Code of Conduct
This Code of Conduct helps us build a community that is rooted in our mission to empower scientists to build community and advance scientific progress. This community is built through authenticity, inclusivity, and constructivism.
Whether you’ve come to find community, find solutions to your R&D problems, or to generously contribute your knowledge and experience, join us in building a community where all scientists feel welcome and can participate.
Our Code of Conduct applies to everyone, from our team, to community members, to moderators, and industry representatives. We commit to enforcing and improving the Code of Conduct.
If you’re here to contribute your experiments, make it as easy as possible for others to reproduce your work. Follow our guidelines for contributing experiments.
If you’re here to get help, make it as easy as possible for others to help you. Follow our guidelines and remember that our community is made possible by volunteers.
Be clear and constructive when giving feedback, and be open when receiving it. Edits, comments, and suggestions are healthy parts of our community.
Be inclusive and respectful. Avoid sarcasm and be careful with jokes — tone is hard to decipher online. Prefer gender-neutral language when uncertain. If a situation makes it hard to be friendly, stop participating and move on.
No subtle put-downs or unfriendly language. Even if you don’t intend it, this can have a negative impact on others.
No name-calling or personal attacks. Focus on the content, not the person. This includes terms that feel personal even when they’re applied to content (e.g. “lazy”).
No bigotry. We don’t tolerate any language likely to offend or alienate people based on race, gender, sexual orientation, or religion — and those are just a few examples. Use stated pronouns (when known). When in doubt, don’t use language that might offend or alienate.
No harassment. This includes, but isn’t limited to: bullying, intimidation, vulgar language, direct or indirect threats, sexually suggestive remarks, patterns of inappropriate social contact, and sustained disruptions of discussion.
Every person contributes to building a kind, respectful community. If you find unacceptable behavior directed at yourself or others, you can:
Reach out to us at firstname.lastname@example.org and we’ll respond as quickly as we can.
Sharing methodologies, optimizations, negative results of experiments, positive but unpublishable (whether by sheer gatekeeping or publication hurdles or the like) are pivotal to creating a knowledge-sharing ecosystem in the scientific world. Expediting empirical or conceptual knowledge related to the applications of science is essential, and opacity in methods is considered antithetical to the scientific ethos. There is tons of knowledge that is of use to the scientific community, especially granular methodologies that can help expedite people’s work across the globe. In this sense, one person’s “trash” is another person’s treasure. In this way, by sharing your discoveries (big or small), you can help save everyone time, resources, and ultimately prevent them from “reinventing the wheel”.
This is an informal platform, but regardless that does not mean that information should be presented in a completely informal way–only that it is not up to the stylistic or written rigors of a journal/publication.
The guidelines to posting an experiment are as follows:
1. Focus on the protocol
Write out clear instructions for steps that you have undertaken. Annotation of protocols is important, as many nuanced steps may be taken in the midst. For example, let’s say you use a vortexer to mix some fluid, but that you notice it’s more viscous and requires you to enhance the strength of the mixing.
2. Generated Data
Datasets, whether big or small, anecdotal or large-scale can be of use to the scientific community when taken in context. If you worked with 8 samples and got a certain result that you want to share, that is worth sharing. You may think that it is wrong, negative, or erroneous, but an expansion of your negative results can result in people learning from them, or from you gaining insight into your data that you may not have gleaned from crowdsourcing.
Try to explain what your goal was (or is) originally and why you think so. Unlike a paper, this is an informal setting, and you may describe your experiments in the way you wish to describe them, without a necessary predisposition for extraneous verbiage or fluff.
4. Reproduced Experiments
If in the generation of your experiment or protocol you have followed guidelines from different protocols, experiments, or papers–cite them. Reproducibility is a huge problem in the sciences (as there is no clear incentive for doing it and using it as a form of review). In your quest for the answer, you’ve most likely reproduced portions of other peoples’ experiments. Share your findings, whether they failed, succeeded, and why you think that was the case. Were the instructions or methods easy to follow, or were there specific tricks that you as a scientist knew already to perform to get the right result but that weren’t explicitly indicated? As opposed to papers, here it’s not so much just to cite it, but also to explain whether it worked or not. You might have alignment with your peers on things that have gone wrong (or right) in the methods in question and find answers to your empirical research much faster.
5. Pictures, Videos, and Diagrams.
Some Experiments lend themselves better to be demonstrated in a visual format. Whether it’s a flow chart, or a picture of your experiment in question (say, your bacterial colony), using images is encouraged to elucidate on necessary aspects.
6. Citation (link to the paper)
When using citations, make sure to link to the direct source where it can be read. Linking to Google Scholar, PubMed, or providing the article’s name in question is essential. Use your judgement when including citations, as it’s not always necessary to inundate your post with them, only to direct people as needed towards components of the experiment that actually require further reading or elucidation.
We’d love to help you. To improve your chances of getting an answer, here are some tips:
Before asking your question, it’s first important to attempt a first stab and searching and researching the answer. A baseline understanding of the foundational science behind the methodology, is the most essential, or looking at the site and seeing if other people have answered this question or relatively similar ones. Even if you don’t find a useful answer elsewhere on the website, providing links and information to related questions that were not sufficient in answering your question can help others achieve an understanding and to explain how your question is different from the rest.
The title is the first thing potential answerers will see, and if your title isn’t interesting, they won’t read the rest. So make it count:
- Pretend you’re talking to a busy colleague and have to sum up your entire question in one sentence: what details can you include that will help someone identify and solve your problem? Include any preliminary assumptions or observations, specific metrics, or unusual circumstances that make your question different from similar questions already on the site.
- Spelling, grammar and punctuation are vital! Ultimately, his is the first part of your question others will see - you want to make it stick. If you’re not comfortable writing in English, ask a friend for edits.
- If you’re having trouble summarizing the problem, write the title last - sometimes writing the rest of the question first can make it easier to describe the problem.
- Bad: DNA Extraction problem
- Good: Why does my DNA keep clogging my Qiagen Columns (CN7384) during extraction?
- Bad: improving rna isolation yield
- Good: How do I keep my RNA from getting degraded when using Trizol extractions?
- Bad: rna bioanalyzer broken peak, help fix?
- Good: Integrating the peaks of the reading for an RNA sample on my Agilent Bioanalyzer 2100 keeps crashing the system when I change the threshold–does anyone know of a way to circumvent this?
In the body of your question, start by expanding on the summary you put in the title. Explain how you encountered the problem you’re trying to solve, and any difficulties that have prevented you from solving it yourself. The first paragraph in your question is the second thing most readers will see, so make it as engaging and informative as possible.
Providing an outline of your process, say, a protocol can help people get up to speed with your experimental pitfalls. Additionally, try to reproduce your logic when approaching the problem. Blindly following experiments is never good, but having an understanding of why certain steps are included can help you troubleshoot the problem.
Try to keep extraneous details out of the question such as why you are performing the experiment. Unless it is essential to providing the answer, there is no need to elucidate on the type of research you are doing or things of that proprietary nature. It is that it may have a lot of irrelevant details that readers will need to ignore when trying to reproduce or think about the problem. Here are some guidelines:
- Include just enough information to help reproduce the problem (either experimentally or conceptually)
- Images, Diagrams, Screenshots may be extremely useful in helping solve the problems. An error in a bioinformatics pipeline, a strange color in your chemical, an unidentifiable bacteria growing in your petri dish. Visual queues can be quick ways of demonstrating the problem for faster answering.
Try to include a tag for the topicality, skills and expertise, discipline, instrumentation, or organism your question relates to. If you start typing in the tags field, the system will suggest tags that match what you’ve typed - be sure and read the descriptions given for them to make sure they’re relevant to the question you’re asking! If you can’t find them, you are also able to insert your own tags–just make sure that they truly aren’t in the list before using custom ones.
Now that you’re ready to ask your question, take a deep breath and read through it from start to finish. Pretend you’re seeing it for the first time: does it make sense? Try reproducing the problem yourself, in a fresh environment, and make sure you can do so using only the information included in your question (This can also just be a thought experiment, without necessarily stepping into the lab). Add any details you missed and read through it again. Now is a good time to make sure that your title still describes the problem!
After you post, leave the question open in your browser for a bit, and see if anyone comments. If you missed an obvious piece of information, be ready to respond by editing your question to include it. If someone posts an answer, be ready to try it out and provide feedback!
What is Eureka ?
Eureka is a point-based aggregate of your contributions to the scientific community via activity on Sci Find that is publically displayed. You can gain Eureka by posting experiments, or by other members granting you Eureka based on stimulating information that you disseminate. They can either grant it for the experiment or question itself, or for comments/replies that follow. Eureka is granted to you by the community, and the more involved you are, the more you can obtain.
Eureka is also associated with disciplinary or experiential tags that you use when proliferating your information. For example, if you posted an experiment that was about Viral Genomics (let’s say, sequencing some viral genome), you would use tags such as “Virology” “Genomics” RNAseq” “Viral Genetics”, and would then gain Eureka within those domains. This way, you are always actively showcasing your evolving knowledge and contributions to the system beyond publications. This is a real-time and fast-paced way of getting the world to know your work, and to help them progress theirs.
Every scientist can’t know everything so it is a way of actively creating statistics related to participation and knowledge sharing. It also signals to other members what your specialties are and where you focus your efforts on the platform. It also might exist as an impetus to branch out and explore other areas of science that you may not have thought otherwise to showcase curiosity or just a breadth of knowledge.
What can I do with Eureka ?
Eureka is a reflection of your standing and participation in the scientific ecosystem beyond the world of publishing. Some perks that come with high Eureka! scores can be moderation privileges in certain domains, badges signifying your status, and access to testing upcoming features that Sci Find is always exploring.
How do I give feedback on the platform?
Feedback on the platform is pivotal to its success and to the future of digital scientific collaboration. Input on philosophy, features, wants, needs, suggestions are important. The platform is made by the scientific community, for the scientific community.
In order to give feedback, feel free to join the ‘meta’ forum here https://forum.scifind.io/ where you can introduce yourself and start to talk about the functional components of the network. There you may present your opinions on strategies or features and see if we can bring it to the table. The team at Sci Find is here to implement these suggestions, from philosophy all the way to execution to help push scientific inquiry forward.
We also host virtual town-hall events that you may attend where it is a vocal open forum session for real-time feedback. These are hosted on Clubhouse and you may receive notifications prompting you to attend and provide your insights.