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Join #Hacktoberfest 2019 with Frictionless Data

- October 3, 2019 in Frictionless Data, hackathon

The Frictionless Data team is excited to participate in #Hacktoberfest 2019! Hacktoberfest is a month-long event where people from around the world contribute to open source software (and – you can win a t-shirt!). How does it work? All October, the Frictionless Data repositories will have issues ready for contributions from the open source community. These issues will be labeled with ‘Hacktoberfest’ so they can be easily found. Issues will range from beginner level to more advanced, so anyone who is interested can participate. Even if you’ve never contributed to Frictionless Data before, now is the time!  To begin, sign up on the official website ( and then read the OKF project participation guidelines + code of conduct and coding standards. Then find an issue that interests you by searching through the issues on the main Frictionless libraries (found here) and also on our participating Tool Fund repositories here. Next, write some code to help fix the issue, and open a pull request for the Frictionless Team to review. Finally, celebrate your contribution to an open source project! We value and rely on our community, and are really excited to participate in this year’s #Hacktoberfest. If you get stuck or have questions, reach out to the team via our Gitter channel, or comment on an issue. Let’s get hacking!

A recap of the 2019 eLife Innovation Sprint

- September 26, 2019 in Events, Frictionless Data, Open Science

Over 36 hours, Jo Barratt and Lilly Winfree from Open Knowledge Foundation’s Frictionless Data team joined 60 people from around the world to develop innovative solutions to open science obstacles at the 2019 eLife Innovation Sprint. This quick, collaborative event in Cambridge, UK, on September 4th and 5th brought together designers, scientists, coders, project managers, and communications experts to develop their budding ideas into functional prototypes. Projects focused on all aspects of open science, including but not limited to improving scientific publishing, data management, and increasing diversity, equity, and inclusion. Both Jo and Lilly pitched projects and thoroughly enjoyed working with their teams on these projects.  Lilly pitched creating an open science game that could be used to teach scientists about open best practices in a fun and informative way. Read on to learn more about these projects, and their experiences at the Sprint. Jo proposed making a podcast documenting the Sprint experience, projects, and people aiming to that would be fully produced and edited and publish the piece during the Sprint.  Lilly’s inspiration to create an open science game came from her experience at Force11 in 2018, where she played a game about FAIR data (Findable, Accessible, Interoperable, and Reusable). She realized that playing a game can be a great way to learn about a subject that might otherwise seem dry, and creating a game prototype seemed like a fun, accessible, and achievable goal for the Sprint. The open science game team formed with eight people from diverse backgrounds, including a game designer, board game enthusiasts, publishers, and scientists. This mix of backgrounds was a big asset to the team, and played a large role in the development of a functional game prototype. To start designing the game, the team first decided that the goal of the game should be to teach scientists about open science best practices, while the collaborative goal for the players would be to make an important scientific discovery – like curing a disease. The team crafted the storyline of the game, and finally worked on the game play mechanics. In the end, the game was made for 2-5 players and ideally would take about 30-45 minutes to play. To play, each player gets a role card — Lab Principal Investigator, Graduate Student, Data Management Librarian, Teaching Assistant, and Data Scientist. Each of these roles has personas and attributes that impact the game. For instance, the Principal Investigator has negative attributes that make sharing research openly harder, while the Teaching Assistant has positive attributes that make it easier to teach new tools to other players. On each turn, the players can draw research object cards or tool cards that help advance the game, but might also draw an event card, which can have positive of negative effects on the gameplay. The ultimate goal is for the players to share their research findings, which requires the player to draw and “research” an insight card and it’s related methods card, data collection card, and analysis card. The game ends once enough research findings are shared (either openly or with restricted access). A fun and interesting part of the game is that the players can role play their characters and see how attitudes towards open science differ and how those attitudes affect the progression of science. Hint: to win the game, the players have to cooperate with each other and openly share at least some of their research findings. The team is currently digitising the game so others can play it – keep track of their progress on their GitHub Repository.
“My team was fantastic to work with. I came to the Sprint with a basic idea and a hope that we could create a fun, educational game on open science, but my team really ran with the idea and created a game that is so much more than I had hoped for!” – Lilly Winfree, OKF

OKF delivery manager, Jo Barratt, brought his storytelling talents to the forefront for the eLife Sprint by proposing the creation of a podcast to document the people and ideas at the Sprint. Jo has produced many podcasts over the years, and thought the podcast format would offer a unique perspective into the inner workings of the Sprint. He was delighted to have two other Sprint members join his Podcast team: Hannah Drury and Elsa Loissel from eLife. Neither Hannah nor Elsa had worked on a podcast before, but both were eager and quick learners. Their project started with Jo giving Hannah and Elsa quick lessons on interviewing, using recording equipment, editing and sound design. Jo was really excited to have such collaborative team members to work with, which was very in line with the synergistic spirit of the Sprint. To capture a feel for the essence of the Sprint, Hannah and Elsa began by interviewing most Sprint members, asking them questions like about their backgrounds and what they hoped to get out of the sprint. Interviewees were also asked to give their views on what ‘open science’ means to them. Next, the team interviewed several projects for a more in depth discussion into how the Sprint works and what types of projects were being developed. In the final podcast, there are interviews with the teams from the open science game project, one on equitable preprints, the project looking at computational training best practices, and the high performance computing in Africa team. Each of these segments shows the people, methods, and progress of the projects, highlighting the diverse people and ideas at the Sprint and giving listeners insight into the process of this type of event as well as many of the problems that face the open science community. Jo’s highlight of the podcast was a conversation between current Innovation officer at eLife, Emmy Tsang, and the past officer, Naomi Penfold. They discussed their experiences hosting the Sprint, and to commented on changes they have witnessed in the open science movement. Listeners to the podcast will notice the overarching themes of openness, collaboration, excitement, and hope for the future of science, while also being challenged to think about who is being left behind in the progress towards a more open world. You can hear the full podcast (and see pictures from the Sprint) here, or listen on Soundcloud here.
“I supported them but really this was made by two scientists who had zero experience in this and I think making this in 2 days is really quite impressive!” – Jo Barratt, OKF
The OKF team would like to thank Emmy and eLife for a great experience at the Sprint!

Part of the Open Knowledge Foundation team met up in Cambridge the day before the Sprint began, and saved the world from a meteor (at an escape room)!

A halfway point update from the 2019 Frictionless Data Tool Fund

- September 25, 2019 in Featured, Frictionless Data, tool fund

In June 2019, we launched the Frictionless Data Tool Fund to facilitate reproducible data workflows in research contexts. Our four Tool Fund grantees are now at the halfway point of their projects, and have made great progress. Read on to learn more about these projects, their next steps, and how you can also contribute.

Stephan Max: Data Package tools for Google Sheets

Stephan’s Tool Fund work is focused on creating an add-on for Google Sheets to allow for Data Package import and export. With this tool, researchers (and other data wranglers) that use Google Sheets will be able to quickly and easily incorporate Data Packages into their existing data processing workflows. Recently, Stephan created a prototype that you can test at the project’s GitHub Repo by following the steps outlined in the README file: Next steps for Stephan’s project include enhancing the user interface, and adding additional information such as licensing options for the export button. If you try the prototype, please leave Stephan feedback as an issue in the repository.

João Peschanski and team: Neuroscience Experiments System (NES)

To improve the way neuroscience experimental data and metadata is shared, João and the team at the Research, Innovation and Dissemination Center for Neuromathematics (RIDC NeuroMat) are working on implementing Data Packages into their Neuroscience Experiments System (NES). NES is an open-source tool for data collection that stores large amounts of data in a structured way. This tool aims to assist neuroscience research laboratories in routine experimental procedures. During the Tool Fund, João and team have created a Data Package exportation module from within NES that reflects the Frictionless specifications for data and metadata interoperability. This export includes a JSON file descriptor (a datapackage.json file) with information related to how the experiment was performed, with a goal of increasing reproducibility. Next steps for the team include more testing and gathering feedback, and then a public release. The NES GitHub repository can be seen here:

André Heughebaert: DarwinCore Archive Data Package support

Inspired by his work with the Global Biodiversity Information Facility (GBIF), André is converting DarwinCore Archives into Data Packages for his Tool Fund project. The DarwinCore is a standard describing biological diversity that is intended to increase interoperability of biological data. André has recently completed a first release of the tool, which appends datapackage.json and files containing the data descriptors and human readable metadata to the DarwinCore archive. This release supports all standard DarwinCore terms, and has been tested with several use cases. You can read more about Frictionless DarwinCore and see all of the use cases André tested for the beta release in the repo’s README file. If you want to test or contribute to this Tool Fund project, please open an issue in the repository.

Shelby Switzer and Greg Bloom: Open Referral Human Services data package support

Shelby’s Tool Fund work is building out datapackage support for Open Referral’s Human Service Data Specification (HSDS) and Human Service Data API Suite (HSDA). Open Referral develops data standards and open source tools for health, human, and social services. For the Tool Fund, Shelby has been developing on their HSDS-Transformer, which takes raw data, transforms it to HSDS format, and then packages it as a datapackage within a zip file, so users can work with tidily packaged data. For example, Shelby and the Open Referral team have been working with 2-1-1 in Miami-Dade, Florida, to help transform and share their resource directory database with their partners in a more sustainable fashion. Next steps for Shelby include creating a UI for their HSDS-Transformer so that anyone can access HSDS-compliant datapackages. Shelby will also be contributing to the improvement of the datapackage Ruby gem during this project.

Frictionless Data at the EPFL Open Science in Practice Summer School

- September 16, 2019 in Featured, Frictionless Data, Open Science

In early September our Frictionless Data for Reproducible Research product manager, Lilly Winfree, presented a workshop at the Open Science in Practice Summer School at EPFL University in Lausanne, Switzerland.  Lilly’s workshop focused on teaching early career researchers about using Frictionless software and specs to make their research data more interoperable, shareable, and open. The audience learned about metadata, data schemas, creating data packages, and validating their data with Goodtables. The slides for her workshop are available here, and are licensed as CC-BY-4.0. The Summer School was organized by Luc Henry, Scientific Advisor at EPFL, and was a week-long series of talks and workshops on open science best practices for research students and early career researchers. A highlight of the workshop for Lilly was having the opportunity to work with Oleg Lavrovsky in person. Oleg is on the board of the Swizz chapter of OKF,, and created the Frictionless Data Julia libraries as a Tool Fund grantee two years ago. Oleg wrote a recap of the workshop, which we are republishing below. The original can be read here. Thanks for your help, Oleg, and for Luc for organizing!

“Open” is the new black. Everybody talks about open science. But what does it mean exactly?

Lilly Winfree of the Frictionless Data for Reproducible Research project at OKF ran a workshop at Open Science in Practice, a week long training organized by the EPFL with Eurotech Universities. It was a top grade workshop delivered to a diverse room of doctoral students, early career researchers, “and beyond” in Lausanne. I had the opportunity to assist her, and learn from her professional delivery, get up to speed with key points about Open Knowledge Foundation, the latest news from the small, diligent people working to make open data more accessible and useful. With a fascinating science background, she connected well with the audience and made a strong case for well published open research data. The workshop reignited my desire to continue publishing Data Packages, contribute to the project, develop better support in various software environments, and be present in community channels. In our conversation afterwards, we talked about the remote work culture and global reach of the team, expectations management, and the challenges ahead. Thanks very much to @heluc and the rest of the #OSIP2019 team for organizing a great event, to all who participated in the workshop for patiently and interestedly hacking their first Data Packages together, and kudos to Lilly for crossing distances to bridge gaps and support Open Science in Switzerland.

Next events

There are two upcoming events that Oleg is involved with that might be of interest to the Frictionless Data and OKF communities: the DINAcon Digital Sustainability Conference, on October 18 in Bern, and the Tourism Hackathon on November 29 in Lucerne.

A warm welcome to our Frictionless Data for Reproducible Research Fellows

- August 29, 2019 in Featured, Frictionless Data, Open Science

As part of our commitment to opening up scientific knowledge, we recently launched the Frictionless Data for Reproducible Research Fellows Programme, which will run from mid-September until June 2020.  We received over 200 impressive applications for the Programme, and are very excited to introduce the four selected Fellows:
  • Monica Granados, a Mitacs Canadian Science Policy Fellow; 
  • Selene Yang, a graduate student researcher at the National University of La Plata, Argentina; 
  • Daniel Ouso, a postgraduate researcher at the International Centre of Insect Physiology and Ecology; 
  • Lily Zhao, a graduate student researcher at the University of California, Santa Barbara. 
Next month, the Fellows will be writing blogs to further introduce themselves to the Frictionless Data community, so stay tuned to learn more about these impressive researchers. The Programme will train early career researchers to become champions of the Frictionless Data tools and approaches in their field. Fellows will learn about Frictionless Data, including how to use Frictionless tools in their domains to improve reproducible research workflows, and how to advocate for open science. Working closely with the Frictionless Data team, Fellows will lead training workshops at conferences, host events at universities and in labs, and write blogs and other communications content. As the programme progresses, we will be sharing the Fellows’ work on making research more reproducible with the Frictionless Data software suite by posting a series of blogs here and on the Fellows website. In June 2020, the Programme will culminate in a community call where all Fellows will present what they have learned over the nine months: we encourage attendance by our community. If you are interested in learning more about the Programme, the syllabus, lessons, and resources are open.

More About Frictionless Data

The Fellows Programme is part of the Frictionless Data for Reproducible Research project at Open Knowledge Foundation. This project, funded by the Sloan Foundation, applies our work in Frictionless Data to data-driven research disciplines, in order to facilitate data workflows in research contexts. Frictionless Data is a set of specifications for data and metadata interoperability, accompanied by a collection of software libraries that implement these specifications, and a range of best practices for data management. Frictionless Data’s other current projects include the Tool Fund, in which four grantees are developing open source tooling for reproducible research. The Fellows Programme will be running until June 2020, and we will post updates to the Programme as they progress.

Meet our 2019 Frictionless Data Tool Fund grantees

- July 4, 2019 in Featured, Frictionless Data

In order to facilitate reproducible data workflows in research contexts, we recently launched the Frictionless Data Tool Fund. This one-time $5,000 grant attracted over 90 applications from researchers, developers, and data managers from all over the world. We are very excited to announce the four grantees for this round of funding, and have included a short description of each grantee and their project in this announcement. For a more in depth profile of each grantee and their Tool Fund projects, as well as information about how the community can help contribute to their work, follow the links in each profile to learn more. We look forward to sharing their work on developing open source tooling for reproducible research built using the Frictionless Data specifications and software.   

Stephan Max

Stephan Max is a computer scientist based in Cologne, Germany, that is passionate about making the web a fair, open, and safe place for everybody. Outside of work, Stephan has contributed to the German OKF branch as a mentor for the teenage hackathon weekends project “Jugend Hackt” (Youth Hacks). Stephan’s Tool Fund project will be to create a Data Package import/export add-on to Google Sheets.
“How can we feed spreadsheets back into a Reproducible Research pipeline? I think Data Packages is a brilliant format to model and preserve exactly that information.”

Read more about Stephan and the Google Sheets Data Package add-on here.  

Carlos Ribas and João Peschanski

João Alexandre Peschanski and Carlos Eduardo Ribas work with the Research, Innovation and Dissemination Center for Neuromathematics (RIDC NeuroMat), from the São Paulo Research Foundation. They are focused on developing open-source computational tools to advance open knowledge, open science, and scientific dissemination. They will be using the Tool Fund to work on the Neuroscience Experiments System (NES), which is an open-source tool that aims to assist neuroscience research laboratories in routine procedures for data collection.
“The advantages of the Frictionless Data approach for us is fundamentally to be able to standardize data opening and sharing within the scientific community.”
Read more about Carlos, João, and NES here.  

André Heughebaert

André Heughebaert is an IT Software Engineer at the Belgian Biodiversity Platform and is the Belgian GBIF Node manager. As an Open Data advocate, André works with GBIF and the Darwin Core standards and related Biodiversity tools to support publication and re-use of Open Data. André’s Tool Fund project will automatically convert Darwin Core Archive into Frictionless Data Packages. 
“I do hope Frictionless and GBIF communities will help me with issuing/tracking and solving incompatibilities, and also to build up new synergies.”
Read more about André and the Darwin Core Data Package project here.  

Greg Bloom and Shelby Switzer

Shelby Switzer and Greg Bloom work with Open Referral, which develops data standards and open source tools for health, human, and social services. Shelby is a long-time civic tech contributor, and Greg is the founder of the Open Referral Initiative. For the Tool Fund, they will be building out Data Package support for all their interfaces, from the open source tools that transform and validate human services data to the Human Services API Specification.
“With the Frictionless Data approach, we can more readily work with data from different sources, with varying complexity, in a simple CSV format, while preserving the ability to easily manage transformation and loading.”
Read more about Greg, Shelby, and their Tool Fund project here.  

More About Frictionless Data

The Tool Fund is part of the Frictionless Data for Reproducible Research project at Open Knowledge Foundation. This project, funded by the Sloan Foundation, applies our work in Frictionless Data to data-driven research disciplines. Frictionless Data is a set of specifications for data and metadata interoperability, accompanied by a collection of software libraries that implement these specifications, and a range of best practices for data management. The Tool Fund projects will be running through the end of 2019, and we will post updates to the projects as they progress.

Open call: become a Frictionless Data Reproducible Research Fellow

- May 8, 2019 in Featured, fellowship program, Frictionless Data, grant, Open Science

The Frictionless Data Reproducible Research Fellows Program, supported by the Sloan Foundation, aims to train graduate students, postdoctoral scholars, and early career researchers how to become champions for open, reproducible research using Frictionless Data tools and approaches in their field. Fellows will learn about Frictionless Data, including how to use Frictionless tools in their domains to improve reproducible research workflows, and how to advocate for open science. Working closely with the Frictionless Data team, Fellows will lead training workshops at conferences, host events at universities and in labs, and write blogs and other communications content. In addition to mentorship, we are providing Fellows with stipends of $5,000 to support their work and time during the nine-month long Fellowship. We welcome applications using this form from 8th May 2019 until 30th July 2019, with the Fellowship starting in the fall. We value diversity and encourage applicants from communities that are under-represented in science and technology, people of colour, women, people with disabilities, and LGBTI+ individuals.

Frictionless Data for Reproducible Research

The Fellowship is part of the Frictionless Data for Reproducible Research project at Open Knowledge International. Frictionless Data aims to reduce the friction often found when working with data, such as when data is poorly structured, incomplete, hard to find, or is archived in difficult to use formats. This project, funded by the Sloan Foundation, applies our work to data-driven research disciplines, in order to help researchers and the research community resolve data workflow issues.  At its core, Frictionless Data is a set of specifications for data and metadata interoperability, accompanied by a collection of software libraries that implement these specifications, and a range of best practices for data management. The core specification, the Data Package, is a simple and practical “container” for data and metadata. The Frictionless Data approach aims to address identified needs for improving data-driven research such as generalized, standard metadata formats, interoperable data, and open-source tooling for data validation.

Fellowship program

During the Fellowship, our team will be on hand to work closely with you as you complete the work. We will help you learn Frictionless Data tooling and software, and provide you with resources to help you create workshops and presentations. Also, we will announce Fellows on the project website and will be publishing your blogs and workshops slides within our network channels.  We will provide mentorship on how to work on an Open project, and will work with you to achieve your Fellowship goals.

How to apply

We welcome applications using this form from 8th May 2019 until 30th July 2019, with the Fellowship starting in the fall. The Fund is open to early career research individuals, such as graduate students and postdoctoral scholars, anywhere in the world, and in any scientific discipline. Successful applicants will be enthusiastic about reproducible research and open science, have some experience with communications, writing, or giving presentations, and have some technical skills (basic experience with Python, R, or Matlab for example), but do not need to be technically proficient. If you are interested, but do not have all of the qualifications, we still encourage you to apply. If you have any questions, please email the team at, ask a question on the project’s gitter channel, or check out the Fellows FAQ section. Apply soon, and share with your networks!

Data Curator – share usable open data

- March 14, 2019 in Frictionless Data, tools

Data Curator is a simple desktop editor to help describe, validate, and share usable open data.

Open data producers are increasingly focusing on improving open data so it can be easily used to create insight and drive positive change. Open data is more likely to be used if data consumers can:

  • understand the structure and quality of the data
  • understand why and how the data was collected
  • look up the meaning of codes used in the data
  • access the data in an open machine-readable format
  • know how the data is licensed and how it can be reused

Data Curator enables open data producers to define all this information, and validate the data, prior to publishing it on the Internet. The data is published as a Tabular Data Package following the Frictionless Data specification. This allows open data consumers to read the data using Frictionless Data applications and software libraries.

“We need to make it easy to manage data throughout its lifecycle and ensure it can be easily and reliably retrieved by people who want to reuse and repurpose it. We developed Data Curator to help publishers define certain characteristics to improve data and metadata quality” – Dallas Stower, Assistant Director-General, Digital Platforms and Data, Queensland Government – Project Sponsor

< p class="part" data-startline="21" data-endline="21">Data Curator allows you to create data from scratch or open an Excel or CSV file. Data Curator requires that each column of data is given a type (e.g. text, number). Data can be defined further using a format (e.g. text may be a URL or email). Constraints can be applied to data values (e.g. required, unique, minimum value, etc.). This definition process can be accelerated by using the Guess feature, that guesses the data types and formats for all columns.

Data can be validated against the column type, format and constraints to identify and correct errors. If it’s not appropriate to correct the errors, they can be added to the provenance information to help people understand why and how the data was collected and determine if it is fit for their purpose.

Data Curator screenshot

Often a set of codes used in the data is defined in another table. Data Curator lets you validate data across tables. This is really useful if you want to share a set of standard codes across different datasets or organisations.

Data Curator lets you save data as a comma, semicolon, or tab separated value file. After you’ve applied an open license to the data, you can export a data package containing the data, its description, and provenance information. The data package can then be published to the Internet. Some open data platforms support uploading, displaying, and downloading data packages. Open data consumers can then confidently access and use quality open data.

Get Started

Download Data Curator for Windows or macOS.

Learn more about Data Curator and Frictionless Data.

Who made Data Curator?

Data Curator was made possible with funding and guidance from the Queensland Government.

The project was led by Stephen Gates from the ODI Australian Network. Software development made possible by Gavin Kennedy and Matt Mulholland from the Queensland Cyber Infrastructure Foundation (QCIF).

Data Curator uses the Frictionless Data software libraries maintained by Open Knowledge International. Data Curator started life as Comma Chameleon an experiment by the Open Data Institute.

Open Knowledge Internacional anuncia fundo para ferramenta de Frictionless Data

- February 21, 2019 in Dados Abertos, dados sem atrito, Data Package, Destaque, Frictionless Data, mini-grant, Open Knowledge Internacional

A Open Knowledge Internacional está lançando o Frictionless Data Tool Fund, um esquema de mini-bolsas que oferece US$5.000 para apoiar indivíduos ou organizações no desenvolvimento de uma ferramenta open source para pesquisa ou ciência reprodutível a partir das especificações e software do projeto Frictionless Data. A organização recebe inscrições até o dia 30 de abril de 2019. O Fundo de Ferramentas faz parte do projeto Frictionless Data for Reproducible Research da Open Knowledge Internacional. Este projeto, financiado pela Fundação Sloan, aplica o trabalho em dados sem atrito a disciplinas de pesquisa orientadas por dados, a fim de facilitar fluxos de trabalho de dados reprodutíveis em contextos de pesquisa. Em sua essência, o Frictionless Data é um conjunto de especificações para interoperabilidade de dados e metadados, acompanhado por uma coleção de bibliotecas de software que implementam essas especificações e uma série de práticas recomendadas para o gerenciamento de dados. A especificação principal, o Data Package, é um “contêiner” simples e prático para dados e metadados. Com esse anúncio, estamos procurando indivíduos ou organizações de cientistas, pesquisadores, desenvolvedores ou organizadores de dados para aproveitar nossas ferramentas e código-fonte existentes de software livre para criar novas ferramentas para pesquisa reprodutível. O fundo estará aceitando submissões até o final de abril de 2019 para trabalhos que serão concluídos até o final do ano. Isso se baseia no sucesso do primeiro fundo de ferramentas em 2017, que financiou a criação de bibliotecas para especificações Frictionless Data em diversas linguagens de programação adicionais. Para o Fundo de Ferramentas deste ano, gostaríamos que a comunidade trabalhasse em projetos que possam fazer diferença para pesquisadores e cientistas. As candidaturas podem ser submetidas preenchendo este formulário até 30 de abril de 2019. A equipe da Frictionless Data notificará todos os candidatos se eles obtiveram sucesso ou não até o final de maio. Os candidatos aprovados serão então convidados para entrevistas antes da decisão final ser dada. A escolha será baseada em evidências de capacidades técnicas e também serão favorecidos os candidatos que demonstrarem interesse no uso prático das especificações de Frictionless Data. Também será dada preferência a candidatos que demonstrem interesse em trabalhar e manter essas ferramentas daqui para frente. Para mais perguntas sobre o fundo, fale diretamente com a Open Knowledge Internacional no fórum, no Gitter chat ou envie um email para Flattr this!

Announcing the Frictionless Data Tool Fund

- February 18, 2019 in Frictionless Data