open-data | Eviota

Big Data for All: Building Collaborative Data Observatories

Thu, 03 Nov 2022 17:30:00 +0000

Reprex’s co-founder, Daniel Antal talked in the Eindhoven Innovation Café about these issues. You can watch the recorded version of the the livestream that starts at 5 minutes and 22 seconds:

This is a past event. Check out our forthcoming events or write to Daniel Antal or to antaldaniel. Or send an email.

The event invitation text and links

Big data and AI creates inequalities. It puts historically marginalized people, like ethnic minorities, and womxn, at a disadvantage. Because AI and checking on AI require plenty of data, usually only giant corporations, the wealthiest governments, and university entities can make it work for them. Reprex is a Hague-based, international startup that wants to impact various sustainable development goals by enabling smaller organizations to join their smaller datasets, use open data, create linked available data, and collaboratively make a change.

Reprex is a finalist for the Hague Innovation Award for impact startup (please 🙏, vote for us!). Daniel Antal, one of the co-founders, will talk about their approach to building an international coalition of music organizations to pool data and challenge data monopolies using organizational techniques, a collaboration ethos, and data from the open-source developer world.

Using the example of independent music creators, who often find themselves in a position where it is more expensive to claim their money from global platforms, he will talk about how to reduce inequalities in the world of big data and AI with collaboration on web 3.0. In the Q&A he will take questions on how to apply their know-how, and generally linked open data to other art+tech or creative segments or problems for which everybody is too small, like meeting the Paris Accord greenhouse gas targets bit by bit, small company by small company.

In the Q&A, we can discuss many things

How can Reprex help an individual creator in music, or in fashion and design, or any other area?
What sort of help it can give to researchers, research institutes, specialist consultancies, law firms, and other knowledge-based actors?

What sort of partners is Reprex looking for in Eindhoven?

Check out our projects

Digital Music Observatory and Listen Local
Cultural & Creative Sectors and Industries Observatory and short call for potential partners.
Green Deal Data Observatory and simple, connected, financial and sustainability reporting for creative enterprises and others

Reprex: the impact startup

Check out our accomplishments since the foundation in 2020

Crunchconf: Open Data, New Gold Without the Rush

Fri, 08 Oct 2021 10:10:00 +0000

Every year, the EU announces that billions and billions of data are now “open” again, but this is not gold. At least not in the form of nicely minted gold coins, but in gold dust and nuggets found in the muddy banks of chilly rivers. There is no rush for it, because panning out its value requires a lot of hours of hard work. Our goal is to automate this work to make open data usable at scale, even in trustworthy AI solutions.

Summary

In his presentation, Daniel compared the current state of open data (including governmental open data and scientific open data) to a thrift store. You can often find bargains, or historical data that would be impossible to source from data vendors, but on a strictly as-is basis, without a catalogue, service, or guarantee. Therefore, working with open data requires a careful reprocessing, validation, and in many cases, frequent re-validation. Open data is often over-estimated: it is never a finished product, often it cannot even be downloaded, therefore it requires further investment to make it valuable. However, because most open data arrives from the governmental sector, you can tap into information sources where no market alternative exists. Open data in some cases may be a cheaper substitute to market vendors, but often it is an exclusive source of information that do not have any market vendors.

Sisyphus was punished by being forced to roll an immense boulder up a hill only for it to roll down every time it neared the top, repeating this action for eternity. This is the price that project managers and analysts pay for the inadequate documentation of their data assets.

The practices related to the exploitation of open data are not only relevant in an open data context: these are good data ingestion and procurement practices for any third party data, and in large organizations, for any cross-departmental data. (See the blogpost: The Data Sisyphus.)
Case Study: Belgian Drought/Flood Risk Awareness, Financial Capacity & Hydrology a complex integration of various open data sources.

In the second part of the presentation, Daniel talked about our modern data observatory concept. We have reviewed about 80 functioning and already defunct international data collection programs. Data observatories, like Copernicus’ Observatory, are permanent infrastructure to record various domain-specific data, such as alternative fuel information, information on homelessness, or on the European music business. In our assessment, most of the EU, OECD, UNESCO recognized or endorsed observatories use obsolete technology and do not rely on the new achievements of data science. Reprex, our start-up offers an open source, open data based alternative solution to build largely automated data observatories. We believe that human judgement is needed in data curation, but processing, documentation and validation is best done by computers.

Case Study: Reprocessing geographical information with administrative boundary changes

At last, he presented a few development directions with our open-source software, mentioning our work withing the rOpenGov community. This part of the presentation was originally meant to open the way for a half-day open data workshop, but due to the current pandemic situation, the physical part of the conference and the workshops were not held.

The presentation largely included the topics of our Data & Lyrics blogpost: Open Data—The New Gold Without the Rush

Presentation Slides

See the presentation slides here.

Open Data

Sun, 16 May 2021 00:00:00 +0000

Many countries in the world allow access to a vast array of information, such as documents under freedom of information requests, statistics, datasets. In the European Union, most taxpayer financed data in government administration, transport, or meteorology, for example, can be usually re-used. More and more scientific output is expected to be reviewable and reproducible, which implies open access.

What’s the Problem with Open Data?

How We Add Value?

Is There Value in It?
If it’s money on the street, why nobody’s picking it up?

Datasets Should Work Together to Give Information
Data is only potential information, raw and unprocessed.

What’s the Problem with Open Data?

“Data is stuff. It is raw, unprocessed, possibly even untouched by human hands, unviewed by human eyes, un-thought-about by human minds.” [1]

Most open data cannot be just “downloaded.”
Often, you need to put more than $100 value of work into processing, validating, documenting a dataset that is worth $100. But you can share this investment with our data observatories.
Open data is almost always lacking of documentation, and no clear references to validate if the data is reliable or not corrupted. This is why we always start with reprocessing and redocumenting.

Our review of about 80 EU, UN and OECD data observatories reveals that most of them do not use these organizations’s open data - instead they use various, and often not well processed proprietary sources.

How We Add Value?

We believe that even such generally trusted data sources as Eurostat often need to be reprocessed, because various legal and political constraints do not allow the common European statistical services to provide optimal quality data – for example, on the regional and city levels.
With rOpenGov and other partners, we are creating open-source statistical software in R to re-process these heterogenous and low-quality data into tidy statistical indicators to automatically validate and document it.
Metadata is a potentially informative data record about a potentially informative dataset. We are carefully documenting and releasing administrative, processing, and descriptive metadata, following international metadata standards, to make our data easy to find and easy to use for data analysts.
We are automatically creating depositions and authoritative copies marked with an individual digital object identifier (DOI) to maintain data integrity.

Is There Value in Open Data?

A well-known story tells of a finance professor and a student who come across a $100 bill lying on the ground. As the student stops to pick it up, the professor says, “Don’t bother—if it were really a $100 bill, it wouldn’t be there.”

But this is not the case with open data. Often, you need to put more than $100 into processing, validating, documenting a dataset that is worth $100.

In the EU, open data is governed by the Directive on open data and the re-use of public sector information - in short: Open Data Directive (EU) 2019 / 1024. It entered into force on 16 July 2019. It replaces the Public Sector Information Directive, also known as the PSI Directive which dated from 2003 and was subsequently amended in 2013.

Open Data is potentially useful data that can potentially replace costlier or hard to get data sources to build information. It is analogous to potential energy: work is required to release it. We build automated systems that reduce this work and increase the likelihood that open data will offer the best value for money.

Most open data is not publicy accessible, and available upon request. Our real curatorial advantage is that we know where it is and how to get this request processed.
Most European open data comes from tax authorities, meteorological offices, managers of transport infrastructure, and other governmental bodies whose data needs are very different from yours. Their data must be carefully evaluated, re-processed, and if necessary, imputed to be usable for your scientific, business or policy goals.
The use of open science data is problematic in different ways: usually understanding the data documentation requires domain-specific specialist knowledge. Open science data is even more scattered and difficult to access than technically open, but not public governmental data.

From Datasets to Data Integration, Data to Information

“Data is only potential information, raw and unprocessed, prior to anyone actually being informed by it.” ^[2]

We are building simple databases and supporting APIs that release the data without restrictions, in a tidy format that is easy to join with other data, or easy to join into databases, together with standardized metadata.

Our service flow and value chain

FAQ

Why Downloading Does Not Work?

Most open data is not available on the internet.
If it is available, it is not in a form that you can easily import into a spreadsheet application like Excel or OpenOffice, or into a statistical application like SPSS or STATA.
Even the data quality of trusted web sources, like the Eurostat website, can be very low. Eurostat just publishes what it gets from governments, and often has no mandate to fix errors. The data is full with missing information, and in the case of regional statistics, faulty region codes and region names that make matching your data or placing them on a map impossible.
Adjusting euros with millions of euros, correctly translating dollars to euros, pounds to kilograms requires plenty of work. This is a very error-prone process when done by humans.

Can Open Data be Used in Machine Learning and AI?

Most public and open data sources have many missing observations; machine learning models usually cannot hanlde missingness. These points must be carefully imputed with approximations, which can be very challenging when the data has geographical dimension.
Removing missing values makes samples extremely biased and your model will learn from omissions, not information.

Photo Credits

What’s the Problem with Open Data? illustration is a photo by Cristina Gottardi How We Add Value? illustration is a photo by Nana Smirnova. Is There Value Left in It? is a photo by Imelda Datasets Should Work Together to Give Information is a photo by Lucas Santos

Footnote References

[1] Pomerantz, Jeffrey. 2021. “Metadata.” MIT Press essential knowledge series. MIT Press. Cambridge, Massachusetts ; London, England : The MIT Press, [2015]

[2] Pomerantz, Jeffrey. 2021. “Metadata.” MIT Press essential knowledge series. MIT Press. Cambridge, Massachusetts ; London, England : The MIT Press, [2015]

Reprex Open Data Day 2021

Sat, 06 Mar 2021 15:30:00 +0200

Open Data Day is an annual celebration of open data all over the world. It is an opportunity to show the benefits of open data and encourage the adoption of open data policies in government, business, and civil society. Reprex is a start-up that utilizes open data with open-source reproducible research: please challenge us with your data requests and participate in our web events.

The Reprex Open Data Day 2021 will be two informal conversations based on a series of run up introductory blogposts centered around two themes. Because important guests became ill in the last days, we are going to consolidate the two talks into one with less structure. We want to create an informal, inclusive, collaborative online event on International Open Data Day 2021. Please, grab a tea, coffee, or even a beer, and join us for an informal conversation. We hope that we will finish the afternoon with ideas on new, open-data driven collaborations.

9.30 EST / 15.30 CET: Open collaboration in business, policy and science. Creating evidence-based policy, business strategy or scientific research with small contributions with independent components with incentives. Short introduction with examples: joining environmental sensory data and public opinion data on maps; creating harmonized datasets across the Arab world. Survey harmonization, mapping, data products. Scaling up open collaboration: making small organizations competitive with big tech in the big data era. Data sharing, data pooling, data altruism and observatories. The new European trustworthy AI and data governance agenda.

You can click through a short presentation to familiarize yourself with our topics.

See you here.

Case studies:

We are connecting raw survey data about Climate Awareness in Eurobarometer surveys. Here is the reproduction code (intermediate to advanced R needed.) You should use the development version of our retroharmonize package at github.com/antaldaniel/retroharmonize
We are tracking changes in the boundaries of provinces, states, counties, parishes with our regions open source software – reproduction code here. You will need our regions package which is available on CRAN or in the rOpenGov GitHub repo.
We will talk about how to join this with air pollution data and put it on the map with Milos Popovic, who prepared this nice choropleth animation.

We will discuss data observatories (permanent data collection programs), open collaboration (open-source inspired way of cooperation among small and large independent actors) and data altruism.

Any questions: send Daniel a message on Keybase, Whatsapp or email.

Hello on International #OpenDataDay2021 from🌷 the Hague!
- We have brought some new data to the light about 🌡climate change awareness
- We created some tutorials how to harmonize survey and geographical data
- Join us at 9.30 EST/15.30 CET 👇https://t.co/7J7pvi3sPC #ODD2021 pic.twitter.com/DwkGQaDhW1
— dataandlyrics (@dataandlyrics) March 6, 2021