According to the United Nations Educational, Scientific, and Cultural Organization (UNESCO), Open Science is the movement to make scientific research and data accessible to all. It has great potential for advancing science. At its core, it includes (but is not limited to) open access, open data, and open research. Some of the associated advantages are promoting collaboration, sharing and reproducibility in research, and preventing the reinvention of the wheel, thus saving resources. As research becomes more globalized and its output grows exponentially, especially in data, the need for open scientific research practices is more evident — the future of modern science. This has resulted in a concerted global interest in open science uptake. Even so, barriers still exist. The formal training curriculum in most, if not all, universities in Kenya does not equip students with the knowledge and tools to subsequently practice open science in their research. Therefore, to work openly and collaboratively, there is a need for awareness and training in the use of open science tools. These have been neglected, especially in most developing countries, and remain barriers to the cause. Moreover, there is scanty research on the state of affairs regarding the practice and/or adoption of open science. Thus, we developed, through the OpenScienceKE framework, a model to narrow the gap. A sensitize-train-hack-collaborate model was applied in Nairobi, the economic and administrative capital of Kenya. Using the model, we sensitized through seminars, trained on the use of tools through workshops, applied the skills learned in training through hackathons to collaboratively answer the question on the state of open science in Kenya. While the former parts of the model had 20–50 participants, the latter part mainly involved participants with a bioinformatics background, leveraging their advanced computational skills. This model resulted in an open resource that researchers can use to publish as open access cost-effectively. Moreover, we observed a growing interest in open science practices in Kenya through literature search and data mining and that lack of awareness and skills may still hinder the adoption and practice of open science. Furthermore, at the time of the analyses, we surprisingly found that out of the 20,069 papers downloaded from BioRXiv, only 18 had Kenyan authors, a majority of which are international (16) collaborations. This may suggest poor uptake of the use of preprints among Kenyan researchers. The findings in this study highlight the state of open science in Kenya and challenges facing its adoption and practice while bringing forth possible areas for primary consideration in the campaign toward open science. It also proposes a model (sensitize-train-hack-collaborate model) that may be adopted by researchers, funders and other proponents of open science to address some of the challenges faced in promoting its adoption in Kenya.

Background Staphylococcus aureus cause diseases both in humans and animals. These diseases range from mild to fatal infections thus necessitating development of a specific molecular method for detection of pathogenic S. aureus. Objectives To identify and analyze genetic profile of pathogenic S. aureus using bacteriophage based genetic biomarkers. Methods Using culture and biochemical methods, 148 S. aureus (87 %) were isolated from 170 raw milk samples taken from 10 dairy farms in Marsabit and Isiolo counties in Northern Kenya between June 2016 and February 2017. The samples were collected directly from dairy lactating cows previously diagnosed with S. aureus in a follow‐up study. The isolates were analyzed by PCR and sequencing of beta hemolysin (hlb) gene. The genetic relationship between five Kenyan S. aureus isolates and five isolates previously identified was inferred. Results From the 96 isolates screened for hlb gene, 75 (78.1%) tested positive. Some of the positive isolates yielded a band size of 975 bp, while others 1100 bp. Through Basic Local Alignment Search Tool (BLAST) search analysis, the two different band sizes (975 bp and 1100 bp) were both confirmed to be hlb gene from S. aureus isolates indicating that the difference in band size may have been due to deletions that were detected in the 975 bp hlb gene. Some S. aureus isolates from Kenya appeared to be closely related to isolates from other parts of the world, while some showed a distant relationship. Conclusions Phage‐derived hlb gene is a suitable molecular marker for detection of pathogenic S. aureus.

Open, collaborative, and reproducible research – Open Science – has great potential for advancing science. However, the training in our local universities does not equip students with the tools to practice open science. Additionally, to work in the open and collaborate, the collaborators should be trained to use shared tools. Therefore, the main barrier to working open is the lack of awareness of the collaboration tools and the skills required to utilize these tools. Thus, to fill the gap, through an open science community funded by a Mozilla Mini-grant, OpenScienceKE, we are promoting open science among bioinformatics students and researchers in the Nairobi area using this model: sensitize, train, hack and collaborate. This model first sensitizes on open science practices through seminars, trains on open science tools through workshops, facilitates the hands-on application of the tools through hackathons, and finally fosters a community of open science enthusiasts through meetups.OpenScienceKE sought to address the following problems: the lack of awareness of open science practices and tools within the Bioinformatics community in Kenya; the low adoption of open science practices in Bioinformatics; and the absence of research establishing the state of affairs in adopting open science in Kenya. Through the OpenScienceKE hackathon, we created an open resource that the students could use to figure out where they can cost-effectively publish open access. We observed a growing interest in open science practices in Kenya through literature search and data mining, but the lack of awareness and skills still hinders adoption. The use of preprints for research dissemination has not caught up in Kenya; out of the 20,069 papers downloaded from BioRXiv, only 18 have Kenyan authors, a majority of which are international (16) collaborations. We also observed a lack of incentives and policies in academic and research institutions to support open science. The fear of being scooped and the competitive spirit within the scientific community are also significant barriers to working in the open.The first iteration of the model, which focused on academic institutions, set the foundation for the next phase: promote open and reproducible science in research institutions. This model provides the framework for the adoption of open science practices within the institutions. As genomic research data generated in Africa grows, there is a need to adopt open science practices in data storage, reproducible pipelines, and collaborative research. We propose an approach, which develops the necessary infrastructure within research institutions, and builds human capacity through the model: sensitize, train, hack, and collaborate. The promotion of open science in Africa recognizes the future direction of research, and OpenScienceKE is growing the culture and practice in research.

No abstract

No abstract