A generic schema and data collection forms applicable to diverse entomological studies of mosquitoes
Kiware, Samson S., Russell, Tanya, Mtema, Zacharia J., Malishee, Alpha D., Chaki, Prosper, Lwetoijera, Dickson, Chanda, Javan, Chinula, Dingani, Majambere, Silas, Gimnig, John E., Smith, Thomas A., and Killeen, Gerry F. (2016) A generic schema and data collection forms applicable to diverse entomological studies of mosquitoes. Source Code for Biology and Medicine, 11. 4. pp. 1-11.
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Abstract
Background: Standardized schemas, databases, and public data repositories are needed for the studies of malaria vectors that encompass a remarkably diverse array of designs and rapidly generate large data volumes, often in resource-limited tropical settings lacking specialized software or informatics support.
Results: Data from the majority of mosquito studies conformed to a generic schema, with data collection forms recording the experimental design, sorting of collections, details of sample pooling or subdivision, and additional observations. Generically applicable forms with standardized attribute definitions enabled rigorous, consistent data and sample management with generic software and minimal expertise. Forms use now includes 20 experiments, 8 projects, and 15 users at 3 research and control institutes in 3 African countries, resulting in 11 peer-reviewed publications.
Conclusion: We have designed generic data schema that can be used to develop paper or electronic based data collection forms depending on the availability of resources. We have developed paper-based data collection forms that can be used to collect data from majority of entomological studies across multiple study areas using standardized data formats. Data recorded on these forms with standardized formats can be entered and linked with any relational database software. These informatics tools are recommended because they ensure that medical entomologists save time, improve data quality, and data collected and shared across multiple studies is in standardized formats hence increasing research outputs.
| Item ID: | 43695 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 1751-0473 |
| Additional Information: | © 2016 Kiware et al. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
| Funders: | Bill and Melinda Gates Foundation (BMGF), Wellcome Trust (WT) |
| Projects and Grants: | BMFG 45114, BMFG 52644, BMFG 51431, WT 076806 |
| Date Deposited: | 27 Jul 2016 22:53 |
| FoR Codes: | 46 INFORMATION AND COMPUTING SCIENCES > 4605 Data management and data science > 460599 Data management and data science not elsewhere classified @ 60% 32 BIOMEDICAL AND CLINICAL SCIENCES > 3207 Medical microbiology > 320704 Medical parasitology @ 40% |
| SEO Codes: | 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890205 Information Processing Services (incl. Data Entry and Capture) @ 60% 96 ENVIRONMENT > 9608 Flora, Fauna and Biodiversity > 960805 Flora, Fauna and Biodiversity at Regional or Larger Scales @ 40% |
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