptor. Myeloid cells are an accessible source for ex vivo gene therapy. We investigated whether myeloid precursor cells genetically modified to express TREM2 affect the disease course of experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis. METHODS AND FINDINGS: EAE was induced in mice by immunization with a myelin autoantigen. Intravenous application of TREM2-transduced bone marrow–derived myeloid precursor cells at the EAE peak led to an amelioration of clinical symptoms, reduction in axonal damage, and prevention of further demyelination. TREM2-transduced myeloid cells applied intravenously migrated into the inflammatory spinal cord lesions of EAE-diseased mice, showed increased lysosomal and phagocytic activity, cleared degenerated myelin, and created an anti-inflammatory cytokine milieu within the CNS. CONCLUSIONS: Intravenously applied bone marrow–derived and TREM2-tranduced myeloid precursor cells limit tissue destruction and facilitate repair within the murine CNS by clearance of cellular debris during EAE. TREM2 is a new attractive target for promotion of repair and resolution of inflammation in multiple sclerosis and other neuroinflammatory diseases

European Language Grid: An Overview

With 24 official EU and many additional languages, multilingualism in Europe and an inclusive Digital Single Market can only be enabled through Language Technologies (LTs). European LT business is dominated by hundreds of SMEs and a few large players. Many are world-class, with technologies that outperform the global players. However, European LT business is also fragmented – by nation states, languages, verticals and sectors, significantly holding back its impact. The European Language Grid (ELG) project addresses this fragmentation by establishing the ELG as the primary platform for LT in Europe. The ELG is a scalable cloud platform, providing, in an easy-to-integrate way, access to hundreds of commercial and non-commercial LTs for all European languages, including running tools and services as well as data sets and resources. Once fully operational, it will enable the commercial and non-commercial European LT community to deposit and upload their technologies and data sets into the ELG, to deploy them through the grid, and to connect with other resources. The ELG will boost the Multilingual Digital Single Market towards a thriving European LT community, creating new jobs and opportunities. Furthermore, the ELG project organises two open calls for up to 20 pilot projects. It also sets up 32 national competence centres and the European LT Council for outreach and coordination purposes

de.NBI Cloud federation through ELIXIR AAI

Belmann P, Fischer B, Krüger J, et al. de.NBI Cloud federation through ELIXIR AAI. F1000Research. 2019;8: 842.The academic de.NBI Cloud offers compute resources for life science research in Germany.  At the beginning of 2017, de.NBI Cloud started to implement a federated cloud consisting of five compute centers, with the aim of acting as one resource to their users. A federated cloud introduces multiple challenges, such as a central access and project management point, a unified account across all cloud sites and an interchangeable project setup across the federation. In order to implement the federation concept, de.NBI Cloud integrated with the ELIXIR authentication and authorization infrastructure system (ELIXIR AAI) and in particular Perun, the identity and access management system of ELIXIR. The integration solves the mentioned challenges and represents a backbone, connecting five compute centers which are based on OpenStack and a web portal for accessing the federation.This article explains the steps taken and software components implemented for setting up a federated cloud based on the collaboration between de.NBI Cloud and ELIXIR AAI. Furthermore, the setup and components that are described are generic and can therefore be used for other upcoming or existing federated OpenStack clouds in Europe

European Language Grid: A Joint Platform for the European Language Technology Community

Europe is a multilingual society, in which dozens of languages are spoken. The only option to enable and to benefit from multilingualism is through Language Technologies (LT), i.e., Natural Language Processing and Speech Technologies. We describe the European Language Grid (ELG), which is targeted to evolve into the primary platform and marketplace for LT in Europe by providing one umbrella platform for the European LT landscape, including research and industry, enabling all stakeholders to upload, share and distribute their services, products and resources. At the end of our EU project, which will establish a legal entity in 2022, the ELG will provide access to approx. 1300 services for all European languages as well as thousands of data sets