Data sharing practices and data availability upon request differ across scientific disciplines

Data sharing is one of the cornerstones of modern science that enables large-scale analyses and reproducibility. We evaluated data availability in research articles across nine disciplines in Nature and Science magazines and recorded corresponding authors' concerns, requests and reasons for declining data sharing. Although data sharing has improved in the last decade and particularly in recent years, data availability and willingness to share data still differ greatly among disciplines. We observed that statements of data availability upon (reasonable) request are inefficient and should not be allowed by journals. To improve data sharing at the time of manuscript acceptance, researchers should be better motivated to release their data with real benefits such as recognition, or bonus points in grant and job applications. We recommend that data management costs should be covered by funding agencies; publicly available research data ought to be included in the evaluation of applications; and surveillance of data sharing should be enforced by both academic publishers and funders. These cross-discipline survey data are available from the plutoF repository.Peer reviewe

Regulation through code as a safeguard for implementing smart contracts in no-trust environments

Smart contracts, self-executing agreements based on blockchain technology, are a hotly debated topic in the tech community, among policy makers, industry stakeholders and in academia. They offer the prospect of cheaper, faster and better transactions. The hype around smart contracts is also viewed with caution. We contribute to the existing academic literature by addressing some of the concerns about the legal nature, anonymity and reliability of smart contracts. Several contract law scholars argue that smart contracts cannot offer a superior solution to many problems addressed by traditional contract law, such as contract validity and legality. Furthermore, they argue that smart contracts cannot replicate the relational context which is essential for the day-to-day practice of contracting. In this contribution, we firstly draw a distinction between smart contracts based on public blockchains and those based on private or permissioned blockchains. While all existing contributions develop their arguments implicitly assuming that smart contracts are based on public blockchains, much commercial experimentation with smart contracts is occurring on permissioned blockchains. Importantly, many of the mentioned problems do not arise on permissioned blockchains. Secondly, we argue that there is a good reason to prefer public blockchains over permissioned blockchains for contracting, namely their capacity to create trust in otherwise no-trust contracting environments. This is the path to unleash the full potential of smart contracts. In contrast to critics, we argue that compared to traditional contract law, smart contracts potentially offer a superior solution for facilitating trade

Machines that make and keep promises - Lessons for contract automation from algorithmic trading on financial markets

An important part of the criticism raised against the adoption of advanced contract automation relates to the inflexibility of automated contracts. Drawing on rational choice theory, we explain why inflexibility, when seen as a constraint, can ultimately not only enhance welfare but also enable cooperation on algorithmic markets. This illuminates the need to address the inflexibility of contracting algorithms in a nuanced manner, distinguishing between inflexibility as a potentially beneficial constraint on the level of transactions, and inflexibility as a set of systemic risks and changes arising in markets employing inflexible contracting algorithms. Using algorithmic trading in financial markets as an example, we show how the automation of finance has brought about institutional changes in the form of new regulation to hedge against systemic risks from inflexibility. Analyzing the findings through the lens of new institutional economics, we explain how widespread adoption of contract automation can put pressure on institutions to change. We conclude with possible lessons that algorithmic finance can teach to markets deploying algorithmic contracting.Published versio

Placemaking and intellectual property

No abstract available