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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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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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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:

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Data is a Team Sport, Episode 1: Enabling Learners

Dirk Slater - June 6, 2017 in community, data literacy, Event report, Fabriders, Online Conversation Notes, Online Curriculum, podcast, research

School of Data’s podcast series exploring the ever evolving data literacy eco-system.  Upcoming episodes will focus on specific areas within the eco-system such as Investigative Journalism, Civil Society, Government and Academia. In this episode we speak with two veteran data literacy practitioners who have been involved with directly engaging learners to get beyond spreadsheets to build confidence and take agency in their own learning. Our guests:
  • Rahul Bhargava is a researcher and technologist specializing in civic technology and data literacy. He creates interactive websites used by hundreds of thousands, playful educational experiences across the globe, and award-winning visualizations for museum settings. As a research scientist at the MIT Center for Civic Media, Rahul leads technical development on projects ranging from interfaces for quantitative news analysis to platforms for crowd-sourced sensing.
  • Lucy Chambers initially embarked on a career as a journalist, she took a few turns which lead to a career at Open Knowledge teaching journalists how and why to work with data. She was one of the editors of the Data Journalism Handbook. She later lead the highly successful School of Data programme which extended technical training to non-profit organisations. Lately, she has focussed on delivery of software projects as a product manager. Most recently, she has been working in West Africa on health related software.

Notes from the first episode

Rahul described methods to data novices to think more creatively by drawing and using a gallery of their artwork to build confidence to think more critically. He says that this experience is what led to the creation of databasic.io, a website designed specifically to engage learners. Lucy tells of School of Data’s initial struggles with setting up a one-size fits all online curriculum and how they learned through focus groups and testing that they needed to focus on people, rather than a tool-based approach. They then turned to developing a fellowship programme which is very much at the core of the School of Data network. Both of our guests had strong opinions about building data literacy culture in organisations. A common mistake is made by letting the IT Department provide data training.  Organisations often produce unhelpful data metrics and dashboards that don’t actually help staff get a full picture of progress.

Gaps in the Data Literacy EcoSystem:

  • Toolbuilders not understanding and subsequently not building for learners.
  • NGO’s not testing out data driven messages with their audiences before they release them.

Adjusting to a ‘post-fact’ world means:

  • We need to make sure that people understand that data not necessarily truth and that it is often used as rhetoric and that it carries bias. Data sets should have a biography attached.
  • Narrative wins, so the data presentation methods where the audience is bombarded with facts and figures just doesn’t work. We have to spend more time pulling out the compelling narrative from the data.

They wanted to plug:

  • Rahul is building a co-hort around further development of databasics.io. Ping him via twitter to get more information on that.
  • Lucy’s blog is Tech to Human and she writes about her work and what she’s learning. She is working on a project for MySociety called EveryPolitician and writing about it on Medium.

Readings/Resources they find inspiring for data literacy work.

View the full online conversations:

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