Towards an open, zoomable atlas for invasion science and beyond

Hypotheses in urban ecology: building a common knowledge base

Urban ecology is a rapidly growing research field that has to keep pace with the pressing need to tackle the sustainability crisis. As an inherently multi-disciplinary field with close ties to practitioners and administrators, research synthesis and knowledge transfer between those different stakeholders is crucial. Knowledge maps can enhance knowledge transfer and provide orientation to researchers as well as practitioners. A promising option for developing such knowledge maps is to create hypothesis networks, which structure existing hypotheses and aggregate them according to topics and research aims. Combining expert knowledge with information from the literature, we here identify 62 research hypotheses used in urban ecology and link them in such a network. Our network clusters hypotheses into four distinct themes: (i) Urban species traits & evolution, (ii) Urban biotic communities, (iii) Urban habitats and (iv) Urban ecosystems. We discuss the potentials and limitations of this approach. All information is openly provided as part of an extendable Wikidata project, and we invite researchers, practitioners and others interested in urban ecology to contribute additional hypotheses, as well as comment and add to the existing ones. The hypothesis network and Wikidata project form a first step towards a knowledge base for urban ecology, which can be expanded and curated to benefit both practitioners and researchers.

Recent advances in availability and synthesis of the economic costs of biological invasions

Biological invasions are a global challenge that has received insufficient attention. Recently available cost syntheses have provided policy- and decision makers with reliable and up-to-date information on the economic impacts of biological invasions, aiming to motivate effective management. The resultant InvaCost database is now publicly and freely accessible and enables rapid extraction of monetary cost information. This has facilitated knowledge sharing, developed a more integrated and multidisciplinary network of researchers, and forged multidisciplinary collaborations among diverse organizations and stakeholders. Over 50 scientific publications so far have used the database and have provided detailed assessments of invasion costs across geographic, taxonomic, and spatiotemporal scales. These studies have provided important information that can guide future policy and legislative decisions on the management of biological invasions while simultaneously attracting public and media attention. We provide an overview of the improved availability, reliability, standardization, and defragmentation of monetary costs; discuss how this has enhanced invasion science as a discipline; and outline directions for future development.

Using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs: the case of COVID-19 epidemiology in Wikidata

Urgent global research demands real-time dissemination of precise data. Wikidata, a collaborative and openly licensed knowledge graph available in RDF format, provides an ideal forum for exchanging structured data that can be verified and consolidated using validation schemas and bot edits. In this research article, we catalog an automatable task set necessary to assess and validate the portion of Wikidata relating to the COVID-19 epidemiology. These tasks assess statistical data and are implemented in SPARQL, a query language for semantic databases. We demonstrate the efficiency of our methods for evaluating structured non-relational information on COVID-19 in Wikidata, and its applicability in collaborative ontologies and knowledge graphs more broadly. We show the advantages and limitations of our proposed approach by comparing it to the features of other methods for the validation of linked web data as revealed by previous research.

SKG4EOSC - Scholarly Knowledge Graphs for EOSC: Establishing a backbone of knowledge graphs for FAIR Scholarly Information in EOSC

In the age of advanced information systems powering fast-paced knowledge economies that face global societal challenges, it is no longer adequate to express scholarly information - an essential resource for modern economies - primarily as article narratives in document form. Despite being a well-established tradition in scholarly communication, PDF-based text publishing is hindering scientific progress as it buries scholarly information into non-machine-readable formats. The key objective of SKG4EOSC is to improve science productivity through development and implementation of services for text and data conversion, and production, curation, and re-use of FAIR scholarly information. This will be achieved by (1) establishing the Open Research Knowledge Graph (ORKG, orkg.org), a service operated by the SKG4EOSC coordinator, as a Hub for access to FAIR scholarly information in the EOSC; (2) lifting to EOSC of numerous and heterogeneous domain-specific research infrastructures through the ORKG Hub’s harmonized access facilities; and (3) leverage the Hub to support cross-disciplinary research and policy decisions addressing societal challenges. SKG4EOSC will pilot the devised approaches and technologies in four research domains: biodiversity crisis, precision oncology, circular processes, and human cooperation. With the aim to improve machine-based scholarly information use, SKG4EOSC addresses an important current and future need of researchers. It extends the application of the FAIR data principles to scholarly communication practices, hence a more comprehensive coverage of the entire research lifecycle. Through explicit, machine actionable provenance links between FAIR scholarly information, primary data and contextual entities, it will substantially contribute to reproducibility, validation and trust in science. The resulting advanced machine support will catalyse new discoveries in basic research and solutions in key application areas.

Some reflections on current invasion science and perspectives for an exciting future

Species spreading beyond their native ranges are important study objects in ecology and environmental sciences and research on biological invasions is thriving. Along with an increase in the number of publications, the research field is experiencing an increase in the diversity of methods applied and questions asked. This development has facilitated an upsurge in information on invasions, but it also creates conceptual and practical challenges. To provide more transparency on which kind of research is actually done in the field, the distinction between invasion science, encompassing the full spectrum of studies on biological invasions and the sub-field of invasion biology, studying patterns and mechanisms of species invasions with a focus on biological research questions, can be useful. Although covering a smaller range of topics, invasion biology today still is the driving force in invasion science and we discuss challenges stemming from its embeddedness in the social context. Invasion biology consists of the building blocks ‘theory’, ‘case studies’ and ‘application’, where theory takes the form of conceptual frameworks, major hypotheses and statistical generalisations. Referencing recent work in philosophy of science, we argue that invasion biology, like other biological or ecological disciplines, does not rely on the development of an all-encompassing theory in order to be efficient. We suggest, however, that theory development is nonetheless necessary and propose improvements. Recent advances in data visualisation, machine learning and semantic modelling are providing opportunities for enhancing knowledge management and presentation and we suggest that invasion science should use these to transform its ways of publishing, archiving and visualising research. Along with a stronger focus on studies going beyond purely biological questions, this would facilitate the efficient prevention and management of biological invasions.