A Data-driven Approach for Core Biodiversity Ontology Development.
A deep learning-based approach for segmenting and counting reproductive organs from digitized herbarium specimen images using refined Mask Scoring R-CNN
A Test Collection for Dataset Retrieval in Biodiversity Research
BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data
BiodivOnto: Towards a Core Ontology for Biodiversity
Building high-quality merged ontologies from multiple sources with requirements customization
Capturing and Semantically Describing Provenance to Tell the Story of R Scripts
Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries
Dataset search in biodiversity research: Do metadata in data repositories reflect scholarly information needs?
Deep leaf: Mask R-CNN based leaf detection and segmentation from digitized herbarium specimen images
ISTMINER: Interactive Spatiotemporal Co-occurrence Pattern Extraction: A Biodiversity case study
Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles.
PhenoDeep: A Deep Learning-Based Approach for Detecting Reproductive Organs from Digitized Herbarium Specimen Images
ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks
Results of the Ontology Alignment Evaluation Initiative 2021
Towards an Ontology Network for the reproducibility of scientific studies
Towards Scientific Data Synthesis Using Deep Learning and Semantic Web
Towards Tracking Provenance from Machine Learning Notebooks
Understanding experiments and research practices for reproducibility: an exploratory study
[Dai:Si] – A Modular Dataset Retrieval Framework with a Semantic Search for Biological Data
BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data
Title: | BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data |
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Authors: | Javad Chamanara, Jitendra Gaikwad, Roman Gerlach, Alsayed Algergawy, Andreas Ostrowski and Birgitta König-Ries |
Source: | Biodiversity Data Journal |
Date: | 2021-11-05 |
Type: | Journal Paper |
Abstract: |
Obtaining fit-to-use data associated with diverse aspects of biodiversity, ecology and environment is challenging since often it is fragmented, sub-optimally managed and available in heterogeneous formats. Recently, with the universal acceptance of the FAIR data principles, the requirements and standards of data publications have changed substantially. Researchers are encouraged to manage the data as per the FAIR data principles and ensure that the raw data, metadata, processed data, software, codes and associated material are securely stored and the data be made available with the completion of the research. We have developed BEXIS2 as an open-source community-driven web-based research data management system to support research data management needs of mid to large-scale research projects with multiple sub-projects and up to several hundred researchers. BEXIS2 is a modular and extensible system providing a range of functions to realise the complete data lifecycle from data structure design to data collection, data discovery, dissemination, integration, quality assurance and research planning. It is an extensible and customisable system that allows for the development of new functions and customisation of its various components from database schemas to the user interface layout, elements and look and feel. During the development of BEXIS2, we aimed to incorporate key aspects of what is encoded in FAIR data principles. To investigate the extent to which BEXIS2 conforms to these principles, we conducted the self-assessment using the FAIR indicators, definitions and criteria provided in the FAIR Data Maturity Model. Even though the FAIR data maturity model is developed initially to judge the conformance of datasets, the self-assessment results indicated that BEXIS2 remarkably conforms and supports FAIR indicators. BEXIS2 strongly conforms to the indicators Findability and Accessibility. The indicator Interoperability is moderately supported as of now; however, for many of the less supported facets, we have concrete plans for improvement. Reusability (as defined by the FAIR data principles) is partially achieved. This paper also illustrates community deployment examples of the BEXIS2 instances as success stories to exemplify its capacity to meet the biodiversity and ecological data management needs of differently sized projects and serve as an organisational research data management system. |
URL: | https://doi.org/10.3897/BDJ.9.e72901 |
BibTex: |
@article{10.3897/BDJ.9.e72901, author = {Javad Chamanara and Jitendra Gaikwad and Roman Gerlach and Alsayed Algergawy and Andreas Ostrowski and Birgitta König-Ries}, title = {BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data}, volume = {9}, number = {}, year = {2021}, doi = {10.3897/BDJ.9.e72901}, publisher = {Pensoft Publishers}, abstract = {Obtaining fit-to-use data associated with diverse aspects of biodiversity, ecology and environment is challenging since often it is fragmented, sub-optimally managed and available in heterogeneous formats. Recently, with the universal acceptance of the FAIR data principles, the requirements and standards of data publications have changed substantially. Researchers are encouraged to manage the data as per the FAIR data principles and ensure that the raw data, metadata, processed data, software, codes and associated material are securely stored and the data be made available with the completion of the research. We have developed BEXIS2 as an open-source community-driven web-based research data management system to support research data management needs of mid to large-scale research projects with multiple sub-projects and up to several hundred researchers. BEXIS2 is a modular and extensible system providing a range of functions to realise the complete data lifecycle from data structure design to data collection, data discovery, dissemination, integration, quality assurance and research planning. It is an extensible and customisable system that allows for the development of new functions and customisation of its various components from database schemas to the user interface layout, elements and look and feel. During the development of BEXIS2, we aimed to incorporate key aspects of what is encoded in FAIR data principles. To investigate the extent to which BEXIS2 conforms to these principles, we conducted the self-assessment using the FAIR indicators, definitions and criteria provided in the FAIR Data Maturity Model. Even though the FAIR data maturity model is developed initially to judge the conformance of datasets, the self-assessment results indicated that BEXIS2 remarkably conforms and supports FAIR indicators. BEXIS2 strongly conforms to the indicators Findability and Accessibility. The indicator Interoperability is moderately supported as of now; however, for many of the less supported facets, we have concrete plans for improvement. Reusability (as defined by the FAIR data principles) is partially achieved. This paper also illustrates community deployment examples of the BEXIS2 instances as success stories to exemplify its capacity to meet the biodiversity and ecological data management needs of differently sized projects and serve as an organisational research data management system.}, issn = {1314-2836}, pages = {e72901}, URL = {https://doi.org/10.3897/BDJ.9.e72901}, eprint = {https://doi.org/10.3897/BDJ.9.e72901}, journal = {Biodiversity Data Journal} } |