How often do we look at the results of our work with frustration, disappointment, or even anger at failed attempts? As another semester of teaching came to a close, I found myself once again with students who were not satisfied with their overall grade in the class, seeking ways to make up for lost time to get better results. The problem, however, is not with the results, but with the effort (or lack thereof) throughout the process.

An old Buddhist proverb says, “If a seed of a lettuce will not grow, we do not blame the lettuce. Instead, the fault lies with us for not having nourished the seed properly.” What are you doing during your writing process to nourish it in a way that produces the results you intend?

In this week’s collection of articles from around the web, we see advice on making everything count, sharpening and revising our work, supporting peer review excellence, and using datasets to conduct research better. This week, focus on taking deliberate action at each step of the writing process to nourish your work in the direction of your future goals. Happy writing!

Writing an end-of-the-month achievements review: Making *everything* count

Often times, we don’t even realize how much we are contributing to scholarly life (to our discipline, our field, our colleagues and peers, our institution). Writing what you did over the course of the month reminds you of that (beyond surviving, which is a success in & of itself).

Sharpen up your application

One of the most basic pieces of advice for writers is ‘know your audience’. Unfortunately, I often find that people write their grant applications for a completely amorphous audience like ‘the government’ or ‘the Department of [Whoever is Funding the Grant]’. That’s just not true. Your grant application will be read by a very small, very specific audience of maybe 5 – 7 people. It is much more effective to write for this very focused imagined audience than for a huge, amorphous undefined audience.

Revising – nine steps for making meaning

Revising for meaning cannot simply depend, Murray asserts, on the feedback of others. Other people do not necessarily know what the writer is trying to say. Readers’ comments may point the writer in a direction that they don’t want to take. The writer may even be unaware of the going-off-course effect because they are not yet sure themselves where their writing is going. Writers need to be their own best critical readers.

How one society is supporting peer review excellence in their community: An interview with Laura Feetham of IOP Publishing

Last year, to coincide with Peer Review Week, IOP Publishing launched the first peer review certification program tailored for the physical sciences — an e-learning hub that forms part of their broader peer review excellence program. They are placing special emphasis on peer review ethics, which is a topic I have a strong personal interest in, so I’m grateful to their Reviewer Engagement Manager, Laura Feetham, for answering my questions about the program overall, and the ethics component in particular.

What do researchers need to know about using datasets?

Want to learn more about research with datasets? This post includes a curated collection of open-access articles about defining characteristics, data literacy skills needed to understand and work with large datasets, and machine learning tools for managing Big Data sources.