This lecture describes how to build research workflows, including a demonstrate using DataJoint Elements to build data pipelines.
This lesson provides an introduction to the Symposium on Science Management at the Canadian Association for Neuroscience 2019 Meeting.
This lesson gives a primer to project management in a scientific context, with a particular neuroinformatic case study.
In this lesson, you will hear about the current challenges regarding data management, as well as policies and resources aimed to address them.
This lesson covers "Knowledge Translation", the activities involved in moving research from the laboratory, the research journal, and the academic conference into the hands of people and organizations who can put it to practical use.
In this lesson, you will hear about the various methods developed and employed in managing performance.
This lesson provides an overview of how to manage relationships in a research context, while highlighting the need for effective communication at various levels.
This lesson introduces several open science tools like Docker and Apptainer which can be used to develop portable and reproducible software environments.
This opening lecture from INCF's Short Course in Neuroinformatics provides an overview of the field of neuroinformatics itself, as well as laying out an argument for the necessity for developing more sophisticated approaches towards FAIR data management principles in neuroscience.
This lecture covers a wide range of aspects regarding neuroinformatics and data governance, describing both their historical developments and current trajectories. Particular tools, platforms, and standards to make your research more FAIR are also discussed.
This lecture provides an overview of successful open-access projects aimed at describing complex neuroscientific models, and makes a case for expanded use of resources in support of reproducibility and validation of models against experimental data.
KnowledgeSpace is a community-based encyclopedia that links brain research concepts to data, models, and literature. It provides users with access to anatomy, gene expression, models, morphology, and physiology data from over 15 different neuroscience data/model repositories, such as Allen Institute for Brain Science and the Human Brain Project.
This talk deals with Identifiers.org, a central infrastructure for findable, accessible, interoperable and re-usable (FAIR) data, which provides a range of services to promote the citability of individual data providers and integration with e-infrastructures.
This lecture gives an introduction to the FAIR (findability, accessibility, interoperability, and reusability) science principles and examples of their application in neuroscience research.
This lecture covers FAIR atlases, including their background and construction, as well as how they can be created in line with the FAIR principles.
This lecture covers why data sharing and other collaborative practices are important, how these practices are developed, and the challenges involved in their development and implementation.
This lecture covers the biomedical researcher's perspective on FAIR data sharing and the importance of finding better ways to manage large datasets.
This lecture covers the needs and challenges involved in creating a FAIR ecosystem for neuroimaging research.
This lecture covers multiple aspects of FAIR neuroscience data: what makes it unique, the challenges to making it FAIR, the importance of overcoming these challenges, and how data governance comes into play.
This lecture introduces the FAIR principles, how they relate to the field of computational neuroscience, and the resources available.