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Tell us how you think we can better support Open Data Day

- November 4, 2020 in community, Events, Open Data Day, Open Data Day 2021, Open Knowledge

This year has been such an eventful year for all of us. As 2020 nears its end, here at Open Knowledge Foundation we are starting to think about Open Data Day 2021. I checked my calendar this morning – and it’s only 4 months away ! Open Data Day is such a great opportunity for the entire open data community to come together to show the benefits of open data. Last year over 300 Open Data Day events took place over 50 countries. Our (OKF’s) role is facilitation As we start to make plans, we would like you to have your say on how we (OKF) can best support Open Data Day. Do you have any ideas? Or comments? Advice? Tell us how you think we can better support Open Data Day  We want to know 
  • The good stuff. What worked at Open Data Day last year? What did you enjoy most? Which events really stood out? Did you meet someone at Open Data Day 2020 that changed the way you work for the better?
  • The bad stuff. What didn’t work last year? What could we have done differently? How would you like Open Data Day to improve? How can we achieve more impact? Are there other data tracks we should focus on?
  • How can we help each other? Open Data Day brings people together from around the world to celebrate open data. Are you interested in volunteering to help the global event happen? We are thinking of running a live online event and maybe some global competitions. And perhaps doing some fundraising for the whole open data community. Do you want to help ?
We’d love it if you can take 3 minutes to share your thoughts in our survey and tell us how you think we can improve Open Data Day.   We want to make Open Data Day 2021 better than ever, and we can only do that with your help !

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DataStories Symposium

- October 29, 2020 in community, Events, News, Open Humanities, Open Research, Talks

At the DataStories Symposium 2020 we will explore how people engage with data to create stories.

Data is represented in different ways to allow us to understand and make use of it: in numbers, in text, in visualisations, in interactive stories and other forms. Data stories are relevant to many areas of our life – they are part of the news, of how we engage with science and research, they inform our decisions and they help us explain the world.

We are getting more and more aware that data should excite as well as inform and be engaging as well as educating. Data should be presented in a transparent manner that allows different perspectives and supports us in understanding the uncertainties attached to it.

The DataStories Symposium 2020 will bring together experts from academia, industry and the third sector to discuss, generate ideas and inspire future interdisciplinary collaborations aiming to explore Human Data Interaction in relation to storytelling with data. Contributors and guests include: researchers, data journalists, data artists, computer scientists, curators, game designers, amongst others. We will have three exciting keynote speakers, interactive sessions and lightning talks to showcase ongoing work and to discuss current challenges around datastories. Topics include, but are not limited to:
  • Experiencing data through storytelling, art and games
  • Narrative practices for data stories
  • Data representations: narrative visualisations and other forms
  • Human Data Interaction
  • Making sense of data and uncertainty
  • Transparent reporting in data journalism
Currently confirmed speakers include: Anna Feigenbaum (Bournemouth University), Andrew Tatem (University of Southampton, Director of WorldPop and Flowminder), Benjamin Bach (University of Edinburgh), David Caswell (BBC News Labs), Phil Harvey (Microsoft), Caelainn Barr (The Guardian), Michele Mauri (DENSITYDESIGN LAB), Kathleen Gregory (DANS), Tom Blount (University of Southampton), Nick Holliman (Newcastle University), Marc Streit (Johannes Kepler University Linz), Ginestra Ferraro (King’s College London), Stefanie Posavec. The event is free of charge and will be held virtually on ZOOM. We are hoping for a diverse audience from a variety of backgrounds, fields and practices.

Please register here.

This blog is reposted from the symposium page on data datastories.co.uk where you will find a full schedule of talks and workshops.

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2017: A Year to Remember for OK Nepal

- January 11, 2018 in community, Community Stories, data literacy, nepal, OK Nepal, Open Data, Open Data Day

This blog has been cross-posted from the OK Nepal blog as part of our blog series of Open Knowledge Network updates.
 Best wishes for 2018 from OK Nepal to all of the Open Knowledge family and friends!! The year 2017 was one of the best years for Open Knowledge Nepal. We started our journey by registering Open Knowledge Nepal as a non-profit organization under the Nepal Government and as we start to reflect 2017, it has been “A Year to Remember”. We were able to achieve many things and we promise to continue our hard work to improve the State of Open Data in South Asia in 2018 also. Some of the key highlights of 2017 are:
  1. Organizing Open Data Day 2017
For the 5th time in a row, the Open Knowledge Nepal team led the effort of organizing International Open Data Day at Pokhara, Nepal. This year it was a collaborative effort of Kathmandu Living Labs and Open Knowledge Nepal. It was also the first official event of Open Knowledge Nepal that was held out of the Kathmandu Valley.  
  1. Launching Election Nepal Portal  
On 13th April 2017 (31st Chaitra 2073), a day before Nepalese New Year 2074, we officially released the  Election Nepal Portal in collaboration with Code for Nepal and made it open for contribution. Election Nepal is a crowdsourced citizen engagement portal that includes the Local Elections data. The portal will have three major focus areas; visualizations, datasets, and twitter feeds.
  1. Contributing to Global Open Data Index  
On May 2nd, 2017 Open Knowledge International launched the 4th edition of Global Open Data Index (GODI), a global assessment of open government data publication. Nepal has been part of this global assessment continuously for four years with lots of ups and downs. We have been leading it since the very beginning. With 20% of openness, Nepal was ranked 69 in 2016 Global Open Data Index. Also, this year we helped Open Knowledge International by coordinating for South Asia region and for the first time, we were able to get contributions from Bhutan and Afghanistan.
  1. Launching Local Boundaries   
To help journalists and researchers visualize the geographical data of Nepal in a map, we build Local Boundaries where we share the shapefile of Nepal federal structure and others. Local Boundaries brings the detailed geodata of administrative units or maps of all administrative boundaries defined by Nepal Government in an open and reusable format, free of cost. The local boundaries are available in two formats (TopoJSON and GeoJSON) and can be easily reused to map local authority data to OpenStreetMap, Google Map, Leaflet or MapBox interactively.
  1. Launching Open Data Handbook Nepali Version  
After the work of a year followed by a series of discussion and consultation, on 7 August 2017 Open Knowledge Nepal launched the first version of Nepali Open Data Handbook – An introductory guidebook used by governments and civil society organizations around the world as an introduction and blueprint for open data projects. The handbook was translated with the collaborative effort by volunteers and contributors.  Now the Nepali Handbook is available at http://handbook.oknp.org
  1. Developing Open Data Curriculum and Open Data Manual  
To organize the open data awareness program in a structured format and to generate resources which can be further use by civil society and institution, Open Knowledge Nepal prepared an Open Data Curriculum and Open Data Manual. It contains basic aspects of open data like an introduction, importance, principles, application areas as well as the technical aspects of open data like extraction, cleaning, analysis, and visualization of data. It works as a reference and a recommended guide for university students, private sectors, and civil society.
  1. Running Open Data Awareness Program
The Open Data Awareness Program was conducted in 11 colleges and 2 youth organization, reaching more than 335+ youths are first of its kind conducted in Nepal. Representatives of Open Knowledge Nepal visited 7 districts of Nepal with the Open Data Curriculum and the Open Data Manual to train youths about the importance and use of open data.
  1. Organizing Open Data Hackathon  
The Open Data Hackathon was organized with the theme “Use data to solve local problems faced by Nepali citizens” at Yalamaya Kendra (Dhokaima Cafe), Patan Dhoka on November 25th, 2017. In this hackathon, we brought students and youths from different backgrounds under the same roof to work collaboratively on different aspects of open data.
  1. Co-organizing Wiki Data-a-thon
On 30th November 2017, we co-organized a Wiki Data-a-thon with Wikimedians of Nepal at Nepal Connection, Thamel on the occasion of Global Legislative Openness Week (GLOW). During the event, we scraped the data of last CA election and pushed those data in WikiData.  
  1. Supporting Asian Regional Meeting  
On 2nd and 3rd December 2017, we supported Open Access Nepal to organize Asian Regional Meeting on Open Access, Open Education and Open Data with the theme “Open in Action: Bridging the Information Divide”. Delegates were from different countries like the USA, China, South Africa, India, Bangladesh, China, Nepal. We managed the Nepali delegates and participants.

2018 Planning

We are looking forward to a prosperous 2018, where we plan to outreach the whole of South Asia countries to improve the state of open data in the region by using focused open data training, research, and projects. For this, we will be collaborating with all possible CSOs working in Asia and will serve as an intermediary for different international organizations who want to promote or increase their activities in Asian countries. This will help the Open Knowledge Network in the long run, and we will also get opportunities to learn from each others’ successes and failures, promote each other’s activities, brainstorm collaborative projects and make the relationship between countries stronger. Besides this, we will continue also our work of data literacy like Open Data Awareness Program to make Nepalese citizens more data demanding and savvy, and launch a couple of new projects to help people to understand the available data. To be updated about our activities, please follow us at different medias:  

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An update from Open Burkina

- September 14, 2017 in community, Energy, network, Open burkina

Energy is fundamental to any development. The National Electricity Company of Burkina Faso (SONABEL) whose task is the generation, transmission, and distribution of electricity in the Burkinabè population, works hard to enable citizens to benefit from this as an important resource. However, it is clear that SONABEL hardly fulfills this mission: hardly a day goes by without a power failure in Ouagadougou. After multiple complaints, which can be found on social networks, citizens have ended up resigning and passively endure the cuts. A tweet that compares the electricity supply to light effect Among these cuts, there are load-sheddings (the deliberate shutdown of electric power in parts of a system to prevent the failure of the entire system), which are due to an insufficient capacity of SONABEL. Other cuts are due to incidents on the transmission or distribution networks. Regarding load-shedding, SONABEL produces a weekly program, but that is not legible for the citizen. It is therefore difficult for them to know if they should be concerned or not. This decreases the value of the program to the citizens. Load-shedding program as it is published by the electricity company On the other hand there is no data on cuts, such as their numbers or their locations, which make citizen advocacy to improve service delivery more difficult. For better service delivery, the Open Knowledge International local group in Burkina Faso, called Open Burkina, started the reflections since 2015. The idea is to provide citizen support to the efforts of the state. From reflection, a project with three components was born.

Mapping components

Through the mapping, the project intends to represent the load-shedding program on a map to make it more readable. A notification system can be set up to send an email or SMS to the residents of areas affected by load-shedding.

Data Collection Components

In this component, domestic sensors are designed to record cuts and current returns. The data will then be centralized and made available in open data. The sensors are designed with Arduino cards drawing on Waziup and Open IoT projects.

Notifying threshold

In the case of power cuts, a system will be provided that will notify residents of an area at the approach of the consumption threshold that can lead to a load-shedding. These users will be invited to reduce their consumption to avoid reaching the threshold. We hope that this system will help regulate the consumption of electricity and avoid outages due to power cuts. A nurse, using her phone light to receive her patients during a power cut in Ouagadougou. Photograph: Aoua Ouédraogo Our project was presented for a competitive grant for open data innovators in Africa, launched by our partner ODI in June 2017. Despite more than 80 candidate projects of all African countries, we are part of the three winning projects. Thanks to this recognition, the project will have a £ 6000 (~ 4.2 million FCFA) funding to achieve its objectives. The project is expected to last three months, and Open Burkina work closely with SONABEL, the IGB, the ANPTIC, Nos3S and the city of Ouagadougou for its success.  

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Fostering open, inclusive, and respectful participation

- August 21, 2017 in community, network, Open Knowledge, Open Knowledge international Local Groups

At Open Knowledge International we have been involved with various projects with other civil society organisations aiming for the release of public interest data, so that anyone can use it for any purpose. More importantly, we focus on putting this data to use, to help it fulfil its potential of working towards fairer and more just societies. Over the last year, we started the first phase of the project Open Data for Tax Justice, because we and our partners believe the time is right to demand for more data to be made openly available to scrutinise the activities of businesses. In an increasingly globalised world, multinational corporations have tools and techniques to their disposal to minimise their overall tax bill, and many believe that this gives them an unfair advantage over ordinary citizens. Furthermore, the extent to which these practices take place is unknown, because taxes that multinational corporations pay in all jurisdictions in which they operate are not reported publicly. By changing that we can have a proper debate about whether the rules are fair, or whether changes will need to be made to share the tax bill in a different way. For us at Open Knowledge International, this is an entry into a new domain. We are not tax experts, but instead we rely on the expertise of our partners. We are open to engaging all experts to help shape and define together how data should be made available, and how it can be put to use to work towards tax systems that can rely on more trust from their citizens. Unsurprisingly, in such a complex and continuously developing field, debates can get very heated. People are obviously very passionate about this, and being passionate open data advocates ourselves, we sympathise. However, we think it is crucial that the passion to strive for a better world should never escalate to personal insults, ad-hominem attacks, or violate basic norms in any other way. Unfortunately, this happened recently with a collaborator on a project. While they made clear they were not affiliated with Open Knowledge International, nevertheless their actions reflected very badly on the overall project and we deeply condemn their actions. Moving forward, we want to make more explicitly clear what behaviour is and is not acceptable within the context of the projects we are part of. To that end, we are publishing project participation guidelines that make clear how we define acceptable and unacceptable behaviour, and what you can do if you feel any of these guidelines are being violated. We invite your feedback on these guidelines, as it is important that these norms are shared among our community. So please let us know on our Open Knowledge forum what you think and where you think these guidelines could be improved. Furthermore, we would like to make clear what the communities we are part of, like the one around tax justice, can expect from Open Knowledge International beyond enforcing the basic behavioural norms that we set out in the guidelines linked above. Being in the business of open data, we love facts and aim to record many facts in the databases we build. However, facts can be used to reach different and sometimes even conflicting conclusions. Some partners engage heavily on social media channels like Twitter to debate conflicting interpretations, and other partners choose different channels for their work. Open Knowledge International is not, and will never be, in a position to be the arbiter on all interpretations that partners make about the data that we publish. Our expertise is in building open databases, helping put the data to use, and convening communities around the work that we do. On the subject matter of, for example, tax justice, we are more similar to those of us who are interested and care about the topic, but would rely on the debate being led by experts in the field. Where we spot abuse of the data published in databases we run, or obvious misrepresentation of the data, we will speak out. But we will not monitor or take a stance on all issues that are being debated by our partners and the wider communities around our projects. Finally, we strongly believe that the open knowledge movement is best served by open and diverse participation. We aim for the project participation guidelines to spell out our expectations and hope these will help us move towards developing more inclusive and diverse communities, where everyone who wants to participate respectfully feels welcomed to do so. Do you think these guidelines are a step in the right direction? What else do you feel we should be doing at Open Knowledge International? We look forward to hearing from you in our forum.

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Data is a Team Sport: Mentors Mediators and Mad Skills

- August 7, 2017 in advocacy, community, Data Blog, data literacy, Data Maturity, DataKind UK, Emma Prest, Event report, Fabriders, Intermediaries, mentoring, Service Organisations, Team Sport, Tin Geber

Data is a Team Sport is our open-research project exploring the data literacy eco-system and how it is evolving in the wake of post-fact, fake news and data-driven confusion.  We are producing a series of videos, blog posts and podcasts based on a series of online conversations we are having with data literacy practitioners. To subscribe to the podcast series, cut and paste the following link into your podcast manager : http://feeds.soundcloud.com/users/soundcloud:users:311573348/sounds.rss or find us in the iTunes Store and Stitcher. This episode features:
  • Emma Prest oversees the running of DataKind UK, leading the community of volunteers and building understanding about what data science can do in the charitable sector. Emma sits on the Editorial Advisory Committee at the Bureau of Investigative Journalism. She was previously a programme coordinator at Tactical Tech, providing hands-on help for activists using data in campaigns. 
  • Tin Geber has been working on the intersection of technology, art and activism for most of the last decade. In his previous role as Design and Tech Lead for The Engine Room, he developed role-playing games for human rights activists; collaborated on augmented reality transmedia projects; and helped NGOs around the world to develop creative ways to combine technology and human rights.
In this episode we take a deep dive into how to get organisations beyond ‘data literacy’ and reach ‘data maturity’, where organisations understand what is good practice on running a data project.  Some main points:
  • A red flag that indicates a data project will end in failure is when the goal is implementation of a tool as opposed to a mission-critical goal.
  • Training in itself can be helpful with hard skills, such as how to do analysis, but in terms of running data projects, it takes a lot of hand-holding and mentorship is a more effective.
  • A critical role in and organisations is people who can champion tech and data work, and they need better support in that role.
  • Fake news and data-driven confusion has meant the need for understanding good data practice is even more important.

DataKind UK’s resources:

Tin’s resources:

Resources that are inspiring Emma’s Work:

Resources that are inspiring Tin’s work:

  • DataBasic.io – A a suite of easy-to-use web tools for beginners that introduce concepts of working with data
  • Media Manipulation and Disinformation Online – Report from Data and Society on how false or misleading information is having real and negative effects on the public consumption of news.
  • Raw Graphs – The missing link between spreadsheets and data visualization

View the full online conversation:

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Data is a Team Sport: Mentors Mediators and Mad Skills

- August 7, 2017 in advocacy, community, Data Blog, data literacy, Data Maturity, DataKind UK, Emma Prest, Event report, Fabriders, Intermediaries, mentoring, Service Organisations, Team Sport, Tin Geber

Data is a Team Sport is our open-research project exploring the data literacy eco-system and how it is evolving in the wake of post-fact, fake news and data-driven confusion.  We are producing a series of videos, blog posts and podcasts based on a series of online conversations we are having with data literacy practitioners. To subscribe to the podcast series, cut and paste the following link into your podcast manager : http://feeds.soundcloud.com/users/soundcloud:users:311573348/sounds.rss or find us in the iTunes Store and Stitcher. This episode features:
  • Emma Prest oversees the running of DataKind UK, leading the community of volunteers and building understanding about what data science can do in the charitable sector. Emma sits on the Editorial Advisory Committee at the Bureau of Investigative Journalism. She was previously a programme coordinator at Tactical Tech, providing hands-on help for activists using data in campaigns. 
  • Tin Geber has been working on the intersection of technology, art and activism for most of the last decade. In his previous role as Design and Tech Lead for The Engine Room, he developed role-playing games for human rights activists; collaborated on augmented reality transmedia projects; and helped NGOs around the world to develop creative ways to combine technology and human rights.
In this episode we take a deep dive into how to get organisations beyond ‘data literacy’ and reach ‘data maturity’, where organisations understand what is good practice on running a data project.  Some main points:
  • A red flag that indicates a data project will end in failure is when the goal is implementation of a tool as opposed to a mission-critical goal.
  • Training in itself can be helpful with hard skills, such as how to do analysis, but in terms of running data projects, it takes a lot of hand-holding and mentorship is a more effective.
  • A critical role in and organisations is people who can champion tech and data work, and they need better support in that role.
  • Fake news and data-driven confusion has meant the need for understanding good data practice is even more important.

DataKind UK’s resources:

Tin’s resources:

Resources that are inspiring Emma’s Work:

Resources that are inspiring Tin’s work:

  • DataBasic.io – A a suite of easy-to-use web tools for beginners that introduce concepts of working with data
  • Media Manipulation and Disinformation Online – Report from Data and Society on how false or misleading information is having real and negative effects on the public consumption of news.
  • Raw Graphs – The missing link between spreadsheets and data visualization

View the full online conversation:

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Why MyData 2017?

- August 2, 2017 in community, network, OK Finland, Open Knowledge

This is a guest post explaining the focus of the MyData conference in Tallinn and Helsinki later this month. By a famous writing tip, you should always start texts with ‘why?’. Here we are taking that tip, and we actually find many ways to answer the big Why. So, Why MyData 2017? Did you get your data after MyData 2016 conference? No, you did not. There is lots of work to be done, and we need all the companies, governments, individuals and NGO’s on board on Aug 31-Sep 1 in Tallinn and Helsinki. When else would you meet the other over 800 friends at once? Because no. 1: The work did not stop after MyData 2016 The organizers Fing, Aalto University, Open Knowledge Finland, and Tallinn University have been working on the topic also after the conference. Fing continues their MesInfos project, started in 2012, which goes to its second phase in 2017: implementing the MyData approach in France with a long-term pilot involving big corporations, public actors, testers and a platform. Aalto University is the home base of human-centric personal data research in Finland. Many Helsinki-based pieces of research contribute their academic skills to the conference’s Academic workshops. Open Knowledge Finland, apart from giving the conference an organizational kick also fosters a project researching MyData implementation in Finnish public sector, of which we will hear in the conference too. Tallinn University, as the newest addition to the group of organizers, will host the conference day in Tallinn to set the base for and inspire MyData initiatives in Estonian companies, public sector, and academic domain. In addition to the obvious ones, multiple MyData inspired companies to continue on their own. Work continues for example in Alliance meetings, and in some cases, there are people working from the bottom up and acting as change makers in their organization. MyData 2016 went extremely well, 95 % of the feedback was positive, and the complaints were related to organizational issues like the positioning of the knives during lunch time. Total individual visitor count was 670 from 24 countries. All this was for (at the time) niche conference, organized for the first time by a team mainly of part time workers. The key to success was the people who came in offering their insights as presenters or their talents in customer care as volunteers. MyData 2017 is, even more, community driven than the year before – again a big bunch of devoted presenters, and the volunteers have been working already since March in weekly meetings, talkoot. Because no. 2: The Community did not stop existing – it started to grow MyData gained momentum in 2016 – the MyData White paper is mentioned in a ‘Staff Working Document on the free flow of data and emerging issues of the European data economy’, on pages 24-25. The white paper is also now translated from Finnish to English and Portuguese. Internationally, multiple Local Hubs have been founded this year – of which you hear more about in the Global track of the conference – and a MyData Symposium was held in Japan earlier this year. The PIMS (Personal Information Management Systems) community, who met for the fourth time during the 2016 conference, has been requesting more established community around the topic. “Building a global community and sharing ideas” is one goal of MyData 2017, and as a very concrete action, the conference organizing team and PIMS community have agreed to merge their efforts under the umbrella name of MyData. The MyData Global Network Founding Members are reviewing the Declaration of MyData Principles to be presented during MyData 2017. Next round table meeting for the MyData Global Network will be held in Aarhus in November 23.–24. 2017.   Open Knowledge Estonia was founded after last year’s conference. Since MyData was nurtured into its current form inside the Open Knowledge movement, where Open Knowledge Finland still plays the biggest role, MyData people feel very close to other Open Knowledge chapters. See for yourself, how nicely Rufus Pollock explains in this video from MyData 2016 how Open Data and MyData are related. Because no. 3: Estonians are estonishing “Why Tallinn then?” is a question we hear a lot. The closeness of the two cities, also sometimes jointly called Talsinki, makes the choice very natural to the Finns and Estonians, but might seem weird looking from outside. Estonia holds the Presidency of the Council of the EU in the second part of 2017. In an e-Estonia, home of the infamous e-residency, MyData fits naturally in the pool of ideas to be tossed around during that period. Now, having the ‘Free movement of data’ as the fifth freedom within the European Union, in addition to goods, capital, service, and people, has been suggested by Estonians, and MyData way of thinking is a crucial part to advance that. Estonia and Finland co-operate in developing X-road, a data exchange layer for national information systems, between the two countries. In 2017, the Nordic Institute for Interoperability (NIIS) was founded to advance the X-road in other countries as well. Finnish population registry center and their digitalized services esuomi.fi is the main partner of the conference in 2017 Estonia and Finland both as small countries are very good places to test new ideas. Both in Helsinki and Tallinn, we now have ongoing ‘MyData Alliance’ meetups for companies and public organizations who want to advance MyData in their organizations. A goal of MyData in general, “we want to make Finland the Moomin Valley of personal data” will be expanded to “we want to make Finland and Estonia the Moomin Valley of personal data”.  

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Data is a Team Sport: One on One with Heather Leson

- July 19, 2017 in community, Data Blog, data literacy, data protection, Event report, Heather Leson, Humanitarian Organisations, IFRC, research, Team Sport

Data is a Team Sport is our open-research project exploring the data literacy eco-system and how it is evolving in the wake of post-fact, fake news and data-driven confusion.  We are producing a series of videos, blog posts and podcasts based on a series of online conversations we are having with data literacy practitioners. To subscribe to the podcast series, cut and paste the following link into your podcast manager : http://feeds.soundcloud.com/users/soundcloud:users:311573348/sounds.rss or find us in the iTunes Store and Stitcher. This episode features a one on one conversation with Heather Leson, the Data Literacy Lead at International Federation of Red Cross and Red Crescent Societies. As a technologist, she strengthens community collaboration via humanitarian technologies and social entrepreneurship. She builds partnerships, curates digital spaces, fosters volunteer engagement and delivers training while inspiring systems for co-creation with maps, code and data. At the International Federation of Red Cross Red Crescent, her mandate includes global data advocacy, data literacy and data training programs in partnership with the 190 national societies and the 13 million volunteers. She is a past Board Member at the Humanitarian OpenStreetMap Team (4 years), Peace Geeks (1 year), and an Advisor for MapSwipe – using gamification systems to crowdsource disaster-based satellite imagery. Previously, she worked as Social Innovation Program Manager, Qatar Computing Research Institute (Qatar Foundation) Director of Community Engagement, Ushahidi, and Community Director, Open Knowledge (School of Data).

Main Points from the Conversation:

  • Data protection is the default setting for humanitarian organisations collecting data.
  • She’s found its critical to focus on people and what they are trying to accomplish, as opposed to focusing on tools.
  • She’s added ‘socialisation’ as the beginning step to the data pipeline.

Heather’s Resources

Blogs/websites Heather’s work The full online conversation:
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Data is a Team Sport: One on One with Daniela Lepiz

- July 3, 2017 in community, Data Blog, Data Journalism, data literacy, Event report, Fabriders, Nigeria, research, Team Sport, West Africa

Data is a Team Sport is our open-research project exploring the data literacy eco-system and how it is evolving in the wake of post-fact, fake news and data-driven confusion.  We are producing a series of videos, blog posts and podcasts based on a series of online conversations we are having with data literacy practitioners. To subscribe to the podcast series, cut and paste the following link into your podcast manager : http://feeds.soundcloud.com/users/soundcloud:users:311573348/sounds.rss or find us in the iTunes Store and Stitcher. This episode features a one on one episode with Daniela Lepiz, a Costa Rican data journalist and trainer, who is currently the Investigation Editor for CENOZO, a West African Investigative Journalism Project that aims to promote and support cross border data investigation and open data in the region. She has a masters degree in data journalism from the Rey Juan Carlos University in Madrid, Spain. Previously involved with OpenUP South Africa working with journalists to produce data driven stories.  Daniela is also a trainer for the Tanzania Media Foundation and has been involved in many other projects with South African Media, La Nacion in Costa Rica and other international organisations.

Notes from the conversation

Daniela spoke to us from Burkina Faso and reflected on the role of journalism and particularly data-driven journalism in functioning democracies.  The project she is working on empowering journalists working cross-border in western Africa to utilise data to expose corruption and violation of human rights.  To identify journalists to participate in the project, they have looked for individuals who are experienced, passionate and curious. The project engages existing media houses, such as Premium Times in Nigeria, to assure that there are places for their stories to appear. Important points Daniela raises:
  • Media is continually evolving and learning to evolve and Daniela can see that data literacy will be a required proficiency in the next five years.
  • The biggest barrier to achieving open-data in government are government officials who resist transparency
  • There is a real fear from journalists of having to be proficient in maths when they are considering improve their skills to produce data-driven stories.  They often fail to realise that its about working with others that have skills on statistics and data analysis.
  • Trust in media has declined in such a big way and it means journalists have to work that much harder, particularly in labelling things as opinion or being biased.

Resources she finds inspiring

Her blogs posts

The full online conversation:

Daniela’s bookmarks!

These are the resources she uses the most often. .Rddj – Resources for doing data journalism with RComparing Columns in Google Refine | OUseful.Info, the blog…Journalist datastores: where can you find them? A list. | Simon RogersAidInfoPlus – Mastering Aid Information for Change

Data skills

Mapping tip: how to convert and filter KML into a list with Open Refine | Online Journalism Blog
Mapbox + Weather Data
Encryption, Journalism and Free Expression | The Mozilla Blog
Data cleaning with Regular Expressions (NICAR) – Google Docs
NICAR 2016 Links and Tips – Google Docs
Teaching Data Journalism: A Survey & Model Curricula | Global Investigative Journalism Network
Data bulletproofing tips for NICAR 2016 – Google Docs
Using the command line tabula extractor tool · tabulapdf/tabula-extractor Wiki · GitHub
Talend Downloads

Github

Git Concepts – SmartGit (Latest/Preview) – Confluence
GitHub For Beginners: Don’t Get Scared, Get Started – ReadWrite
Kartograph.org
LittleSis – Profiling the powers that be

Tableau customized polygons

How can I create a filled map with custom polygons in Tableau given point data? – Stack Overflow
Using Shape Files for Boundaries in Tableau | The Last Data Bender
How to make custom Tableau maps
How to map geographies in Tableau that are not built in to the product (e.g. UK postcodes, sales areas) – Dabbling with Data
Alteryx Analytics Gallery | Public Gallery
TableauShapeMaker – Adding custom shapes to Tableau maps | Vishful thinking…
Creating Tableau Polygons from ArcGIS Shapefiles | Tableau Software
Creating Polygon-Shaded Maps | Tableau Software
Tool to Convert ArcGIS Shapefiles into Tableau Polygons | Tableau and Behold!
Polygon Maps | Tableau Software
Modeling April 2016
5 Tips for Making Your Tableau Public Viz Go Viral | Tableau Public
Google News Lab
HTML and CSS
Open Semantic Search: Your own search engine for documents, images, tables, files, intranet & news
Spatial Data Download | DIVA-GIS
Linkurious – Linkurious – Understand the connections in your data
Apache Solr –
Apache Tika – Apache Tika
Neo4j Graph Database: Unlock the Value of Data Relationships
SQL: Table Transformation | Codecademy
dc.js – Dimensional Charting Javascript Library
The People and the Technology Behind the Panama Papers | Global Investigative Journalism Network
How to convert XLS file to CSV in Command Line [Linux]
Intro to SQL (IRE 2016) · GitHub
Malik Singleton – SELECT needle FROM haystack;
Investigative Reporters and Editors | Tipsheets and links
Investigative Reporters and Editors | Tipsheets and Links

SQL_PYTHON

More data

2016-NICAR-Adv-SQL/SQL_queries.md at master · taggartk/2016-NICAR-Adv-SQL · GitHub
advanced-sql-nicar15/stats-functions.sql at master · anthonydb/advanced-sql-nicar15 · GitHub
2016-NICAR-Adv-SQL/SQL_queries.md at master · taggartk/2016-NICAR-Adv-SQL · GitHub
Malik Singleton – SELECT needle FROM haystack;
Statistical functions in MySQL • Code is poetry
Data Analysis Using SQL and Excel – Gordon S. Linoff – Google Books
Using PROC SQL to Find Uncommon Observations Between 2 Data Sets in SAS | The Chemical Statistician
mysql – Query to compare two subsets of data from the same table? – Database Administrators Stack Exchange
sql – How to add “weights” to a MySQL table and select random values according to these? – Stack Overflow
sql – Fast mysql random weighted choice on big database – Stack Overflow
php – MySQL: Select Random Entry, but Weight Towards Certain Entries – Stack Overflow
MySQL Moving average
Calculating descriptive statistics in MySQL | codediesel
Problem-Solving using Graph Traversals: Searching, Scoring, Ranking, …
R, MySQL, LM and quantreg
26318_AllText_Print.pdf
ddi-documentation-english-572 (1).pdf
Categorical Data — pandas 0.18.1+143.g3b75e03.dirty documentation
python – Loading STATA file: Categorial values must be unique – Stack Overflow
Using the CSV module in Python
14.1. csv — CSV File Reading and Writing — Python 3.5.2rc1 documentation
csvsql — csvkit 0.9.1 documentation
weight samples with python – Google Search
python – Weighted choice short and simple – Stack Overflow
7.1. string — Common string operations — Python v2.6.9 documentation
Introduction to Data Analysis with Python | Lynda.com
A Complete Tutorial to Learn Data Science with Python from Scratch
GitHub – fonnesbeck/statistical-analysis-python-tutorial: Statistical Data Analysis in Python
Verifying the email – Email Checker
A little tour of aleph, a data search tool for reporters – pudo.org (Friedrich Lindenberg)
Welcome – Investigative Dashboard Search
Investigative Dashboard
Working with CSVs on the Command Line
FiveThirtyEight’s data journalism workflow with R | useR! 2016 international R User conference | Channel 9
Six issue when installing package · Issue #3165 · pypa/pip · GitHub
python – Installing pip on Mac OS X – Stack Overflow
Source – Journalism Code, Context & Community – A project by Knight-Mozilla OpenNews
Introducing Kaggle’s Open Data Platform
NASA just made all the scientific research it funds available for free – ScienceAlert
District council code list | Statistics South Africa
How-to: Index Scanned PDFs at Scale Using Fewer Than 50 Lines of Code – Cloudera Engineering Blog
GitHub – gavinr/geojson-csv-join: A script to take a GeoJSON file, and JOIN data onto that file from a CSV file.
7 command-line tools for data science
Python Basics: Lists, Dictionaries, & Booleans
Jupyter Notebook Viewer

PYTHON FOR JOURNALISTS

New folder

Reshaping and Pivot Tables — pandas 0.18.1 documentation
Reshaping in Pandas – Pivot, Pivot-Table, Stack and Unstack explained with Pictures – Nikolay Grozev
Pandas Pivot-Table Example – YouTube
pandas.pivot_table — pandas 0.18.1 documentation
Pandas Pivot Table Explained – Practical Business Python
Pivot Tables In Pandas – Python
Pandas .groupby(), Lambda Functions, & Pivot Tables
Counting Values & Basic Plotting in Python
Creating Pandas DataFrames & Selecting Data
Filtering Data in Python with Boolean Indexes
Deriving New Columns & Defining Python Functions
Python Histograms, Box Plots, & Distributions
Resources for Further Learning
Python Methods, Functions, & Libraries
Python Basics: Lists, Dictionaries, & Booleans
Real-world Python for data-crunching journalists | TrendCT
Cookbook — agate 1.4.0 documentation
3. Power tools — csvkit 0.9.1 documentation
Tutorial — csvkit 0.9.1 documentation
4. Going elsewhere with your data — csvkit 0.9.1 documentation
2. Examining the data — csvkit 0.9.1 documentation
A Complete Tutorial to Learn Data Science with Python from Scratch
For Journalism
ProPublica Summer Data Institute
Percentage of vote change | CARTO
Data Science | Coursera
Data journalism training materials
Pythex: a Python regular expression editor
A secure whistleblowing platform for African media | afriLEAKS
PDFUnlock! – Unlock secured PDF files online for free.
The digital journalist’s toolbox: mapping | IJNet
Bulletproof Data Journalism – Course – LEARNO
Transpose columns across rows (grefine 2.5) ~ RefinePro Knowledge Base for OpenRefine
Installing NLTK — NLTK 3.0 documentation
1. Language Processing and Python
Visualize any Text as a Network – Textexture
10 tools that can help data journalists do better work, be more efficient – Poynter
Workshop Attendance
Clustering In Depth · OpenRefine/OpenRefine Wiki · GitHub
Regression analysis using Python
DataBasic.io
DataBasic.io
R for Every Survey Analysis – YouTube
Git – Book
NICAR17 Slides, Links & Tutorials #NICAR17 // Ricochet by Chrys Wu
Register for Anonymous VPN Services | PIA Services
The Bureau of Investigative Journalism
dtSearch – Text Retrieval / Full Text Search Engine
Investigation, Cybersecurity, Information Governance and eDiscovery Software | Nuix
How we built the Offshore Leaks Database | International Consortium of Investigative Journalists
Liz Telecom/Azimmo – Google Search
First Python Notebook — First Python Notebook 1.0 documentation
GitHub – JasonKessler/scattertext: Beautiful visualizations of how language differs among document types
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