Computational science uses large-scale computation and data to gain insights into complex natural problems ranging from the microscopic to the planetary scale. The legitimacy of computational science emerges from a continuous process of hypothesising, experimentation and recombination of code across these datasets.
We've asked ourselves how we might recenter computational science on the numerous people involved in this process, and so propose the following first set of three principles to start the conversation. We invite interested people to join our exploration.
Science is a human endeavor shaped by contributions from many individuals, and scientific insights stem from and flow through people. All stakeholders, such as academics, curators, traditional knowledge holders, journalists, reviewers, policymakers, and citizens, should be included in and benefit from the process. We aim to build digital infrastructure to both support inquisitive scientific exploration and also to distribute the benefits of evidence-driven actions across society.
Opening the door to public participation in the scientific discourse means broadening access to data and the skills required to analyse it. Today, large institutions play the important role of bringing together researchers under one roof, but emerging digital infrastructure promises new opportunities for participation across institutional and geographic boundaries. We aim to decouple access to the tools for science from institutional affiliation, and thus reduce the barrier to meaningful participation.
We get a maximal return on investments in science when academics, journalists, politicians, curators and others all collaborate effectively across their respective specialisms. We aim to empower creators from all walks of life to create, share and review datasets towards the accumulation of reliable evidence, and incentivize the responsible, ongoing curation of datasets.
Modern computational science should leverage both traditional and community-centered sources of insights and data, and enable such groups to take full advantage of digital resources. We want to develop these in an open and collaborative process that follows the principles above. We invite you to work with us!
Our vision is a world where everybody can access tools to explore, participate in and benefit from computational science.
We are identifying use cases that can be used to help design and iterate on systems towards implementing our manifesto. The use cases are intended to represent needs that different kinds of scientists have. There will be many other additional use cases to bring to light concerns that may not be represented here. Please consider contributing yours!
Some large-scale research projects require acquiring, aggregating, manipulating, analyzing, and reporting on a multitude of data sets. Sometimes, the outputs may even connect to real-time systems, such as data dashboards or sensor networks, which need to be configured as a result of the analysis.
We explore how to balance open science with necessary privacy for sensitive ecological data.
Investigators: Michael Coblenz, Anil Madhavapeddy, Cyrus Omar
Meaningful participation in important scientific discourses requires specialist knowledge, but access to specialized training is currently centralized in universities and gated behind tuition fees and time barriers.
We aim to build sustainable infrastructure for a decentralized network of publicly accessible courseware.
Investigators: Jonathan Sterling, Anil Madhavapeddy
Many research projects require inputs from other researchers, including those in different areas. Finding, using, and extending other researchers' digital artifacts is challenging today.
We're developing systems to make it easier to discover digital artifacts, track contributions, and reduce friction for sharing between research groups.
Investigators: Michael Coblenz
We'd love to have you on board as well; we recognise that we need lots of input and participation from diverse stakeholders across disciplines, and so we invite you to join our exploration and contribute to this open collaboration. Just get in touch with any of the participants above and we can add you to the list above. We're using Matrix to stay connected as well.
Programming for the Planet (PROPL) will bring us together again to refine the manifesto and continue designing our systems for decentralised science.
We held the Bellairs research summit on planetary computing, where we launched the first version of the manifesto towards human computational science.
Jon Sterling publishes the Forester 5.0 design for global identity.
Ian Brown contrasts Mastodon vs BlueSky in a deep-dive of their architectures.
Thomas Gazagnaire launches SpaceOS to perform scientific computation in orbit.
Mark Elvers operates the first capability-based distributed build platform for open source software.
Aurojit Panda rethinks the architecture of edge Internet services to bring back end-to-end simplicity.
Anil Madhavapeddy makes the case for planetary computing for data-driven environmental policy-making to handle the ingestion, transformation, analysis and publication of environmental data products.
Nate Foster considers how programming languages might help to capture property conveyancing, sparking an interest in the legal applications of ownership.
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