If Open Data is Like Open Source (20 Years Ago) 5/5: Inner Data

In five posts, I want to speculate about the next twenty years of open data based on the past twenty years of open source. The idea is to transfer what we learned from open source in one way or another to open data.

This is part 5 on inner data, that is, the collaborative creation and sharing of data within one company.

If this sounds easy, please meet the “modern” corporation with internal competition, phlegmatism and personal antipathy, all of which ensure the corporate silo structure.

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If Open Data is Like Open Source (20 Years Ago) 1/5: Definition

In five posts, I want to speculate about the next twenty years of open data based on the past twenty years of open source. The idea is to transfer what we learned from open source in one way or another to open data.

This is part 1 on the definition of open data.

Please note that beyond this intellectual exercise, some of this is already here and some of it is simply different.

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Enabling Open Innovation with Open Data using the JValue Open Data Service

Today I gave my JValue Open Data Service talk at USM (University of Sciences, Malaysia, at Penang). I am grateful for the opportunity and the recording.

Abstract: Open data has the potential to create significant practical value for its users through open innovation. Yet, to realize this value, we need an open ecosystem, next to open data, that allows app developers to create that value. In this talk I present my view of this open ecosystem of open data and how it should be structured. I then present the JValue Open Data Service (ODS), an open source software under development at my research group, that provides a key piece of this ecosystem. The goal of the JValue ODS project is to enable open innovation through app developers.

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Open Data: Source of Public Income or Invaluable Common Good?

Not surprisingly, this huddling panel at the 2018 Berlin Open Data Day came to no specific conclusion, just different opinions on business models and who should earn what income.

Some nuggets of insight: Leave it to public institutions to decide for themselves — open data should be freely available, otherwise some commercial business models break down — cities should be neutral to startups and establish collaborations for everyone’s benefit — leave it to companies to generate value from open data and they will give back #muwhaha — don’t monetarize open data at all — if users don’t pay, public institutions won’t have the funds to provide open data — open data should be considered public infrastructure and follow established practices — the data belongs to the public anyway — selling data is too expensive for a city.

In related news, some cheap laughs for public institution bashing from one panelist. Personally, I find this less than helpful.

One amusing quote from another panelist:

In theory, we all agree, in practice, we do not.

I guess more sustainability research is needed.

Open Data is Moving, Slowly but Surely

I’ve been participating in various workshops and working groups on open data now. It is hard scrabble, but things are moving. Today I participated in a workshop of the open data task force of Bitkom which I am a member of. The highlight of the day was the participation of Saskia Esken who explained some and handled questions and answers on the new open data for government law that is coming up in Germany.

In related news, the task force finished its open data manifest, a collection of quality attributes of what good open data are and what to ask of providers and the government. A small handbook is in work as well.