Enhancing Location-Related Hydrogeological Knowledge

OPTIMETA – Strengthening the Open Access publishing system through open citations and spatiotemporal metadata

The BMBF project OPTIMETA aims to strengthen the Open Access publishing system by connecting open citations and spatiotemporal metadata from open access journals with openly accessible data sources. For this purpose, we will extend Open Journal Systems (OJS) to give it functionalities for collecting and distributing open data by developing two OJS plugins for capturing citation networks and articles' spatial and temporal properties as machine-readable and accessible metadata. We will ensure the target group-orientated design of the plugins by performing a comprehensive needs analysis for key stakeholders: the editors or operators of OA journals and the researchers, as authors and readers of articles. The developments will be designed and tested in cooperation with several independent journals and OA publishers. Overall, OPTIMETA supports the attraction of independent OA journals as publication venues by substantially improving the discoverability and visibility of OA publications through enrichment and interlinking of article metadata.

Extracting and modeling geographic information from scientific articles

Scientific articles often contain relevant geographic information such as where field work was performed or where patients were treated. Most often, this information appears in the full-text article contents as a description in natural language including place names, with no accompanying machine-readable geographic metadata. Automatically extracting this geographic information could help conduct meta-analyses, find geographical research gaps, and retrieve articles using spatial search criteria. Research on this problem is still in its infancy, with many works manually processing corpora for locations and few cross-domain studies. In this paper, we develop a fully automatic pipeline to extract and represent relevant locations from scientific articles, applying it to two varied corpora. We obtain good performance, with full pipeline precision of 0.84 for an environmental corpus, and 0.78 for a biomedical corpus. Our results can be visualized as simple global maps, allowing human annotators to both explore corpus patterns in space and triage results for downstream analysis. Future work should not only focus on improving individual pipeline components, but also be informed by user needs derived from the potential spatial analysis and exploration of such corpora.

Place versus Space: From Points, Lines and Polygons in GIS to Place-Based Representations Reflecting Language and Culture

Around the globe, Geographic Information Systems (GISs) are well established in the daily workflow of authorities, businesses and non-profit organisations. GIS can effectively handle spatial entities and offer sophisticated analysis and modelling functions to deal with space. Only a small fraction of the literature in Geographic Information Science—or GIScience in short—has advanced the development of place, addressing entities with an ambiguous boundary and relying more on the human or social attributes of a location rather than on crisp geographic boundaries. While the GIScience developments support the establishment of the digital humanities, GISs were never designed to handle subjective or vague data. We, an international group of authors, juxtapose place and space in English language and in several other languages and discuss potential consequences for Geoinformatics and GIScience. In particular, we address the question of whether linguistic and cultural settings play a role in the perception of place. We report on some facts revealed by this multi-language and multi-cultural dialogue, and what particular aspects of place we were able to discern regarding the few languages addressed.

An online method database for mapping and assessing ecosystem services

Since the foundation of the ecosystem services concept in the ninetieth of the last century (Costanza et al. 1998, Costanza et al. 1997, de Groot 1992), many methods to map and assess ecosystem services have been developed and applied to policy and business questions worldwide. While many flexible methods exist at different spatial scales and ecosystem types, Jax et al. (2018) express the difficulty in choosing and applying the correct method to the right topic of interest. To enable a selection of appropriate methods, Harrison et al. (2018) developed a decision tree approach. However, Dunford et al. (2018) argue that often not a single method but a combination of methods are required for appropriate decision-making in real world situations. Thus, applying the concept of ecosystem services in practice is challenging, especially at institutional level (Saarikoski et al. 2018). This hampers comparability, applicability and transferability of ecosystem services assessments and related mapping applications across scales and European regions. It also impedes a solid overview of existing methods suitable for use at different scales in different biomes and types of ecosystems. These challenges require a consistent knowledge capitalisation infrastructure, where information is synthesised in a publicly accessible portal to enable a consistent description of different ecosystem conditions and the services they provide.

Going beyond the previously mentioned challenges requires a flexible methodology for assessing and mapping ecosystem services. The Horizon 2020 project ESMERALDA (Enhancing ecoSysteM sERvices mApping for poLicy and Decision mAking) developed this methodology and implemented it into the "MAES explorer"*5 and the "MAES Methods Explorer*1 (MME)". The MME complements previous developments from the EU projects OpenNESS*2 and OPERAs*3. In contrast to the OPPLA*4 case-study-finder with case study areas and accompanied study area booklets and descriptions, MME focuses on methods for mapping and assessing ecosystem services and links those to selected literature and case studies. Additionally, MME provides a comprehensive and publicly searchable collection of peer-reviewed journal references and grey literature about mapping and assessing ecosystem services in Europe. This compilation is cross-related with the case study booklets produced by the ESMERALDA project and particularly methods, which are specifically used to assess and map particular ecosystem services within the case study area. Thus, searching for and filtering of particular case study areas, (related) literature references and/or methods is possible. Santos-Martin et al. (2018) provide the detailed description about the scientific procedure behind the MME tool described here.