Scientific Writing Best Practices

Most people don’t need more charts. They need the right chart. This graphic shows 50 ways to visualize data — and that’s exactly why many dashboards are confusing. Too many choices, not enough thinking. Here’s how I’d use this: Start with the question, not the chart. Comparison? Use column/bar. Trend? Line, area, or sparkline. Distribution? Histogram or box/violin (not 12 pie charts…). Choose by relationship, not aesthetics. Correlation → scatter, correlogram. Composition → stacked bar/area, not donut overload. Flow or structure → Sankey, org chart, network. One insight per visual. If your audience can’t say, “This chart shows X,” in 5 seconds, it’s decoration, not communication. Reduce cognitive load. Fewer colors. Clear labels. No 3D anything. Ever. Build your “go-to 10.” From these 50, pick 10 charts you’ll master. Use them 90% of the time. The pros look “simple” because they obsess over clarity, not complexity. Save this as a checklist for your next report or dashboard. And if you want to go deeper into data storytelling and visualization, Corporate Finance Institute® (CFI)'s resources are a great place to start.

You're wasting your time submitting research without a strategic approach. Yes, there are millions of academic submissions to journals each year, which means there is a lot of potential publication opportunity for you to get. But over the last decade, 95% of research papers submitted to top-tier journals get rejected. Chances are, you are going to be in the 95% rejection bucket. So, does this mean you shouldn't pursue academic publishing? No, it just means you are doing it wrong. The old way of academic publishing, which is what most researchers focus on is... - They write traditional papers using conventional methodologies. - They submit without understanding journal-specific requirements. - They hope for the best. That's why most researchers don't succeed in getting published. That model doesn't work. Academic publishing is valuable and worth doing ONLY IF you do it right. What's the right way? Here are 7 proven steps: 1. Select the right journal Target journals specifically aligned with your research domain and impact factor. 2. Understand submission guidelines Meticulously review and follow every single journal requirement. 3. Craft a compelling title and abstract Your first impression matters - make it crisp, clear, and captivating. 4. Develop rigorous methodology Ensure your research methodology is transparent, replicable, and innovative. 5. Present clean, structured data Use impactful visualizations and statistical analyses that tell a clear story. 6. Write with academic precision Maintain professional language, eliminate grammatical errors, and follow citation standards. 7. Prepare for peer review Anticipate potential questions, be open to constructive feedback, and be ready to revise. Pro Tip: Remember, persistence is key. Even renowned researchers face initial rejections. Have you successfully published in a top-tier journal? What was your biggest challenge? #Research #Science #Scientist #Publishing #Professor #PhD #postdoc #postgraduate #ChemicalEngineering

I want to get published in a #nursing journal! ❓How do I get started❓ 🔹 Consider your area of expertise - What do you know about? What do you research? What have you lived? When writing for a journal, always write about what you know. Your manuscript will be strongest when you write about something that you know know. I once heard someone say that you want to write about whatever you can talk about for an hour without any prep. #greatadvice 🔹 What journal do you want to publish in? - Not every topic is a good match for every journal. Some journals publish original research. Others won’t publish QI projects while others will. There are sections for focused audiences. For example, I am a section editor for a section in the Journal Of Emergency Nursing that is focused on content for early career emergency nurses. If you have a manuscript focused not on infection control in the ambulatory surgical setting for experienced perioperative nurses, your manuscript would not be a good fit for the section that I edit. Finding the right journal and even section of a journal to match your manuscript content and vice versa can help guide your submissions and writing. 🔹 Read the journal - This sounds simple, but it’s necessary. Read past issues of each journal that you are considering a submission for to see what they publish, if they tend to focus on certain style or content, and make sure your writing matches their past content. 🔹 Connect with editors - Considering writing a paper for publication? Reach out to editors to see if they can answer questions or help you with your writing process. As a section editor, I work with authors directly who want to submit for our section. This supports the author and me to optimize submissions in getting accepted. You can often find editorial board members’ contact info on each journal’s website. 🔹 Know the author guidelines - Every journal should have listed author guidelines (or similarly named info) on their website. This info includes word counts, formatting specifics, how to cite your sources, info on specific journal sections, etc. Never start a submission without looking at these guidelines first and ensuring your manuscript is in alignment with the journal’s requirements. 🔹 Find a mentor! - Journal writing is an extremely different style than other forms of writing. A mentor (or several) can help you brainstorm topics, advise on what journals to submit to, connect you with other published writers, act as an editor, and more! Many nursing associations have mentorship programs that are included with your membership dues. Explore your school and professional networks to find someone to support you through the writing process. What other questions do you have? There is so much to consider, and I know I did not capture it all in this post. Already a published author or a journal editor? What did I miss? #nursesonlinkedin #publishing

🔍 Data Visualization (AI & Telecom - PART 9) In data analysis, understanding the underlying patterns within a dataset is critical. Beyond measures like central tendency and dispersion, visualization serves as a powerful tool to unlock insights that numbers alone might hide. Let’s dive into three popular visualization techniques: histograms, box plots, and scatter plots—what they do, and why they matter. 1️⃣ Histogram: Grouping Data for Clarity When you want to analyze a range of values (e.g., internet speeds of different users), histograms shine. Imagine you’re measuring speeds ranging from 1 to 200 Mbps. A histogram helps visualize how many users fall into specific ranges (e.g., 10–20 Mbps, 20–30 Mbps). This distribution, divided into intervals or “bins,” highlights patterns like the most frequent or least frequent values at a glance. Python Tip: Use matplotlib to quickly create histograms with customizable bins for clear groupings. 2️⃣ Box Plot: Summarizing Data in Quarters A box plot offers a clean, visual summary of your dataset by dividing it into four quartiles: It highlights key metrics: minimum, maximum, median, and the 1st & 3rd quartiles. For example, if analyzing call durations, a box plot shows which 25% of users have the shortest calls, the median duration, and the longest calls. 3️⃣ Scatter Plot: Finding Correlations When comparing two variables (e.g., user IDs vs call durations), scatter plots visualize relationships. Each point represents an individual user, making it easy to spot trends or outliers. For example, plotting call durations helps identify users with unusually long or short calls, guiding further investigation. Pro Tip: Add titles and labels to make scatter plots more intuitive for your audience. Why Visualization Matters for Machine Learning Before diving into algorithms, it’s crucial to explore your data visually: Identify Patterns: Spot correlations and relationships that inform feature selection. Filter Noise: Discard irrelevant parameters. Shape Your Models: Visualization helps you understand how individual variables impact the overall analysis. In short, visualizing data transforms it from a sea of numbers into actionable insights—helping you make informed decisions with confidence. 🎯 Whether you’re a beginner or a seasoned data enthusiast, mastering visualizations is a stepping stone toward deeper analytical capabilities. Learn it at - https://lnkd.in/eq6-f8QZ

I sat on an editor's panel this past week, and one of the questions asked was: Why do you desk reject papers? My first thought was: YIKES! Senior editors and editor in chiefs really don't like talking about desk rejection - bc it's the most uncomfortable part of the job. After pausing to think for a second, I replied: formatting. Then explained, if the paper was not formatted for the journal, it usually meant that the authors had not paid attention to the guidelines ... And that was just the start. So, based on my comments, and the comments of other panelists, here are five common reasons that an academic paper never got off the desk! 1. Formatting. If you didn’t follow the journal’s submission guidelines, you’re already making the editor’s life harder. Wrong reference style? Missing abstract? Sloppy figures? That’s not minor—it signals you didn’t take the venue seriously. Note: I was serious in my initial response. 2. Journal Fit. Just because it’s a great paper doesn’t mean it belongs in that journal. If your manuscript doesn’t speak to the journal’s audience or mission, it’s likely getting desk rejected bounced. Editors are looking for fit, not just stories. Note: I have handled several submissions to top journals in my field, which indicate that they were written for another field. If you are going to hop fields, make sure you learn the norms and language of that field. 3. Method Flaws. Every journal has a baseline expectation of methodological rigor. If your sample’s too small, your measure’s unvalidated, or your analysis ignores endogeneity—you may not even make it to review. Note: Some journals simply don't take certain methods. JMIS desk rejects all papers that use PLS, as an example. 4. Weak Contribution. A paper that “extends prior work” isn’t enough. Editors want to see something new, clear, and significant. If they have to dig through three pages of lit review to find the point—you’re in trouble. Note: This bar varies with some journals. In many top IS journals, they want a novel construct. In many top Psych journals, they want a boundary condition. In both fields, they love methodological advances. 5. No Theoretical Center. If you can’t tell me what your study means beyond the data, it's done. Description is not contribution. A good paper builds, refines, or challenges theory. A desk reject often signals that none of those happened. Note: This is true for my genre of work. Critical approaches and true interpretive work uses a very different rubric for evaluation - yet - be it my genre or another - the expectation is that you will advance theory along with description. Want to avoid a desk reject? Start by reading the formatting guidelines for your target journal, then the mission statement on the types of papers and contributions expected. Then, read your paper and ask yourself, honestly: Would I send this out for review? #AcademicWriting #PhDAdvice #PublishingTips

PhD Students - Before you submit your paper to a journal, read this. Pass your paper through this checklist. 1. Your manuscript is free from all kinds of plagiarism? 2. Your manuscript is free from formatting and typo errors? 3. Your article is a good fit for the selected journal/conference? 4. You are adhering to the guidelines of your ethics application? 5. You have disclosed all conflicts of interests? 6. You have read the journal's instructions for authors? 7. Your manuscript adheres to the journal's formatting requirements? 8. You have got consent from all authors for submission? 9. Check review method - single/double blind and follow accordingly? 10. Each reference has dates (sometimes they get missed)? 11. Abstract is within the allocated words limit? 12. Authors' names, affiliations, and emails are included for journals? 13. Each figure and table are correctly numbered and cited in text? 14. The related work section is up to date and complete? 15. Your work is clearly positioned with respect to the related works? 16. You have included ethics statement (if applicable)? 17. You have acknowledged the fundings bodies (if applicable)? 18. You have included the keywords? Any other check you want to add to this list? #research #papers

I know you've been told not to use it, but sometimes, the passive voice can be your friend. For example, when the action (or the target of that action) is what you want to emphasize: "The nation's premier civil rights legislation, the Civil Rights Act of 1964, was signed into law on July 2, 1964." I could've written: "The US president signed the Civil Rights Act of 1964 into law on July 2, 1964 as the nation's premier civil rights legislation" ... but I wanted the "star" of the sentence to be the Civil Rights Act ... or "My bike was stolen last week. I had to walk to work until I could get a new one. I could've written, "Somebody stole my bike last week" ... but I wanted the attention to be on my bike and that it was stolen, not an anonymous thief. Using the passive voice is a matter of style, not a grammatical error. That being said, don't overuse it. The passive voice can make your writing wordy with complicated sentence structures. And overuse can make your writing flat and uninteresting. #Writing #PassiveVoice #Grammar

🎯 Submitting Your Journal Article? Here’s the Real Checklist Most early rejections happen before peer review, simply because authors miss the basics. 1. Choose the Right Journal, then Read the Guidelines Every publisher has its own system: ✔️ Elsevier uses Editorial Manager; formatting is journal-specific. ✔️ Springer requires structure check their “Submission Guidelines.” ✔️ Taylor & Francis often allows format-free first submissions (but not always) ✔️ Wiley has direct upload and ScholarOne, instructions vary widely. ⚠️ Don’t assume. Download the template. Read the checklist. Use their structure. 2. Structure and Format the Manuscript Stick to a clean, professional structure: Title Abstract Keywords Introduction Methods Results Discussion References (Use the journal's preferred style) 💡 Tip: Even if not explicitly required, keep it under ~8,000-12,000 words including references/tables. 3. Build the Right Title Page Full manuscript title (plus short title if needed) All authors’ full names, affiliations, and emails Designated corresponding author ORCID iDs (especially for corresponding and first authors) Author contributions (CRediT roles), or add in a separate statement if asked 4. Write a Real Cover Letter If required (and it often is), make it personal: Address the editor by name Briefly explain why the paper fits this journal Highlight novelty, not just your topic Clarify prior posting (e.g., thesis, preprint, conference paper) 5. Get Your Declarations in Order Mandatory sections include: 1. Funding: Name agency + grant no., or say "no external funding" 2. Conflicts of interest: Disclose clearly, or declare none 3. Ethics: Approval ID, consent, or a note explaining why not needed 4. Data statement: Indicate availability or provide link 6. Figures, Tables & Supplementary Files High-res figures: TIFF, EPS, or PDF at 300–600 dpi Editable tables: Never submit images of tables Label supplementary files clearly (e.g., Figure S1, Table A2) Some journals require graphical abstracts or research highlights, check ahead: Highlights = 3-5 bullets under 20 words each Graphical abstract = simple visual + short caption 7. Reference Style & Similarity Check Use exact citation style requested Run a plagiarism/similarity check before submission 8. Author Biographies Often requested at the end or in metadata. Keep it clean: “Dr. R.A. is an Assistant Professor of Public Policy at XYZ University. Her work focuses on labor regulation and development finance.” 9. Before You Click Submit 🔁 Double-check: Right journal + updated author guidelines Template followed or accepted format-free file Ethics, funding, ORCID, conflicts disclosed Figures/tables clean, cited, labeled Custom cover letter Final version approved by all authors Then upload via: Editorial Manager (Elsevier, Springer) ScholarOne (Wiley, Taylor & Francis) Or journal’s own portal #PublishingTips #ManuscriptSubmission #AcademicPublishing

𝗙𝗼𝘂𝗿 𝗱𝗮𝘁𝗮𝘀𝗲𝘁𝘀. 𝗦𝗮𝗺𝗲 𝘀𝘁𝗮𝘁𝘀. 𝗪𝗶𝗹𝗱𝗹𝘆 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝘀𝘁𝗼𝗿𝗶𝗲𝘀. Visual inspection is 𝘯𝘰𝘵 optional. Anscombe's Quartet is a classic reminder of why plots matter: Each of the four datasets has: 👉The same mean for X and Y 👉The same variance for X and Y 👉The same correlation between X and Y 👉The same linear regression line But when you plot them? 🚨Completely different shapes: ✅A linear relationship ✅A clear curve ✅An outlier dominating the trend ✅A vertical line with a single influential point Same stats. Different stories. 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝘄𝗼𝗿𝗹𝗱: 👉KPIs may hide anomalies 👉Descriptive stats can misinterpret patterns 👉Decision-makers might rely on misleading summaries What looks like a tidy trend could actually be noise. Or worse: a trap. In data science, context is everything. And 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 is often the fastest way to: ✅Spot errors ✅Identify outliers ✅Understand relationships Before trusting any model, always ask: 𝗛𝗮𝘃𝗲 𝘄𝗲 𝘀𝗲𝗲𝗻 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮? 🎯 Plot first. Analyze second. Let's make this a norm: No summary statistics without visual context... ... especially in low-dimensional data. Curious to hear from others: Have you ever been fooled by stats that looked perfect on paper but broke down when you visualized them? Drop your favorite example below. #statistics #datascience #dataviz #analytics

Data science or data analytics without storytelling is void. You can do all the SQL, all the Python, all the modeling — but if the final insight is not communicated in the right visual form, the value is lost. This cheat sheet is a perfect reminder that choosing the right chart is not decoration — it is part of analysis. It breaks the decision down by purpose of insight: 1) Composition Waterfall, Progress bar, Pie, Gauge — great when you want to show parts contributing to a whole or target progress. 2) Comparison Bar charts, Row charts, Line charts, Combo charts — useful when comparing categories or trends over time. 3) Distribution & Relationship Histogram and Scatter plot — when you want to show how values are spread or how two variables interact. 4) Stage Analysis Sankey and Funnel — ideal for visualizing drop-offs or flow across process stages. 5) Single Value KPIs Number & Trend cards — best for dashboards where one metric needs to stand out with context. The skill is not in plotting a chart — the skill is in selecting the correct one for the question being asked. Your analysis is only as powerful as the clarity of how you present it. cc Metabase #DataAnalytics #DataScience #DataVisualization #StorytellingWithData #BI #Metabase #DashboardDesign #DecisionMaking