Abstract

The 2018 paper titled “Common Patterns in Revolutionary Infrastructures and Data” has been cited frequently, since we compared the current discussions about research data management with the developments of large infrastructures in the past believing, similar to philosophers such as Luciano Floridi, that the creation of an interoperable data domain will also be a revolutionary step. We identified the FAIR principles and the FAIR Digital Objects as nuclei for achieving the necessary convergence without which such new infrastructures will not take up. In this follow-up paper, we are elaborating on some factors that indicate that it will still take much time until breakthroughs will be achieved which is mainly devoted to sociological and political reasons. Therefore, it is important to describe visions such as FDO as self-standing entities, the easy plug-in concept, and the built-in security more explicitly to give a long-range perspective and convince policymakers and decision-makers. We also looked at major funding programs which all follow different approaches and do not define a converging core yet. This can be seen as an indication that these funding programs have huge potentials and increase awareness about data management aspects, but that we are far from converging agreements which we finally will need to create a globally integrated data space in the future. Finally, we discuss the roles of some major stakeholders who are all relevant in the process of agreement finding. Most of them are bound by short-term project cycles and funding constraints, not giving them sufficient space to work on long-term convergence concepts and take risks. The great opportunity to get funds for projects improving approaches and technology with the inherent danger of promising too much and the need for continuous reporting and producing visible results after comparably short periods is like a vicious cycle without a possibility to break out. We can recall that coming to the Internet with TCP/IP as a convergence standard was dependent on years of DARPA funding. Building large revolutionary infrastructures seems to be dependent on decision-makers that dare to think strategically and test out promising concepts at a larger scale.

Highlights

  • In our 2018 paper “Common Patterns in Revolutionary Infrastructures and Data” [1], we argued that revolutionary infrastructures can be characterized by simple core standards which, on the one hand, promise some stability associated with a step of disruption but, on the other hand, act as a new common platform for dynamic evolution above that platform

  • We identified the FAIR principles [2] and the FAIR Digital Objects

  • “virtual data collection” which we introduced above: (1) the Digital Object (DO) approach based on Handles/DOIs and DOIP [10] and (2) the Linked Data (LD) approach [11] based on URIs and the Web protocol stack

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Summary

Introduction

In our 2018 paper “Common Patterns in Revolutionary Infrastructures and Data” [1], we argued that revolutionary infrastructures can be characterized by simple core standards which, on the one hand, promise some stability associated with a step of disruption but, on the other hand, act as a new common platform for dynamic evolution above that platform. The bit-sequences of FDOs can include all kinds of types (data, metadata, software, etc.).) [3,4] as candidates for achieving convergence and admitted that it will take time to agree on these concepts and turn them into practice. Three more years of discussions, substantial investments in infrastructure projects, and new initiatives confirm our view that FAIR and FDOs are good candidates, but that more years will be needed to achieve a state where major stakeholders will have come to agreements and where industry will join to develop technology. Y.N. Harari describes in his book “Homo Deus” [5] that information (and data) want to be free and that this is a new revolutionary step in the development of culture.

Integrated Virtual Data Collection
Easy Plug-In
Self-Standing Entities
Built-In Security
Summary
Research Infrastructures
NIH Commons
Stakeholder Interests
Researchers
Tool Developers
Industry
Policy-Makers
Conclusions
Full Text
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