TDR, the Special Programme for Research and Training in Tropical Diseases hosted at the World Health Organization, GigaScience Press and GBIF are today announcing a new call for authors to submit Data Release papers on vectors of human disease in a thematic series to be published in GigaByte Journal.
Vector-borne diseases account for about one quarter of all infectious diseases. Although there has been significant progress for malaria, with a recent decrease in malaria morbidity and mortality rates, this progress is currently halting. Other diseases, such as those caused by arboviruses like dengue, chikungunya, yellow fever and more recently Zika, are expanding, with an increased number of cases and fatalities.
The necessity to develop new vector control strategies, approaches and tools was recognized through the Global Vector Control Response approved by the World Health Assembly in 2017. Among the mutually agreed objectives between GBIF and TDR is to work on a repository of data related to vectors and support design and identification of sources and contacts for data mobilization campaigns to improve data coverage to help research on human health. Within the framework of this collaboration, GigaByte will support a special issue on data papers on vectors.
The data papers submitted should describe datasets with the following criteria:
- Data has clear relevance for research on vectors of human vector-borne diseases
- Dataset contains more than 5,000 records that are new to GBIF.org in 2021/22 along with high-quality data and metadata
- Data is dedicated to the public domain under an open CC0 designation
The call for manuscripts will be open until 28 February 2022.
The article processing fee—normally US$350—will be waived for 15 papers, provided that the publications are accepted and meet the above criteria.
Instructions for Authors
The manuscript must be prepared in English and submitted in accordance with GigaByte’s instructions to authors.
Authors may contribute to more than one manuscript, and Data Releases can support and be published alongside traditional analysis publications, but the work and data release described needs to stand-alone and justify itself by adding value.
GigaByte will publish a special issue including the selected papers by the first half of 2022. As a newly launched journal we are working to index our papers as widely as possible, and the journal is currently indexed in the Directory of Open Access Journals (DOAJ), CNKI and JGate. The authors contributing to the series will also be acknowledged and invited as contributing authors to an accompanying series announcement article in GigaByte’s well established sister journal GigaScience, which is indexed by MEDLINE, PubMed, the Science Citation Index Expanded, CAS, CNKI, EMBASE and Scopus.
Manuscripts and datasets will go through an open and transparent peer-review process, including data auditing and curation from the GigaScience Press data team. To find out more about data publishing, see the GBIF.org explainer on data papers, the Quick guide to publishing data through GBIF.org and the GigaByte submission instructions. GigaByte Data Release articles have a simple easy-to-write format, and authors can make their submissions using Microsoft word (DOC, DOCX), PDF and TeX/LaTeX files (see Overleaf template. We recommend that authors start by preparing the dataset and publishing it through GBIF.org before turning to manuscript writing and editing.
GigaByte's novel, end-to-end XML publishing platform, means publication can be done in a quicker and more cost-effective manner better designed for these more granular research objects that don’t require such a labour intensive and detailed vehicle for sharing. It also allows additional interactivity and we can work with the authors to embed maps, video and imaging data plugins and other relevant tools for visualizing data and results in the final publications. Please discuss with the editors if you have any dynamic content you would like to highlight.
Definition of terms
- Datasets with relevance for research on vectors of human vector-borne diseases
This sponsored call for data papers has a thematic focus on vectors of human vector-borne diseases. Authors can prepare data papers that describe checklist, occurrence or sampling-event datasets; this blog post will help authors determine which class of dataset is most suitable. Data on pathogens (viruses, bacteria and parasites) can be published as attributes of vector data in the
associatedOccurrencesfield in occurrence and sampling event datasets, No human data can be included in the datasets. See examples of existing checklist, occurrence, and sampling-event datasets.
- Datasets with more than 5,000 records that are new to GBIF.org
The 5,000 occurrence records minimum threshold is merely a guiding number, not the target to publish a dataset which is cut to be just over the limit to pass. Data must be new to GBIF.org in 2021/22, providing high-quality data and metadata. Checklist and sampling-event datasets below the threshold will be considered eligible on the basis of exceptional value and handled case-by-case by the editor. Minimum publishable units, salami publishing and dataset version papers are discouraged: datasets should be published in their original, untrimmed state. Many datasets are, by nature, dynamic, and while a data paper promotes and describes the dataset at its current state at submission, the dataset link can and often will resolve to the evolving online resource. Therefore, a data paper should ideally be written in a way that it serves as a bibliographic citation, a showcase and a lasting “home” for the dataset. Any datasets with additional supporting data not suitable for GBIF will be curated and hosted in the GigaScience Press GigaDB repository or other domain-specific repositories.
- Datasets with high-quality data and metadata
Authors should start by publishing a dataset comprising data and metadata that meets GBIF's data-quality requirements. This effort will involve work on an installation of the GBIF Integrated Publishing Toolkit (IPT). If the Darwin Core archive is constructed elsewhere, the use of the GBIF Data Validator is recommended before the publication.