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An update from Open Burkina

Teg-wende Idriss TINTO - 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.  

Fostering open, inclusive, and respectful participation

Sander van der Waal - 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.

Data is a Team Sport: Mentors Mediators and Mad Skills

Dirk Slater - 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

Dirk Slater - 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?

Open Knowledge Finland - 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”.  

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

Dirk Slater - 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

Dirk Slater - 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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New Open Knowledge Network chapter in Nepal

Oscar Montiel - June 26, 2017 in community, OK Nepal

We are happy to announce that this month a new Chapter at the Open Knowledge Network is being launched officially: welcome Open Knowledge Nepal in this new stage! Since February 2013, Open Knowledge Nepal has been involved in research, advocacy, training, organizing meetups and hackathons, and developing tools related to Open Data, Open Government Data, Open Source, Open Education, Open Access, Open Development, Open Research and others. The organization also helps and supports Open Data entrepreneurs and startups to solve different kinds of data related problems they are facing through counseling, training and by developing tools for them. Nikesh Balami, CEO of Open Knowledge Nepal tells us: from random groups of people to build a core team of diverse backgrounds, starting from messy thoughts to realistic plans and long-term goals, we have become more organized and robust. [We] Identified ourselves as a positive influence towards the community and nation. After being incorporated as a Chapter, we now can reach out extensively among interested groups and also expect to create impact in a most structured way in national and international level. Our main goal is to establish ourselves as a well-known open data organization/network in Nepal. Pavel Richter, CEO of Open Knowledge International, underscored the importance of chapters: “Most of the work to improve people’s lives is and has to happen in local communities and on a national level. It is therefore hugely important to build a lasting structure for this work, and I am particularly happy to welcome Nepal as a Chapter of the growing Open Knowledge Family.” Chapters are the Open Knowledge Network’s most developed form, they have legal independence from the organization and are affiliated by a Memorandum of Understanding. For a full list of our current chapters, see here and to learn more about their structure visit the network guidelines. The Open Knowledge global network now includes groups in over 40 countries. Twelve of these groups have now affiliated as chapters. This network of dedicated civic activists, openness specialists, and data diggers are at the heart of the Open Knowledge International mission, and at the forefront of the movement for Open. Check out the work OK Nepal does at oknp.org

Announcing our new member: ‘Caribbean School of Data’

Meg Foulkes - June 21, 2017 in announcement, community

Today we’re delighted to welcome a new organisational member to our network: the Caribbean Open Institute! They will carry the Caribbean School of Data Initiative. The new Caribbean initiative is led by Maurice McNaughton who coordinates the Caribbean Open Institute, as the regional node for the Open Data for Development network activities in the Caribbean. The COI coalition of partner organisations and individuals conduct regional open data research, advocacy, and capacity-building activities such as the Global Open Data Index and the Open Data Barometer. The new “Caribbean School of Data” will be hosted at the Mona School of Business & Management, UWI and affiliate institutions are planned for other countries across the Caribbean (including Trinidad & Tobago,  Haiti, Cuba and Guyana). Already in the group’s pipeline is a virtual incubation model to encourage and facilitate data-driven entrepreneurial startups as well as a project to build a Caribbean data competency map, to identify and make searchable and accessible, individual and institutional clusters of data skills, knowledge and capabilities in the region. School of Data is already working with the Caribbean Open Institute on a Data literacy project in Haïti called “Going Global: Digital Jobs and Gender” for which we have recently recruited two Fellows. Welcome, Caribbean School of Data!   About School of Data members School of Data’s organisational members are legally independent groups, affiliated formally through a memorandum of understanding. Our members are groups whose mission and activities are aligned with ours and with whom we plan to collaborate in this data literacy work. Caribbean School of Data  is our fourteenth member!   Flattr this!

Data is a Team Sport: Data-Driven Journalism

Dirk Slater - June 20, 2017 in Anti-corruption, community, Data Blog, data driven journalism, Data Journalism, data literacy, Event report, Fabriders, Gender Data, research, Rights

Our podcast series that explores the ever evolving data literacy eco-system. Cut and paste this link into your podcast app to subscribe: http://feeds.soundcloud.com/users/soundcloud:users:311573348/sounds.rss or find us in the iTunes Store and Stitcher. In this episode we speak with two veteran data literacy practitioners who have been involved with developing data-driven journalism teams. Our guests:
  • Eva Constantaras is a data journalist specialized in building data journalism teams in developing countries. These teams that have reported from across Latin America, Asia and East Africa on topics ranging from displacement and kidnapping by organized crime networks to extractive industries and public health. As a Google Data Journalism Scholar and a Fulbright Fellow, she developed a course for investigative and data journalism in high-risk environments.
  • Natalia Mazotte is Program Manager of School of Data in Brazil and founder and co-director of the digital magazine Gender and Number. She has a Master Degree in Communications and Culture from the Federal University of Rio de Janeiro and a specialization in Digital Strategy from Pompeu Fabra University (Barcelona/Spain). Natalia has been teaching data skills in different universities and newsrooms around Brazil. She also works as instructor in online courses in the Knight Center for Journalism in the Americas, a project from Texas University, and writes for international publications such as SGI News, Bertelsmann-Stiftung, Euroactiv and Nieman Lab.

Notes from this episode

They both describe the lessons learned in getting journalists to use data that can drive social change. For Eva, getting journalists to work harder and just reporting that corruption exists is not enough, while Natalia, talks about how they use data on gender to drive debate and discussion around equality. What is critical for democracy is the existence of good journalism and this includes data-driven journalism that uncovers facts and gets at the root causes.

Gaps in the Data Literacy EcoSystem:

Natalia points out that corporations and government has the power because they are data-literate and can use it effectively, while people in low-income communities, such as favela’s really suffer because they are at the mercy of what story gets told by looking at the ‘official’ data. Eva feels that there has been too much emphasis on short-term and quick solutions from individuals who have put a lot of money in making sure that data is ready and accessible.  Donors need to support more long-term efforts and engagement around data-literacy.

Adjusting to a ‘post-fact’ world means:

Western journalists have spent too much time focusing on reporting on polling data rather than reporting on policies and it’s important for newer journalists to understand why that was problematic. In Brazil, the main stream media is focusing on ‘what’s happened’ while independent media is focusing on ‘why it’s happened’ and this means the media landscape is changing.

They also talked about:

  • Ethics and the responsibility inherent in gathering and storing data, along with the grey areas around privacy.
  • How to get media outlets to value data-driven journalism by getting them to understand that people are increasingly getting their ‘breaking news’ from social media, so they need to look at providing more in-depth stories.

They wanted to plug:

Readings/Resources they find inspiring for their work.

Resources contributed from the participants:

View the online conversation in full:

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