Global Health Engineering https://global-health-engineering.github.io/website/blog/ Homepage for slides, tutorials, and other teaching material. quarto-1.9.38 Tue, 02 Jun 2026 00:00:00 GMT Plan for tomorrow today: why you need a data steward Lars Schöbitz Prof. Elizabeth Tilley https://global-health-engineering.github.io/website/blog/posts/2024-03-08-swissrn-abstract/

Slides

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Title: “Plan for tomorrow today: why you need a data steward” (10 / 40 words)

Abstract (350/350 words)

This talk will promote the RTR research practices we have applied to research at the Chair of Global Health Engineering (ETH Zurich) and the scientific community. Using our group as a case study example, we will highlight our approach to producing open data and code as individual research products and explain how they are separate from and sometimes more valuable than the scientific articles derived from them.

The R package development environment allows researchers to keep an audit trail from unprocessed raw data to analysis-ready data. Data is stored in a git repository on GitHub with the code for data processing, rich metadata and documentation, following FAIR data sharing principles. The repository contains a citation file format (.cff) file that records each contributor’s ORCID ID and a permissive CC-BY license. The GitHub to Zenodo integration allows for the automated generation of a digital object identifier (DOI) and ensures long-term archiving, following internationally recommended best practices by funding agencies. Once published, the entry is imported to the ETH Research Collection via the DOI for increased discoverability and institutional archiving. For data communication purposes, the R package pkgdown is ideal. Without any web development experience, the package allows competent R practitioners to prepare a visually appealing website with R code snippets showing exploratory data analysis examples.

We invest in this process at the data collection point long before preparing a scientific article. The process actively promotes rigorous research data management practices among our students and senior staff, who follow best practices for transparency and open scholarship as part of their daily practice rather than in an ad-hoc fashion at the end of the project. Researchers can then use the published R data package to prepare a scientific article and cite the repository. In doing so, they can comply with the journal’s data availability statements and long-term archiving policies.

Implementing these practices was only feasible by hiring a full-time data steward. We will discuss how invested financial resources will pay off as publishers of high-quality journals will increasingly require that article submissions comply with data and code transparency, the foundation of computational reproducibility.

Conference info

Selected Topic: Transparency and Open Scholarship

Explore the transformative wave of open scholarship, emphasizing the importance of transparency in the research lifecycle. From pre-registration and registered reports to open access publications, research data, and code—this session illuminates the pivotal role of open practices in fostering trust and collaboration in the scientific community.

Conference Goals

  • Engage with researchers to make their research rigorous, transparent and reproducible
  • Promote RTR research practices
  • Disseminate ways to improve research quality

Opportunities and Exposure:

  • Foster scientific exchange across all disciplines in Switzerland
  • Provide the research community with a unique exposure to resources, expertise, and approaches in reproducible research
]]> https://global-health-engineering.github.io/website/blog/posts/2024-03-08-swissrn-abstract/ Tue, 02 Jun 2026 00:00:00 GMT From Smoke to Solution: Advancing Black Carbon as a Regulatory Pollutant Saloni Vijay Mian Zhong Elizabeth Tilley https://global-health-engineering.github.io/website/blog/posts/2024-07-16-black-carbon/

License: CC BY 4.0 DOI

What is Black Carbon?

Black carbon is an air pollutant: a component of fine particulate matter that is smaller than 2.5 mm in diameter (PM2.5), it is formed through the incomplete combustion of fossil fuels, biomass, and waste. Essentially, it is a very small particle that forms part of a smoke plume that is either inhaled or dispersed into the atmosphere.

Black carbon, a sooty particulate matter in emission plumes. Photo by Thijs Stoop on Unsplash.

The Case for Regulation

Due to its significant climate and health impacts, as well as its traceability to specific sources, black carbon is increasingly discussed as a potential regulatory pollutant.

Climate Impacts: Black carbon emissions are of concern due to their extremely high global warming potential: up to 5000 times greater than CO2. Black carbon absorbs sunlight and heats the atmosphere, accelerating global warming. When deposited on ice and snow, it reduces their reflectivity, leading to quicker melting.

Health Impacts: These minute particles penetrate deep into the lungs and enter the bloodstream, exacerbating respiratory and cardiovascular diseases and increasing the risk of lung cancer. A specific form of PM2.5, it is more toxic to human health than other types of PM2.5 such as dust.

Source Identification: One reason why black carbon would be easier to regulate than other pollutants is our ability to pinpoint the source. Black carbon from fossil fuels and biomass can be distinguished by their optical properties, allowing for targeted reduction strategies. This capability enhances the effectiveness of emission reduction efforts, enabling evidence-based decisions to address the predominant sources.

Gaps in Global Monitoring: The case of Africa

Despite the significant climate and health impacts of black carbon, global monitoring efforts remain inadequate. While ambient black carbon monitoring is increasing in European countries, the United States, India and China, but Africa lags behind. Only a few countries, such as Ghana, Kenya, and Rwanda.), have some ambient black carbon data, with the high cost of monitors being a major barrier to more extensive data collection.

Even PM2.5, which was declared a regulatory pollutant in 1997 in the U.S., is still inadequately monitored in many African countries. Western Africa has approximately one reference-grade1 PM2.5 monitor per 10 million people, and the situation is even worse in Eastern Africa, with only one reference-grade monitor per 100 million people.). Introducing black carbon as a regulatory pollutant would require substantial investment and infrastructure development to achieve effective monitoring across the continent. Figure 1 illustrates the global distribution of PM2.5 monitoring stations, as documeted by OpenAQ2.

Figure 1: A screenshot from OpenAQ illustrating the global distribution of PM2.5 monitoring stations.

Overcoming Cost Barriers: Innovating Affordable Solutions

Low-cost PM2.5 monitors have expanded access to air quality data. We need similar advancements for black carbon monitoring. Developing hybrid networks that integrate low-cost monitors with reference-grade stations could enhance coverage and accuracy. Currently, what is considered cost-effective often exceeds 3000 USD. During my PhD research in Malawi, I utilized the microAeth® MA200 monitor for personal exposure measurements, which, while less costly than other monitors, was still expensive for the low-income context. Each filter tape, costing approximately 100 USD, lasted only three days due to the high-concentration environment, underscoring the ongoing financial challenges in resource-limited settings.

Research efforts are crucial to developing affordable monitoring technology, particularly in regions like Asia and Africa that contribute 63% of global black carbon emissions. Current monitors, primarily designed for cleaner environments, are inadequate for high-emission areas; even after the initial investment, recurring costs such as filter tapes continue to pose challenges.

Saloni Vijay, the author of this blog (right), and Hope Kelvin Chilunga (left), a collaborator of the GHE group, setting up an experiment to monitor black carbon emissions from cooking with solid biofuels in Blantyre, Malawi. Photo by Saloni Vijay, CC-BY license.

Steps Forward

Effective black carbon regulation requires a multifaceted approach that includes technological, regulatory, and educational initiatives.

Develop Affordable Monitors: To make black carbon regulation feasible, affordable and reliable monitoring technology must be developed. Investment in research and the development of low-cost monitors is essential to facilitate widespread adoption.

Establish Clear Guidelines for Monitoring and Reporting: These guidelines should be internationally harmonized to ensure consistency and comparability of data. Additionally, proper limits for ambient concentrations need to be established to provide clear standards for assessing black carbon levels and their impacts.

Raise Awareness and Build Capacity: This includes training and resources for local authorities to implement and maintain monitoring networks.

Policy Integration:  Leveraging existing infrastructure and expertise from PM2.5 monitoring could accelerate the implementation of black carbon regulations.

By addressing these key areas, we can enhance our ability to monitor, regulate, and reduce black carbon concentrations, ultimately improving air quality and public health.

About the author

Saloni Vijay is a PhD student in the Global Health Engineering group, ETH Zurich. She is currently focused on evaluating the environmental risks and health impacts of open trash burning, with a specific emphasis on black carbon concentrations in Blantyre, Malawi.

If you are interested in learning more about Saloni’s work on Black Carbon in Blantyre, feel free to write her an email at svijay@ethz.ch or on LinkedIn.

Saloni is giving a talk at the European Aerosol Conference, 2024 in August in Tampere, Finland, and attending the International Global Atmospheric Chemistry (IGAC) short course and conference, 2024 in September in Malaysia. If you are present at any of these events, please reach out and connect. She would love to hear about your work and share hers.

Footnotes

  1. A reference-grade air quality monitor is a high-precision, certified instrument used for accurate and reliable measurements of air pollutants, meeting stringent regulatory standards.↩︎

  2. OpenAQ is a nonprofit organization providing universal access to air quality data to empower a global community of changemakers to solve air inequality—the unequal access to clean air.↩︎

Citation

BibTeX citation:
@misc{vijay2024,
  author = {Vijay, Saloni and Zhong, Mian and Tilley, Elizabeth},
  title = {From {Smoke} to {Solution:} {Advancing} {Black} {Carbon} as a
    {Regulatory} {Pollutant}},
  date = {2024-07-16},
  url = {https://ghe.ethz.ch/ghe-blog-news.html},
  doi = {10.5281/zenodo.12705811},
  langid = {en}
}
For attribution, please cite this work as:
Vijay, Saloni, Mian Zhong, and Elizabeth Tilley. 2024. “From Smoke to Solution: Advancing Black Carbon as a Regulatory Pollutant.” From Smoke to Solution: Advancing Black Carbon as a Regulatory Pollutant, July 16. https://doi.org/10.5281/zenodo.12705811.
]]> air quality black carbon regulations https://global-health-engineering.github.io/website/blog/posts/2024-07-16-black-carbon/ Tue, 16 Jul 2024 00:00:00 GMT Motivation for Team Award Lars Schöbitz https://global-health-engineering.github.io/website/blog/posts/2024-02-27-swissrn-award/ This motivation was written in response to the call for nominations for the Swiss Reproducibility Award 2024. The motivation was written by Lars Schöbitz, a team member at the Global Health Engineering group at ETH Zurich.

The result of the review process was announced on 8th May 2024 and this nomination has not been selected as the winner of the category.

Motivation (word count: 347/350 words)

We are dedicated to rigorous, transparent, and reproducible research. We aim to make all our research outputs reproducible and foster an Open Science culture. For this purpose, we use public GitHub repositories for version control, collaboration, and integration with Zenodo for long-term archiving and generation of a Digital Object Identifier (DOI).

We categorize our data into three stages:

  • Stage 1: unprocessed raw data
  • Stage 2: processed analysis-ready data
  • Stage 3: data supporting publication results

The raw data’s value is relatively low, but the code transforming it into analysis-ready data is invaluable. This code enhances transparency, promotes reusability, and boosts efficiency. It streamlines data cleaning, a crucial but often overlooked task. Moreover, by packaging our code as functions, we enhance efficiency in data cleaning for similar future projects. We ensure a complete audit trail from raw to analysis-ready data by openly sharing both alongside the code within the same repository. In addition, we use a permissive CC-BY license, assign DOIs, and link ORCID IDs to acknowledge all contributors, including those often unrecognized in scientific outputs (e.g. surveyors and lab technicians). Finally, our data is published as an R data package, enhancing accessibility and usability.

In Stage 2, we use the above R data package to prepare a reproducible manuscript. We utilize a literate programming tool to integrate narrative and code. The manuscript is stored and managed in another git repository. It receives a separate DOI, highlighting the differences between data cleaning and curation activities, which is performed by a data steward supporting the group, and the actual work that goes into authoring a manuscript, fine-tuning tables, figures and models, which rests with the scientists.

In Stage 3, we produce CSV files for the data supporting the publication results (e.g. tables, figures, models), allowing others to use our results quickly.

Our team has an Open Science Specialist who mentors our staff and students in applying open science principles, which unifies our team, aligning everyone with our vision and mission. Our team deserves this award to recognize our efforts to make science more rigorous, transparent, and reproducible.

]]> https://global-health-engineering.github.io/website/blog/posts/2024-02-27-swissrn-award/ Tue, 27 Feb 2024 00:00:00 GMT Attention, Prof: You need a data steward for your team. Lars Schöbitz https://global-health-engineering.github.io/website/blog/posts/2024-02-13-data-steward/ Note: This blog post was published is a re-published version from the Global Health Engineering website. For attribution, please see the Citation information at the end of this post.

Lead

You are a professor. You’re working long hours; you’re working weekends; you’re sitting in committees, and stuck in meetings that could have been emails; you’re teaching, grading, supervising, and mentoring. And now, on top of all that, you are supposed to make all your research data public, by applying FAIR principles. You need a data steward.

What’s a data steward?

In simple terms and in the context of research, a data stewards are defined as “people who support the management of research data and reproducible data workflows in research groups, institutes and departments.”1

What profile do they need?

Few established programmes specifically qualify people to be a data steward (e.g. Postgraduate Center University of Vienna2). At the moment, it’s a skill that’s mostly learned on the job. Do not look for academic degrees (e.g. a PhD) or for someone on an academic career path (e.g. with a long list of publications). Look for someone who has an affinity for IT, has worked in various organizations (government, private sector, research) , and with different types of data (lab experiments, observations, quantitative & qualitative surveys). A Research Software Engineer, which is a more established term, could be a good fit, but there are other suitable profiles, too.

What can you offer them?

Whether it’s data stewardship or research software engineering, both career paths still need to be fully recognized and established within the scientific community. However, at ETH Zurich, there is an attractive career path for someone without a PhD. It falls under the “administrative, technical, IT and laboratory staff” category. The assigned function code 4042 (System specialist / software engineering) offers an attractive salary for someone with >5 years of experience, the yearly appraisal interview for mechanisms of a performance-bound annual increase, and also the potential for a permanent position.

What are the tasks?

A data steward will support you in defining your strategy for Research Data Management (RDM). Ideally, this is a strategy that promotes the concepts of open research data and open code to support computational reproducibility, a practice that is increasingly important to make research more rigorous, transparent, and impactful. When we established our group in 2021, we defined this role more generally as “Open Science Specialist”, and you can find the published job description2 for your own use. Since then, we have established new projects and defined our RDM strategy and workflows3.

How a data steward supports the group

On a group level, a data steward hosts strategic meetings. They organize workshops to identify current file and data management practices within a group. They don’t prescribe one way of doing things but rather help determine the best practices for the group, allowing individual researchers to use the workflows and tools that suit them best to maintain scientific autonomy.

How a data steward supports the individual

On an individual level, a data steward offers weekly RDM support. They become the bridge from abstract concepts like FAIR principles, version control, and literate programming to the actual intellectual work needed.

Data stewardship in practice

At Global Health Engineering, we aim to make all our research outputs reproducible and foster an Open Science culture. In our workflow (which starts with designing a research study and ends with the production of a scientific article), we categorize our data into three stages:

  • Stage 1: unprocessed raw data
  • Stage 2: processed analysis-ready data
  • Stage 3: data supporting publication results

The unique work required to manage the collected data is recognized in each of these stages. We assign a digital object identifier (DOI) to the code that transforms the unprocessed raw data from Stage 1 into processed analysis-ready data (Stage 2). Together, they form a data package, which is fully documented with relevant metadata, and is citeable and reusable by the research community. A data steward is uniquely positioned to support data cleaning and curation, so that the researcher can focus on applying their expertise to the data rather than on the data itself. The actual work that goes into authoring a manuscript, fine-tuning tables, and preparing figures and models rests with the researcher and is what we consider getting data from Stage 2 to Stage 3. The data steward remains available to support the researcher in applying best practices for data management. Still, the researcher is the one who is responsible for the analysis, discussion, and conclusions.

ETH Library Data Stewardship Network

The ETH Library initiated a programme funded by swissuniversities to build a data stewardship network at ETH4. It has identified six people at ETH who already consider themselves to have this role and dedicate 20% of their time to data stewardship activities beyond the tasks they already perform for the research group. Through these activities, data stewards can further explore and develop their skills and competencies in data stewardship and, at the same time, support other researchers in applying best practices for data management and sharing5.

Hire now & discuss

Hiring a data steward for your group who can connect and engage with other data stewards at ETH and beyond will significantly advance the impact of your research. If you are interested in speaking about hiring a data steward, please get in touch: <ghe@mavt.ethz.ch> or connect with us for a discussion on our open room on Matrix chat: https://matrix.to/#/#ghe-open:staffchat.ethz.ch

Footnotes

  1. https://library.ethz.ch/en/researching-and-publishing/data-management-and-policies/research-data-management/data-stewardship.html↩︎

  2. https://github.com/Global-Health-Engineering/job-descriptions/blob/main/open-science-specialist/README.md↩︎

  3. https://ghe.ethz.ch/open-science.html↩︎

  4. https://library.ethz.ch/en/researching-and-publishing/data-management-and-policies/research-data-management/data-stewardship.html↩︎

  5. https://ethz.ch/staffnet/en/news-and-events/internal-news/archive/2023/03/interview-eine-vision-fuer-open-science-and-data-stewardship-an-der-eth-zuerich.html↩︎

Citation

BibTeX citation:
@misc{schöbitz2024,
  author = {Schöbitz, Lars},
  title = {Attention, {Prof:} {You} Need a Data Steward for Your Team.},
  date = {2024-02-13},
  url = {https://ghe.ethz.ch/ghe-blog-news.html},
  doi = {10.5281/zenodo.8318442},
  langid = {en}
}
For attribution, please cite this work as:
Schöbitz, Lars. 2024. “Attention, Prof: You need a data steward for your team.” Global Health Engineering Blog, February 13. https://doi.org/10.5281/zenodo.8318442.
]]> open science open data metrics https://global-health-engineering.github.io/website/blog/posts/2024-02-13-data-steward/ Tue, 13 Feb 2024 00:00:00 GMT We can’t decolonize research until we fix publishing Elizabeth Tilley https://global-health-engineering.github.io/website/blog/posts/2023-11-14-change-publishing/ Note: This blog post was published is a re-published version from the Global Health Engineering website. For attribution, please see the Citation information at the end of this post.

In the olden days, back before the internet, academic publishing was a laborious, but distinguished process. Authors would submit manuscripts to prestigious publishers, who would in turn, seek out the most renowned scientists in the field and solicit their commentary. The publisher would then type-set, print, and mail the bound paper journal to the few institutions that could afford the pricey, yet vital, subscription. Being an invited reviewer, or an editor was an honour, and the honour was deemed to be sufficient compensation for hours, if not days of work.

But things changed. On the one hand, “open-access” publishing has allowed millions (billions?) of people to read scientific papers without having to pay for a subscription; as of 2020, about 36% of articles have full open access 1. In 2021, The International Water Association (IWA), which publishes important WASH-sector journals like Water Science & Technology2, and my favourite, WASHDEV3, announced that 10 of their titles would be published completely open-access4 going forward and would allow authors from 103 countries to publish for free, or for an unlucky 33, a 50% discount5 (sorry, Nicaragua). These initiatives are part of “decolonizing research”, i.e. increasing access to those researchers and students without the means to subscribe, submit, or read papers behind unaffordable paywalls. Unfortunately, researchers from the Global South, are still publishing at rates far lower than their more funded colleagues, and even more worrisome, are still rarely included as authors about work done in their own countries: of the publications on Africa climate research, 58% (7232) included no African authors6. The measures in place are not enough, but there is growing recognition that more must be done to increase diversity and reduce bias within publishing, and fee waivers are a start.

On the other hand, for-profit publishing houses have become increasingly commercial and monopolistic, multiplying the mechanisms for making money from authors while expanding the need for unpaid reviewers and editors. Currently, academic publishing is dominated by 5 main houses: Elsevier, John Wiley & Sons, Taylor & Francis, Springer Nature, and SAGE who, combined, generate about 50% of the $19 billion in annual profit7. Elsevier, who manages 2928 different journals, reported £8.5 billion in revenue for 2022, and £2.6 billion in adjusted operating profit8. Meanwhile, few editors are paid for their service, and the hoards of reviewers, upon whom the entire industry rests, are kindly thanked (sometimes with a coupon).

As a response to what can only be called the greedy hyperaccumulation of wealth, some are pushing back. More than 40 scientists resigned from the editorial board of Elsevier’s journal Neuroimage9 and in 2019, The University of California (one of the largest academic institutions in the US) decided to not renew its $11 million a year subscription fee10 contract with Elsevier, after lengthy negotiations failed to ensure that all UC publications would be made open access. These bold actions are commendable and are adding cracks to an already eroded foundation of trust in traditional publishing. Transformation is underway and inevitable but requires action from everyone: not just big account holders. What, you may be wondering, can I do? Whether you are a first time reviewer or a seasoned pro, I’ve compiled a few, simple actions that you can take to help make publishing more fair, diverse, and efficient for everyone.

Actions for Reviewers who want to make an impact within the current system

In 2022, over 5 million papers were published11. For any given paper, an Editor may send out between 5 and 20 reviewer invitations to get 2-3 acceptable reviews that can be returned to, and actually help, the author. Editors don’t want to flood your inboxes with requests, but we are increasingly becoming desperate to find sufficient and suitable reviewers within a manageable time frame. The best thing you can do as a reviewer is to accept the invitation, write a great report, and submit it on time. This keeps the wheels of academia moving.

If you don’t have the time or expertise, the next best thing you can do is reject the invitation immediately. Typically, an editor will set a “respond-by” date: if the invited reviewer does not respond within say, 2 weeks, the editor will look for another. Waiting until the invitation expires means that the clock starts again, and the paper continues to languish, frustrating the author and editor alike. If you really can’t do the review, click the “reject” button and let the Editor get to work on finding a replacement.

However, before blindly following my advice and rejecting every invitation that comes your way, consider your obligations to the system as well as your opportunities to change it. Go check your profile on Web of Science12: there, you can see your publications, your citations, and your review statistics. With a Peer Review to Publication ratio of 1.9:1, I am in the 95th percentile of reviewers who have a median of 0.3:1. In other words, I review almost 2 papers for every one I publish, which is at the low-end of what is needed to fully cover the reviews that I receive for my publications. For everyone else who is reviewing less than 1 paper for every 3 they publish, we need more from you. And if you haven’t been invited as a reviewer yet, send an email to the editor of your favourite journal asking them to add you to their database: they will be thrilled!

And yes, asking for more is a big request; especially for junior faculty, women, and those already burdened with various types of unpaid labour. But you have choices: consider passing up requests from “top tier” journals and focus your limited time on providing feedback for first-time authors or manuscripts from less represented countries13. As long as the journal is indexed14, you get the same amount of credit for reviewing for a journal that is considered “less prestigious”, but your impact will be much greater. Importantly, you can also always decline to review if you see something you don’t like: refusing to take on a manuscript without an author from the country of study, sends a strong signal to the editor, and hopefully, in time, the journal.

Until we have a complete overhaul of the publishing industry that includes new models of reviewing15, funding16, and disseminating research17, we must do our best to exist within it. However, small, consistent, acts by millions of ethical academics will hasten the crumbling of a system that excludes too many and profits too few. What role will you play?

Elizabeth Tilley is currently an Associate Editor for WASHDEV18 and WaterSA19, and was formerly an Editor for Waste Management20 and The Malawi Medical Journal21.

Footnotes

  1. https://wordsrated.com/academic-publishing-statistics/↩︎

  2. https://iwaponline.com/wst↩︎

  3. https://iwaponline.com/washdev↩︎

  4. https://iwa-network.org/news/iwap-open-access/↩︎

  5. https://iwaponline.com/open_access/pages/Research4Life↩︎

  6. https://doi.org/10.1016/j.envsci.2021.10.023↩︎

  7. https://wordsrated.com/academic-publishers-statistics/↩︎

  8. https://stories.relx.com/2022-relx-highlights/index.html↩︎

  9. https://t.co/0aamG7bemJ↩︎

  10. https://www.universityofcalifornia.edu/news/why-uc-split-publishing-giant-elsevier↩︎

  11. https://wordsrated.com/academic-publishing-statistics/↩︎

  12. https://www.webofscience.com↩︎

  13. https://www.ajol.info/index.php/ajol↩︎

  14. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3354504/↩︎

  15. https://openreview.net/about↩︎

  16. https://doi.org/10.1186/s41073-021-00118-2↩︎

  17. https://zenodo.org/records/7974116↩︎

  18. https://iwaponline.com/washdev↩︎

  19. https://watersa.net/↩︎

  20. https://www.sciencedirect.com/journal/waste-management↩︎

  21. https://www.mmj.mw/↩︎

Citation

BibTeX citation:
@misc{tilley2023,
  author = {Tilley, Elizabeth},
  title = {We Can’t Decolonize Research Until We Fix Publishing},
  date = {2023-11-14},
  url = {https://ghe.ethz.ch/ghe-blog-news.html},
  doi = {10.5281/zenodo.8318442},
  langid = {en}
}
For attribution, please cite this work as:
Tilley, Elizabeth. 2023. “We can’t decolonize research until we fix publishing.” Global Health Engineering Blog, November 14. https://doi.org/10.5281/zenodo.8318442.
]]> decolonization publishing peer-review https://global-health-engineering.github.io/website/blog/posts/2023-11-14-change-publishing/ Tue, 14 Nov 2023 00:00:00 GMT Creating collaboration on the ground: Reflecting on my first visit to Kenya Jakub Tkaczuk https://global-health-engineering.github.io/website/blog/posts/2023-10-10-collaboration-kenya/ Note: This blog post was published is a re-published version from the Global Health Engineering website. For attribution, please see the Citation information at the end of this post.

As a freshly employed senior scientist at Global Health Engineering, part of my role is coordinating the multitude of student projects we offer each semester. Our students are engaged in a range of vital research projects related to human health across several African countries. For instance, over the past two years GHE students have partnered with Sistema Bio in Kenya to design and test the use of biogas for the thermal disinfection of wastewater. And, although as a mechanical engineer I have been able to evaluate and advise on this work, one problem remains - I have never been to Kenya and I’ve never personally engaged with the problems we are trying to help address. What’s the best way to address this professional shortcoming? Although we are all trying to reduce our personal carbon emissions, Zoom calls can only get you so far - sometimes you have to travel to learn.

In September 2023 I had the privilege to travel to Kenya with my supervisor Prof. Tilley to connect with our biogas project partners. My journey in Kenya allowed me to engage with a variety of individuals from diverse backgrounds who all enriched my own understanding of Kenya and its socio-​technical challenges. This included learners and educators at schools in Kiababu and Ikinu, a Meru University of Science and Technology professor1, and entrepreneurs in Kisumu2 made. The enthusiasm of students and educators was contagious; I was impressed by their dedication to learning. Apart from all the engaging and meaningful exchanges, I also stirred cubic meters of human waste for the first time in my life. Again, Zoom is a useful tool, but standing together and getting your hands dirty trying to solve a problem can bring the answer much quicker. With all of the partners in the same space, learning together, we were able to identify issues with the biogas installation, found clear paths for further development, and devised a sustainable plan for future collaboration to scale up our findings nationally.

By accident, at the same time as our stay in Kenya, the first Africa Climate Summit3 took place, bringing around 30 - 35 thousand visitors to Nairobi. I had a chance to exchange with the Summit’s participants. The opportunity was invaluable and provided additional context for framing my work. After the Covid-​19 pandemic, everyone got used to virtual meetings and remote working, but the trip reminded me that travel, and the experiences that come with it, can be invaluable. Although you may collaborate from a distance, in-​person interactions can provide immediate answers to problems which otherwise would take long days to understand through a chain of email exchanges. In retrospect, my first trip to Kenya was a rich and diverse experience, both professionally and personally. I departed with an intent to return, and a clearer vision of how I can support both my students and our Kenyan partners. Moreover, I left Kenya with a profound sense of appreciation for its culture, as well as hope for its future to be brighter. Although I may have returned to Zurich, to a calendar full of online meetings, I’m already thinking ahead to my next trip.

 

Footnotes

  1. https://www.must.ac.ke/celebrating-excellence-dr-joy-riungu-receives-the-distinguished-alumni-award-2022-from-ihe-delft/↩︎

  2. https://www.opero-services.com/↩︎

  3. https://africaclimatesummit.org/↩︎

Citation

BibTeX citation:
@misc{tkaczuk2023,
  author = {Tkaczuk, Jakub},
  title = {Creating Collaboration on the Ground: {Reflecting} on My
    First Visit to {Kenya}},
  date = {2023-10-10},
  url = {https://ghe.ethz.ch/ghe-blog-news.html},
  doi = {10.5281/zenodo.8318442},
  langid = {en}
}
For attribution, please cite this work as:
Tkaczuk, Jakub. 2023. “Creating collaboration on the ground: Reflecting on my first visit to Kenya.” Global Health Engineering Blog, October 10. https://doi.org/10.5281/zenodo.8318442.
]]> collaboration travel learning https://global-health-engineering.github.io/website/blog/posts/2023-10-10-collaboration-kenya/ Tue, 10 Oct 2023 00:00:00 GMT In an era of open science, how is ‘transparency’ shifting within qualitative research Marc Kalina https://global-health-engineering.github.io/website/blog/posts/2023-09-04-qualitative-data/ Note: This blog post was published is a re-published version from the Global Health Engineering website. For attribution, please see the Citation information at the end of this post.

Qualitative research is inherently not reproducible or replicable, a fact those with a more positivist view of knowledge creation find hard to digest. Reproducibility means obtaining consistent results using the same protocol and data, while replicability entails obtaining the same results using the same methods but with different data or a different sample. When using interpretive qualitative methods (which rely on the co-creation of knowledge between researcher and respondent), both the study conditions and the results obtained can hinge on a variety of factors, not least of all, the positionality of the individual researcher. Simply put: when you ask someone a question, you are not guaranteed the same response I might receive.

Therefore, within qualitative research it is more common to speak of transparency, rather than reproducibility or replicability, when evaluating the scientific rigour of a given piece of work. And, while the broader scientific community has moved towards increased openness with data and analysis, there has been a growing debate within qualitative research communities on how much transparency is necessary or possible within current praxis. Sebastian Karcher1 of the Qualitative Data Repository has helpfully distinguished between three three types of transparency most relevant in qualitative research.

  1. Production transparency: Information on how a study generates or collects data. This can include an interview schedule, and the types of methodological detail that would flesh out a good methods section, such as sample, subject recruitment, exclusion criteria, etc.
  2. Analytic transparency: Information on how data is prepared and analysed.
  3. Data access: Data availability, including access conditions.

Of these forms, the first two have become increasingly de rigueur, with detailed methods sections becoming expected, and information on analysis, including codebooks, becoming increasingly common as supplementary submissions to articles. However, data transparency, including open use and access for qualitative material, especially within the social sciences, has lagged far behind other disciplines where open access is increasingly becoming the standard. There are practical reasons for this, because, as Sebastian Karcher notes, transparency within qualitative research is not a straightforward path, and is often fraught with ethical considerations and practical barriers. What are we doing at Global Health Engineering (GHE) to move this discussion forward and become more transparent in our own work?

At GHE we have made a pledge to embrace the full spectrum of transparency: to make all of our data, either quantitative or qualitative, open access under permissive licenses, and to publicly document how it has been produced and analysed2. This is, of course, important, so that the rigour of our research practice can be clearly evaluated, and so that our data can be accessible to other researchers, who may favour other modes of analysis, allowing the words of our respondents to resonate further and make an impact beyond what we may have foreseen.

Through our partnership with the openwashdata team we recently published our first open access qualitative dataset: a series of 61 semi-structured interviews with biogas plant owners in southern Malawi (Schöbitz et al. 2023). Moving forward, we intend to publish all of our work in similar fashion, but as a qualitative researcher going through this process for the first time, what did I learn from the experience?

First, making our data open access necessitates a change in ethical practice, particularly in how we obtain consent and inform participants on how their responses will be utilised. Will participants be as willing to speak freely if they know their responses will be made public, albeit anonymously? Second, the preparation of qualitative material for open access is an important step– but is time and resource intensive. Even with an in-house ETH data steward who was able to automate some of these processes, the anonymisation and packaging of transcripts is time consuming. Although we were able to devote the time and resources towards publishing the data package, I am concerned about the feasibility for scholars in less-resourced institutional contexts of giving their work the same platform as standards for transparency shift.

Nonetheless, we are pleased with the results of our first effort, and invite engagement and feedback from the greater scientific community. Moving forward, what do we want to improve? First, we would like to be more timely with our outputs, with data packages being published soon after they are collected, ensuring their broader usefulness and to support our own published analyses. Second, to date, we have only published transcripts in English. In the future we will also publish transcripts in the language in which the data collection was conducted, so that the un-translated voices of our respondents can stand on their own. Finally, we intend to develop data management guidelines and open source tools to support data preparation processes so that scholars from low-resource contexts can pursue data publishing without regard to material constraints.

The future is hard to predict, but we are hopeful it will be more transparent.

References

Schöbitz, Lars, Sebastian Camilo Loos, Marc Kalina, Jonathan Olal Ogwang, Jonathan Kwangulero, and Elizabeth Tilley. 2023. Biogasoutcomesmalawi: Data for 61 Semi-Structured Interviews with Biogas Owners in Malawi. https://doi.org/10.5281/zenodo.8289621.

Footnotes

  1. This is a great blog post by Open Working summing up a presentation by Sebastian Karcher at TU Delft on the limits of reproducibility within qualitative research: https://openworking.wordpress.com/2019/02/11/what-does-reproducibility-mean-for-qualitative-research/↩︎

  2. Learn more about how we do this in this interview with Dr. Julian Dederke of the ETH Library: https://ethz.ch/staffnet/en/news-and-events/internal-news/archive/2023/03/interview-eine-vision-fuer-open-science-and-data-stewardship-an-der-eth-zuerich.html↩︎

Citation

BibTeX citation:
@misc{kalina2023,
  author = {Kalina, Marc},
  title = {In an Era of Open Science, How Is “Transparency” Shifting
    Within Qualitative Research},
  date = {2023-06-21},
  url = {https://ghe.ethz.ch/ghe-blog-news.html},
  doi = {10.5281/zenodo.8318442},
  langid = {en}
}
For attribution, please cite this work as:
Kalina, Marc. 2023. “In an era of open science, how is ‘transparency’ shifting within qualitative research.” Global Health Engineering Blog, June 21. https://doi.org/10.5281/zenodo.8318442.
]]> qualitative data transparency transcripts https://global-health-engineering.github.io/website/blog/posts/2023-09-04-qualitative-data/ Wed, 21 Jun 2023 00:00:00 GMT https://global-health-engineering.github.io/website/blog/posts/2025-10-30-ai-at-ghe/index.docx https://global-health-engineering.github.io/website/blog/posts/2025-10-30-ai-at-ghe/index.docx Tue, 02 Jun 2026 10:42:49 GMT