Neuroinformatics is a research field devoted to the development of neuroscience data and knowledge bases together with computational models and analytical tools for sharing, integration, and analysis of experimental data and advancement of theories about the nervous system function. In the INCF context, neuroinformatics refers to scientific information about primary experimental data, ontology, metadata, analytical tools, and computational models of the nervous system.
Common to both the large brain projects and individual investigator led research is the recognition that neuroscience as a whole needs to converge towards a more open and collaborative enterprise, with neuroscientists around the globe committed to open sharing of data and tools. The Declaration of Intent of the International Brain Initiative, an alliance of large national brain projects, states: “Researchers working on brain initiatives from around the world recognise that they are engaged in an effort so large and complex that even with the unprecedented efforts and resources from public and private enterprise, no single initiative will be able to tackle the challenge to fully understand the brain”.
Effective resource sharing means not just that data, processing methods, workflows and tools are made available, but that they are made available in a way that ensures that published findings can be reproduced.
Of equal importance, in the age of machine learning and artificial intelligence, data should be published with integration and reuse in mind, so they can be interpreted in new ways, and leveraged so that new knowledge can be extracted. For that to happen, neuroscience as a discipline needs to adopt the FAIR principles, ensuring that the results of science are Findable, Accessible, Interoperable and Reusable, to both humans and machines.
The FAIR principles are guidelines for improving the Findability, Accessibility, Interoperability, and Reuse of digital assets. Researchers increasingly rely on computational support to deal with big and complex data, therefore the FAIR principles emphasise the machine-actionability of data - the capacity of computational systems to find, access, interoperate, and reuse data without human intervention.
The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.
As an individual you can become an INCF member and receive discounts on registration fees, products, and services provided by INCF and our partner organizations. Get actively involved by joining an existing Working Group or forming your own, by participating in our annual Neuroinformatics Assembly, and other events. You can also subscribe to our newsletter, interact with us at other conferences, and engage with us on social media:
Organizations, institutions, companies, and governments can also become members in order to participate in decision-making and discussions around global strategy for neuroinformatics, trainin, and standards and best practises for neuroscience.
The INCF Governing Members contribute financially to INCF, and have decision-making power for the organization through representation on the INCF Governing Board. The European Union is also represented on the Board as an observer.
The Board is advised by the Council for Training, Science, and Infrastructure (CTSI) on priorities and target areas for neuroinformatics. The CTSI has appointed subcommittees for focused efforts in training and education, infrastructure, and the management of INCF's endorsement process for standards and best practices.
TrainingSpace (TS) is an online hub that hosts multimedia educational content from courses, conference lectures, and laboratory exercises from some of the world’s leading neuroscience institutes and societies, and makes the content accessible to the global neuroscience community. TS provides users with courses and study tracks for self-guided study, tutorials on tools and open science resources for neuroscience research, a Q&A forum, and access to publicly-available datasets as well as links to literature references.
KnowledgeSpace (KS) is a community-based, data-driven encyclopedia for neuroscience that links brain research concepts to the data, models, and literature that support them. KS is a framework that combines general descriptions of neuroscience concepts found in wikipedia with more detailed content from NeuroLex. It then integrates the content from those two sources with the latest neuroscience citations found in PubMed and data found in some of the world’s leading neuroscience repositories.
Neurobot is a data access tool developed by INCF in close collaboration with the CENTER-TBI Data Curation Task Force. It is continuously updated to meet the needs of CENTER-TBI researchers to easily find the study variables and export them for further analysis. In addition to the Clinical data, the associated imaging and ICU data are currently available through Neurobot. Links are provided to large data files such as imaging and high-resolution ICU data, and they are combined with the clinical data of the individual patients based on the Global Unique Personal Identifier (GUPI).
Neurostars (NS) is a question and answer forum that serves the INCF network as:
- a forum for knowledge exchange between groups around the world,
- a point of interaction between neuroscientists, software developers, and infrastructure providers, and
- an integral resource in the network’s training and mentoring initiative