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Ten Simple Rules for FAIR Sharing of Experimental and Clinical Data with the Modeling Community

Abstract (Expand)

Science continues to become more interdisciplinary and to involve increasingly complex data sets. Many projects in the biomedical and health-related sciences follow or aim to follow the principles of …rinciples of FAIR data sharing, which has been demonstrated to foster collaboration, to lead to better research outcomes, and to help ensure reproducibility of results. Data generated in the course of biomedical and health research present specific challenges for FAIR sharing in the sense that they are heterogeneous and highly sensitive to context and the needs of protection and privacy. Data sharing must respect these features without impeding timely dissemination of results, so that they can contribute to time-critical advances in medical therapy and treatment. Modeling and simulation of biomedical processes have become established tools, and a global community has been developing algorithms, methodologies, and standards for applying biomedical simulation models in clinical research. However, it can be difficult for clinician scientists to follow the specific rules and recommendations for FAIR data sharing within this domain. We seek to clarify the standard workflow for sharing experimental and clinical data with the simulation modeling community. By following these recommendations, data sharing will be improved, collaborations will become more effective, and the FAIR publication and subsequent reuse of data will become possible at the level of quality necessary to support biomedical and health-related sciences.

Authors: Matthias König, Jan Grzegorzewski, Martin Golebiewski, Henning Hermjakob, Mike Hucka, Brett Olivier, Sarah Keating, David Nickerson, Falk Schreiber, Rahuman Sheriff, Dagmar Waltemath

Date Published: 19th Nov 2021

Publication Type: Journal

Improving the FAIRness of Health Studies in Germany: The German Central Health Study Hub COVID-19.

Abstract (Expand)

The German Central Health Study Hub COVID-19 is an online service that offers bundled access to COVID-19 related studies conducted in Germany. It combines metadata and other information of epidemiologic, … public health and clinical studies into a single data repository for FAIR data access. In addition to study characteristics the system also allows easy access to study documents, as well as instruments for data collection. Study metadata and survey instruments are decomposed into individual data items and semantically enriched to ease the findability. Data from existing clinical trial registries (DRKS, clinicaltrails.gov and WHO ICTRP) are merged with epidemiological and public health studies manually collected and entered. More than 850 studies are listed as of September 2021.

Authors: J. Darms, J. Henke, X. Hu, C. O. Schmidt, M. Golebiewski, J. Fluck

Date Published: 18th Nov 2021

Publication Type: Journal

Combining dictionary- and rule-based approximate entity linking with tuned BioBERT

Abstract (Expand)

Chemical named entity recognition (NER) is a significant step for many downstream applications like entity linking for the chemical text-mining pipeline. However, the identification of chemical entities … in a biomedical text is a challenging task due to the diverse morphology of chemical entities and the different types of chemical nomenclature. In this work, we describe our approach that was submitted for BioCreative version 7 challenge Track 2, focusing on the ‘Chemical Identification’ task for identifying chemical entities and entity linking, using MeSH. For this purpose, we have applied a two-stage approach as follows (a) usage of fine-tuned BioBERT for identification of chemical entities (b) semantic approximate search in MeSH and PubChem databases for entity linking. There was some friction between the two approaches, as our rule-based approach did not harmonise optimally with partially recognized words forwarded by the BERT component. For our future work, we aim to resolve the issue of the artefacts arising from BERT tokenizers and develop joint learning of chemical named entity recognition and entity linking using pre-trained transformer-based models and compare their performance with our preliminary approach. Next, we will improve the efficiency of our approximate search in reference databases during entity linking. This task is non-trivial as it entails determining similarity scores of large sets of trees with respect to a query tree. Ideally, this will enable flexible parametrization and rule selection for the entity linking search.

Authors: Ghadeer Mobasher, Lukrécia Mertová, Sucheta Ghosh, Olga Krebs, Bettina Heinlein, Wolfgang Müller

Date Published: 11th Nov 2021

Publication Type: Proceedings

A Novel Wikipedia based Dataset for Monolingual and Cross-lingual Summarization

Abstract

Not specified

Authors: Mehwish Fatima, Michael Strube

Date Published: 10th Nov 2021

Publication Type: InProceedings

Countering the Influence of Essay Length in Neural Essay Scoring.

Abstract

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Authors: Sungho Jeon, Michael Strube

Date Published: 10th Nov 2021

Publication Type: InProceedings

The CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis in Dialogue

Abstract (Expand)

In this paper, we provide an overview of the CODI-CRAC 2021 Shared-Task: Anaphora Resolution in Dialogue. The shared task focuses on detecting anaphoric relations in different genres of conversations. … Using five conversational datasets, four of which have been newly annotated with a wide range of anaphoric relations: identity, bridging references and discourse deixis, we defined multiple subtasks focusing individually on these key relations. We discuss the evaluation scripts used to assess the system performance on these subtasks, and provide a brief summary of the participating systems and the results obtained across ?? runs from 5 teams, with most submissions achieving significantly better results than our baseline methods.

Authors: Sopan Khosla, Juntao Yu, Ramesh Manuvinakurike, Vincent Ng, Massimo Poesio, Michael Strube, Carolyn Rosé

Date Published: 10th Nov 2021

Publication Type: InProceedings

Proceedings of the 2nd Workshop on Computational Approaches to Discourse, Punta Cana, Dominican Repbulich and Online

Abstract

Not specified

Authors: Chloé Braud, Christian Hardmeier, Junyi Jessy Li, Annie Louis, Michael Strube, Amir Zeldes

Date Published: 10th Nov 2021

Publication Type: Proceedings

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