Git Product home page Git Product logo

paper_writing_checklist's Introduction

As an earth system scientist and ecologist I model ecosystem processes, such as vegetation growth or drought / disturbance resistance, using various -retrospective- proxy measurements in a model data fusion approach, including among others remote sensing, dendrochronology and recovered historical data records.

Throughout my career I worked interdisciplinary borrowing heavily from fields, outside of ecology, such as image vision processing (computer science), remote sensing and engineering to assist in either field measurements and/or model driven analysis. In addition, I study and publish on swift migration and movement ecology.

I'm the co-founder of BlueGreen Labs, a company dedicated to making sense of oceans of data and address climate change through data driven methods. In this repository you will find legacy projects which are kept for future reference. For recent work I refer to the BlueGreen Labs github page.

paper_writing_checklist's People

Contributors

khufkens avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar

paper_writing_checklist's Issues

More details on writing papers

The idea for improving this document: There should be some clear difference between a product-based paper vs research-based paper.

For a product:

  1. What are the product feature requirements?
  2. How is the product used?
  3. What are the test used to determine the product effectiveness?
  4. Are there any satisfaction surveys for the service?

For research:

  1. What is the research goal?
  2. What are the basic concepts, terms, and definitions?
  3. What are the possible methods of finding the goal?
  4. What is the benchmarking metric for the goal?
  5. Has the benchmarking results been shown?
  6. What is the conclusion of this experiment?
  7. How does the research related to real-life applications

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.