preVIEW: from a fast prototype towards a sustainable semantic search system for central access to COVID-19 preprints

The current COVID-19 pandemic emphasizes the use of so-called preprints - a type of publication that is not subject to peer review. Due to its global relevance, there is an immense number of COVID-19-related preprints every day. To help researchers find relevant information, we have developed the semantic search engine preVIEW, it integrates preprints from currently seven different preprint servers. For semantic indexing, we implemented various text mining components to tag, for example, diseases or SARS-CoV-2 specific proteins. While the service initially served as a prototype developed together with users, we present a re-engineering towards a sustainable semantic search system, which was inevitable due to the continuously growing number of preprint publications. This enables easy reuse of the components and allows rapid adaptation of the service to further user needs

CTO: A Community-Based Clinical Trial Ontology and Its Applications in PubChemRDF and SCAIViewH

Driven by the use cases of PubChemRDF and SCAIView, we have developed a first community-based clinical trial ontology (CTO) by following the OBO Foundry principles. CTO uses the Basic Formal Ontology (BFO) as the top level ontology and reuses many terms from existing ontologies. CTO has also defined many clinical trial-specific terms. The general CTO design pattern is based on the PICO framework together with two applications. First, the PubChemRDF use case demonstrates how a drug Gleevec is linked to multiple clinical trials investigating Gleevec’s related chemical compounds. Second, the SCAIView text mining engine shows how the use of CTO terms in its search algorithm can identify publications referring to COVID-19-related clinical trials. Future opportunities and challenges are discussed

Semantic Metadata Annotation Services in the Biomedical Domain—A Literature Review

For all research data collected, data descriptions and information about the corresponding variables are essential for data analysis and reuse. To enable cross-study comparisons and analyses, semantic interoperability of metadata is one of the most important requirements. In the area of clinical and epidemiological studies, data collection instruments such as case report forms (CRFs), data dictionaries and questionnaires are critical for metadata collection. Even though data collection instruments are often created in a digital form, they are mostly not machine readable; i.e., they are not semantically coded. As a result, the comparison between data collection instruments is complex. The German project NFDI4Health is dedicated to the development of national research data infrastructure for personal health data, and as such searches for ways to enhance semantic interoperability. Retrospective integration of semantic codes into study metadata is important, as ongoing or completed studies contain valuable information. However, this is labor intensive and should be eased by software. To understand the market and find out what techniques and technologies support retrospective semantic annotation/enrichment of metadata, we conducted a literature review. In NFDI4Health, we identified basic requirements for semantic metadata annotation software in the biomedical field and in the context of the FAIR principles. Ten relevant software systems were summarized and aligned with those requirements. We concluded that despite active research on semantic annotation systems, no system meets all requirements. Consequently, further research and software development in this area is needed, as interoperability of data dictionaries, questionnaires and data collection tools is key to reusing and combining results from independent research studies

Continuous development of the semantic search preVIEW: from COVID-19 long COVID

Langnickel L, Darms J, Heldt K, Ducks D, Fluck J. Continuous development of the semantic search preVIEW: from COVID-19 long COVID. Database: The Journal of Biological Databases and Curation. 2022;2022: baac048.preVIEW is a freely available semantic search engine for Coronavirus disease (COVID-19)-related preprint publications. Currently, it contains >43 800 documents indexed with >4000 semantic concepts, annotated automatically. During the last 2 years, the dynamic situation of the corona crisis has demanded dynamic development. Whereas new semantic concepts have been added over time-such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of interest-the service has been also extended with several features improving the usability and user friendliness. Most importantly, the user is now able to give feedback on detected semantic concepts, i.e. a user can mark annotations as true positives or false positives. In addition, we expanded our methods to construct search queries. The presented version of preVIEW also includes links to the peer-reviewed journal articles, if available. With the described system, we participated in the BioCreative VII interactive textmining track and retrieved promising user-in-the-loop feedback. Additionally, as the occurrence of long-term symptoms after an infection with the virus SARS-CoV-2-called long COVID-is getting more and more attention, we have recently developed and incorporated a long COVID classifier based on state-of-the-art methods and manually curated data by experts. The service is freely accessible under https://preview.zbmed.d

A Semantic Representation of the NFDI4Health Metadata Schema Utilizing the CEDAR Workbench - Poster

Rich metadata is required for a comprehensive description of research assets. We developed a metadata schema for clinical and epidemiological research studies based on existing generic and domain-specific metadata vocabularies. It forms the basis for various search and data management services. Interoperability remains a challenge, as various health research standards are to be supported in the medium term. At the same time, embedding our infrastructure in national and international initiatives requires the use of overarching syntactic and semantic standards and vocabularies. In this paper we present a prototypical implementation in CEDAR Workbench. This not only provides a graphical web interface for collaboration and a possibility for form-based data entry for testing purposes. CEDAR also enables the use of standard vocabularies, annotation of concepts with medical terminologies, and a serialization in an RDF-JSON format

COVID-19 preVIEW: Semantic Search to Explore COVID-19 Research Preprints

Langnickel L, Baum R, Darms J, Madan S, Fluck J. COVID-19 preVIEW: Semantic Search to Explore COVID-19 Research Preprints. In: Mantas J, Stoicu-Tivadar L, Chronaki C, et al., eds. Public Health and Informatics. Proceedings of MIE 2021. Studies in Health Technology and Informatics. Vol 281. Amsterdam: IOS Press; 2021: 78-82.During the current COVID-19 pandemic, the rapid availability of profound information is crucial in order to derive information about diagnosis, disease trajectory, treatment or to adapt the rules of conduct in public. The increased importance of preprints for COVID-19 research initiated the design of the preprint search engine preVIEW. Conceptually, it is a lightweight semantic search engine focusing on easy inclusion of specialized COVID-19 textual collections and provides a user friendly web interface for semantic information retrieval. In order to support semantic search functionality, we integrated a text mining workflow for indexing with relevant terminologies. Currently, diseases, human genes and SARS-CoV-2 proteins are annotated, and more will be added in future. The system integrates collections from several different preprint servers that are used in the biomedical domain to publish non-peer-reviewed work, thereby enabling one central access point for the users. In addition, our service offers facet searching, export functionality and an API access. COVID-19 preVIEW is publicly available at https://preview.zbmed.de