Open science and data
In this part, you will learn about what is open science, what are the different principles in open science and ways how you can practice it.
What is Open Science
Open science is the practice of making scientific research and its dissemination accessible to all, regardless of expertise level. This movement promotes transparency and collaborative work by encouraging the sharing of publications, data, physical samples, and software openly. Key aspects of open science include advocating for open access to research publications, practicing open-notebook science, which involves the open sharing of data and code, and engaging a broader audience in the scientific process. The goal is to facilitate easier publication, access, and communication of scientific knowledge, fostering a more inclusive and collaborative scientific community.
Open data
Open data refers to information that is available for anyone to access, utilize, and distribute. In other words “Open data is data that can be freely used, re-used and redistributed by anyone - subject only, at most, to the requirement to attribute and sharealike.” This data can be used by governments, businesses, and individuals to drive social, economic, and environmental benefits.
Some of the sources of open data include
- Data repositories like Zenodo, Figshare, pangea,gbif
- Global institutions like Food and Agricultural Organization, WorldBank
- Remote sensing data like OpenStreetMap, Google Earth Engine, DIVAGIS, Humanitarian OSM, NASA Earth data, European Space Agency Copernicus Hub
- Social and environmental data like SEDAC
FAIR data
The FAIR data principles are guidelines to ensure that data are Findable, Accessible, Interoperable, and Reusable. These principles aim to make data easy to locate, obtain, and use for various purposes, and to be compatible with other datasets and tools for analysis.
-F - Findable - easy discovery by both researchers as well as computers -A - Accessible - easy availablity under well defined conditions -I - Interoperable - easy integration and sharing across different platforms -R - Reusable - optimize the reuse of research data
Read in detail about the FAIR principles here
Collaborating and sharing your knowledge
- github and gitlab
- quartro
- google collab