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
Understanding experiments and research practices for reproducibility: an exploratory study
Title: | Understanding experiments and research practices for reproducibility: an exploratory study |
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Authors: | Sheeba Samuel, Birgitta König-Ries |
Place: | PeerJ |
Date: | 2021-04-21 |
Type: | Journal Paper |
Abstract: |
Scientific experiments and research practices vary across disciplines. The research practices followed by scientists in each domain play an essential role in the understandability and reproducibility of results. The “Reproducibility Crisis”, where researchers find difficulty in reproducing published results, is currently faced by several disciplines. To understand the underlying problem in the context of the reproducibility crisis, it is important to first know the different research practices followed in their domain and the factors that hinder reproducibility. We performed an exploratory study by conducting a survey addressed to researchers representing a range of disciplines to understand scientific experiments and research practices for reproducibility. The survey findings identify a reproducibility crisis and a strong need for sharing data, code, methods, steps, and negative and positive results. Insufficient metadata, lack of publicly available data, and incomplete information in study methods are considered to be the main reasons for poor reproducibility. The survey results also address a wide number of research questions on the reproducibility of scientific results. Based on the results of our explorative study and supported by the existing published literature, we offer general recommendations that could help the scientific community to understand, reproduce, and reuse experimental data and results in the research data lifecycle. |
URL: | https://peerj.com/articles/11140 |
BibTex: |
@article{10.7717/peerj.11140, title = {Understanding experiments and research practices for reproducibility: an exploratory study}, author = {Samuel, Sheeba and König-Ries, Birgitta}, year = 2021, month = apr, keywords = {Reproducibility, Reproducible research recommendations, Experiments, Reuse, Understandability, Research data lifecycle, Reproducibility crisis, FAIR data principles}, abstract = { Scientific experiments and research practices vary across disciplines. The research practices followed by scientists in each domain play an essential role in the understandability and reproducibility of results. The “Reproducibility Crisis”, where researchers find difficulty in reproducing published results, is currently faced by several disciplines. To understand the underlying problem in the context of the reproducibility crisis, it is important to first know the different research practices followed in their domain and the factors that hinder reproducibility. We performed an exploratory study by conducting a survey addressed to researchers representing a range of disciplines to understand scientific experiments and research practices for reproducibility. The survey findings identify a reproducibility crisis and a strong need for sharing data, code, methods, steps, and negative and positive results. Insufficient metadata, lack of publicly available data, and incomplete information in study methods are considered to be the main reasons for poor reproducibility. The survey results also address a wide number of research questions on the reproducibility of scientific results. Based on the results of our explorative study and supported by the existing published literature, we offer general recommendations that could help the scientific community to understand, reproduce, and reuse experimental data and results in the research data lifecycle. }, volume = 9, pages = {e11140}, journal = {PeerJ}, issn = {2167-8359}, url = {https://doi.org/10.7717/peerj.11140}, doi = {10.7717/peerj.11140} } |