During these past tumultuous years, it has been striking to witness the role that information has played in furthering suffering: misinformation, lack of data transparency, and closed technology have worsened the pandemic, increased political strife, and hurt climate policy. Building on these observations, the team at Open Knowledge Foundation are refocusing our energies on how we can come together to empower people, communities, and organisations to create and use open knowledge to solve the most urgent issues of our time, including climate change, inequality, and access to knowledge . Undaunted by these substantial challenges, we entered 2022 with enthusiasm for finding ways to work together, starting with climate data.
To start this year fresh and inspired, we convened two gatherings of climate researchers, activists, and organisations to brainstorm ways to collaborate to make open climate data more usable, accessible, and impactful. Over 30 experts attended the two sessions, from organisations around the world, and we identified and discussed many problems in the climate data space. We confirmed our initial theory that many of us are working siloed and that combining skills, knowledge and networks can result in a powerful alliance across tech communities, data experts and climate crisis activists.
Now, we want to share with you some common themes from these sessions and ask: how can we work together to solve these pressing climate issues?
A primary concern of attendees was the disconnect between how (and why) data is produced and how data can (and should) be used. This disconnect shows up as frictions for data use: we know that much existing “open” data isn’t actually usable. During the call, many participants mentioned they frequently can’t find open data, and even when they can find it, they can’t easily access it. Even when they can access the data, they often can’t easily use it.
So why is it so hard to find, access, and use climate data? First, climate data is not particularly well standardised or curated, and data creators need better training in data management best practices. Another issue is that many climate data users don’t have technical training or knowledge required to clean messy data, greatly slowing down their research or policy work.
# How will the Open Knowledge Foundation fix the identified problems? Skills, standards and community.
An aim for this work will be to bridge the gaps between data creators and users. We plan to host several workshops in the future to work with both these groups, focusing on identifying both skills gaps and data gaps, then working towards capacity building.
Our goal with capacity building will be to give a data platform to those most affected by climate change. How do we make it easier for less technical or newer data users to effectively use climate data? Our future workshops will focus on training data creators and users with the Open Knowledge Frictionless Data tooling (opens new window) to better manage data, create higher quality data, and share data in impactful ways that will empower trained researchers and activists alike. For instance, the Frictionless toolbox can help data creators generate clean data that is easy to understand, share, and use, and the new Frictionless tool Livemark can help data consumers easily share climate data with impactful visualisations and narratives.
Another theme that emerged from the brainstorm sessions was the role data plays in generating knowledge versus the role knowledge plays in generating data, and how this interplay can be maximised to create change. For instance, we need to take a hard look at how “open” replicates cycles of inequalities. Several people brought up the great work citizen scientists are doing for climate research, but how these efforts are rarely recognised by governments or other official research channels. So much vital data on local impacts of climate change are being lost as they aren’t being incorporated into official datasets. How do we make data more equitable, ensuring that those being most affected by climate change can use data to tell their stories?
We call on data organisations, climate researchers, and activists to join us in these efforts. How can we best work together to solve pressing climate change issues? Would you like to partner with us for workshops, or do you have other ideas for collaborations? Let us know! We would like to give our utmost thanks to the organisations that joined our brainstorming sessions for paving the way in this important work. To continue planning this work, we are creating a space to talk in our Frictionless Data community chat, and we invite all interested parties to join us. We are currently migrating our community from Discord to Slack. We encourage you to join the Slack channel, which will soon be populated with all Frictionless community members: https://join.slack.com/t/frictionlessdata/shared_invite/zt-14x9bxnkm-2y~uQcmmrqarSP2kV39_Kg (opens new window)
(We also have a Matrix mirror if you prefer Matrix: https://matrix.to/#/#frictionless-data:matrix.org (opens new window))
Finally, we’d like to share this list of resources that attendees shared during the calls:
- Patrick J McGovern Data for Climate 2022 Accelerator: https://www.mcgovern.org/foundation-awards-4-5m-including-new-accelerator-grants-to-advance-data-driven-climate-solutions/ (opens new window)
- Open Climate: https://www.appropedia.org/OpenClimate (opens new window)
- Environmental Data and Governance Initiative: https://envirodatagov.org/ (opens new window)
- Earth Science Information Partners: https://www.esipfed.org/about (opens new window)
Course on environmental data journalism by School of Data Brazil: https://escoladedados.org/courses/jornalismo-de-dados-ambientais/ (opens new window)
- Catalogue of environmental databases in Brazil by School of Data Brazil: https://bit.ly/dados-ambientais (opens new window)
- A monthly meetup for small companies to share best practices (and data): https://climatiq.io/blog/climate-action-net-zero-ambition-best-practices-for-sme (opens new window)
- Reddit Datasets: https://www.reddit.com/r/datasets/ (opens new window)
- Hardware information standard: https://barbal.co/the-open-know-how-manifest-specification-version-1-0/ (opens new window)
- Catalyst Cooperative: https://github.com/catalyst-cooperative/pudl (opens new window) and https://zenodo.org/communities/catalyst-cooperative/ (opens new window)
- Research Data Alliance Agriculture: https://www.rd-alliance.org/rda-disciplines/rda-and-agriculture (opens new window)
- Open Climate Now!: https://branch.climateaction.tech/issues/issue-2/open-climate-now/ (opens new window)
- Metadata Game Changers: https://metadatagamechangers.com (opens new window)
- Excellent lecture by J McGlade bridging attitudes etc. to the data story and behaviour change effects: https://www.youtube.com/watch?v=eIRlLlrnmBM&t=1561s (opens new window)
- The Integrated-Assessment Modeling Community (IAMC) is developing a Python package “pyam” for scenario analysis & data visualization: https://pyam-iamc.readthedocs.io (opens new window)
- IIASA is hosting numerous scenario ensemble databases, see https://data.ece.iiasa.ac.at (opens new window), most importantly the scenario ensemble supporting the quantitative assessment in the IPCC 1.5°C Special Report (2018), and a similar database will be released in two months together with IPCC AR6 WG3
- Letter to IEA by the openmod community, https://forum.openmod.org/t/open-letter-to-iea-and-member-countries-requesting-open-data/2949 (opens new window)