March 24 2022 GM

Glitter Meetups What are Glitter Meetups Notes from Past Glitter Meetups Virtual Events Calendar Join the IFF Mattermost

Glitter Meetup is the weekly town hall of the Internet Freedom community at the IFF Square on the IFF Mattermost, at 9am EST / 1pm UTC. Do you need an invite? Learn how to get one here.

Date: Thursday, March 24th

Time: 9am EDT / 1pm UTC

Who: Laureen Van Breen, Tom Howie, Lucia Ixtacuy

Where: As a guest of the Glitter Meetup on IFF Mattermost Square Channel.

• Don't have an account to the IFF Mattermost? you can request one following the directions here.

The WikiRate project

At WikiRate, we have developed an open data platform that allows anyone to systematically gather, analyze and report publicly available information on corporate ESG practices. By bringing this information together in one place making it accessible, comparable, and free for all, we aim to provide society with the tools and evidence it needs to help and encourage companies to respond to the world's social and environmental challenges. To date, WikiRate.org is the largest open-source registry of ESG data, with more than 2.5 million data points for over 100,000 companies.

During the session, we will highlight how WikiRate is used as a tool to assess companies' disclosed policies and practices, including those related to digital rights.

• Laureen van Breen comes from the Netherlands and joined the WikiRate team in Berlin in 2016. She leads the organization, overseeing its operations, developing and implementing its strategy, setting up organizational structures, advocating for open data practices, and securing funding that enables the organization to flourish.

• Tom Howie joined the WikiRate team in Berlin in 2021 as Content and Communications Manager. Working closely with all teams, he shapes and leads communications that show WikiRate’s unique position at the intersection of research, open data, innovation, and collective action. He comes from the United Kingdom.

• Lucía Ixtacuy joined WikiRate in 2018 as Project Manager. Currently, she is maintaining and growing our academic engagements and developing a community of WikiRate contributors. She is responsible for improving data quality in public data sets on WikiRate. Lucía comes from Mexico and lives in Berlin.

Notes

This week's guests are @lucia and @tomwikirate, from The WikiRate project, an open data platform that allows anyone to systematically gather, analyze and report publicly available information on corporate ESG practices. Environmental, social, and corporate governance (ESG) is an approach to evaluating the extent to which a corporation works on behalf of social goals that go beyond the role of a corporation to maximize profits.

WikiRate is an independent non-profit initiative, and we have built an open source and open platform for aggregating and analyzing company data. We are also a wiki in the sense that anyone with an interest in creating or using company data can contribute and view data on companies' environmental, social, and governance performance, as well as supply chain transparency disclosures, and companies progress toward the Sustainable Development Goals. We are based in Berlin, Germany, but run projects globally. You can find more about it here.

Could you explain what Machine Readability Data is?

• In its simplest form, a computer program could "read" a pdf, extract the relevant data and transfer and transform the data to another digital format that is easier to analyze.
• A relatable example to most is when something is definitely NOT machine readable:
  • Imagine you have a pdf document and you want to copy a couple of sentences via ctrl+c / v. You go to highlight the section and the whole page lights up.
  • Your heart sinks as you realize you'll have to manually transfer the info.
• That's machine unreadability in a nutshell. The document hasn't been prepared in a way that makes it easy to transfer and manipulate the data.
• Obviously when it comes to company reporting it's a bit more complex. But the issue is the same, it's about saving time and being able to analyze at scale effectively and efficiently.
• We can do that if companies report in a standardized way.

Could you please expand on the UK Modern Slavery Act standard and how do you use it in Wikirate?

• The UK Modern Slavery Act (MSA) is a piece of legislation enacted by the UK government in 2015. It mandates that companies that carry out business operations in any part of the United Kingdom, and have a turnover GBP 36 million per annum are required to report on their actions to combat modern slavery in their supply chains.
• In 2016, we established a partnership with Walk Free to develop metrics based on the Act to document how well companies report to the requirements of the Act. To carry out the assessment, each year we team up with universities and students around the world.
• In this sense, it is a project that collects/crowed-researches data!

​​Could you tell us a bit about your methodologies regarding data sets? And you help folks locate that data as well? Ie, do you have data sets available to folks through your project?

• Well, there is not a methodology as such. Data Sets are rather a tool to help users to structure information on WikiRate by combining Companies and Metrics associated with a particular Topic or theme. So, users decide what information they want to include in a Data Set .
• In that sense, you decide which Companies, Metrics and Years you want in your Data Set
• The Metrics and Companies hosted on WikiRate can be browsed directly on the platform. For instance here
• It's a bit hard to wrap your head around at first, regarding how our data is arranged.
• But the main thing is that it is extremely flexible, users have the ultimate decision about what they want to measure, and how they want to then compare that data.
• What separates WikiRate from a benchmarking site is that the analysis (methodology) is always relative to other data, and not dependent on a third party defining "good" or "bad"

What is the License that WikiRate publishes the data sets under? Are different data sets governed by different licenses?

• Our data model is available under Creative Commons - Attribution-Share Alike 4.0 International License
• This includes, without being necessarily an exhaustive list, data sheets (any content related to metrics such as metric names, methodology etc.), wiki content (such as reviews and overviews), and metric values
• Also, the whole of WikiRate is creative commons, so theoretically someone could copy our whole site and start doing what we're doing!

Does WikiRate also scrape data itself?

• We do! We have a Data Engineer on our team that help us get as much data as possible when we have sources with structured data

When you say in your intro video: "When answers to key questions are unavailable, we can urge companies to provide them", what do you mean by that? What kind of actions do you mean?

• Lucia says that they are hoping that as more information is available via their platform, all stakeholders can use data for advocate for more transparency and better disclosures that at the end, will result on companies being accountable for their different impacts
• So for instance, activists, journalist, academics, consumers they can all use this data in different ways (research, campaigns, reports)
• Tom adds that that's a really good question, and speaks to the complexity of how the world works. At its simplest we can see from the data set which companies are, and which aren't providing data.
• As WikiRate has grown, it have partnered with organizations like Walk Free and the Business and Human Rights Resource Centre, to help produce reports and online resources on modern slavery reporting, fashion transparency, and tea transparency. With their community, tools, and data, those organizations can tell the story of the data and what is missing from it. They advocate for what needs to be reported. Of course this is a little more complex than just "asking" but that's also about the complexity of the world.

Which indicators do you use to assess a corporation’s performance regarding climate?

• We have an open data project that is collecting environmental impact data on the 100 most greenhouse gas emitting companies in the world
• That project focuses on Emissions Data, some of our main indicators are:
  • Amount of greenhouse gas (GHG) emissions (in tonnes of CO2 equivalent) that the organization is directly responsible for
  • How much reduction in Greenhouse Gas (GHG) emissions has the company achieved as a direct result of initiatives to reduce emissions (in metric tons of CO2 equivalent)
  • Whether the organization expressed its support for the TCFD (Task Force on Climate-related Financial Disclosures) recommendations
  • Whether the company set a science based target commitment and if so, what is the status of that commitment
• The process would be:
  • A user would start by asking the question: How many carbon tonnes of greenhouse gasses per year does a company produce?
  • Then a WikiRater would go and look for the answer for say Facebook, in the year 2021. Probably in a company report.
  • Companies are publishing a lot of data regarding their performance, it's just that it's sometimes tucked away in a shiny pdf.
  • Machine readability of data is a massive issue right now, something we would love to see the EU take more action on when companies report.
  • Although excel tables might not look the most attractive they have their uses!
• Obviously we can look for other sources other than company reports, but it's a good place to start.

Can you tell us about your experience and strategies towards developing a community of WikiRate contributors? What have been some of the challenges you've faced with engagement?

• It is challenging. Our platform has been improving year on year. The first years we focused mainly on getting data onto the platform and perfecting its usability. Our main wiki community comes from our University partnerships and individuals who approach us, so, we are still far from having an active community such as yours, but it is our dream!

Do any of the data sets (or work) focus on surveillance and censorship?

• We have onboarded data of the Ranking Digital Rights that have evaluated 24 of the world's most powerful internet, mobile and telecommunications companies on their disclosed commitments and policies affecting freedom of expression and privacy of internet users across the world. The data on our platforms looks like this.
• We would be happy to hear insights from this community, what Metrics would be of interest for you, which companies you'd like to research and so on
• Definitely recommend looking into OONI's open data

Your audience is not just UK companies, but really anyone that is trying to do ESG work anywhere, correct? Also, any insight into the tech sector? Its so influential in our space, it would be nice to hear a bit about that.

• Companies are worldwide, that's also a tricky point when it comes to company reporting. Company structures make it hard to identify who is operating/responsible where. We do quite a bit of work analyzing supply chains too
• The tech sector would be really interesting to investigate further. I am not aware any current project with WikiRate, but i'm sure we'd be happy to talk about this with you more