A reputation economy: how individual reward considerations trump systemic arguments for open access to data : Palgrave Communications

Abstract:  Open access to research data has been described as a driver of innovation and a potential cure for the reproducibility crisis in many academic fields. Against this backdrop, policy makers are increasingly advocating for making research data and supporting material openly available online. Despite its potential to further scientific progress, widespread data sharing in small science is still an ideal practised in moderation. In this article, we explore the question of what drives open access to research data using a survey among 1564 mainly German researchers across all disciplines. We show that, regardless of their disciplinary background, researchers recognize the benefits of open access to research data for both their own research and scientific progress as a whole. Nonetheless, most researchers share their data only selectively. We show that individual reward considerations conflict with widespread data sharing. Based on our results, we present policy implications that are in line with both individual reward considerations and scientific progress.

Open Academic Society

“Open Academic Society is formed by a group of institutions to create a shared, open and expanding knowledge graph of research and education-focused entities and relationships. With the initial contributions from the Microsoft Academic by Microsoft Research and the AMiner graph from Tsinghua University, the reach and depth of the knowledge graph will come through the Society members’ contributions. The data set is available under a freely accessible cloud API, and the society will organize workshops, challenges, and data sharing activities for the benefit of the larger computer science community….”

Sharing Detailed Research Data Is Associated with Increased Citation Rate

Abstract:  

Background

Sharing research data provides benefit to the general scientific community, but the benefit is less obvious for the investigator who makes his or her data available.

Principal Findings

We examined the citation history of 85 cancer microarray clinical trial publications with respect to the availability of their data. The 48% of trials with publicly available microarray data received 85% of the aggregate citations. Publicly available data was significantly (p?=?0.006) associated with a 69% increase in citations, independently of journal impact factor, date of publication, and author country of origin using linear regression.

Significance

This correlation between publicly available data and increased literature impact may further motivate investigators to share their detailed research data.

Open Data for Development — Global Partnership for Sustainable Development Data

“Open Data for Development is a global partnership of more than 65 institutions eager to advance the creation of locally-driven and sustainable open data ecosystems in developing countries. It focuses on building up the supply of quality open data and improving the use of that data by leaders in government, civil society, the media and business so that it furthers public interest and improves peoples’ lives.

Funded by the International Development Research Centre (IDRC), World Bank, Global Affairs Canada and U.K. Department for International Development (DFID), OD4D works with leading open data organizations to create knowledge and inform policies, standards, innovation and research in Latin America, the Caribbean, Eastern Europe, Africa and Asia. OD4D’s focus in 2014-16 has been on helping developing-country governments, entrepreneurs and civil society create a global action plan to harness open data for development and to manage national data initiatives….”

Open Science Federation | to open science

“The Open Science Federation is a nonprofit alliance working to improve the conduct and communication of science. We are scientists and citizen scientists, writers, journalists, and educators, and makers of and advocates for Open Data, Open Access, and Open Source and Standards.

Get to know us at @openscience on Twitter, or in Google+, and elsewhere, with which we have connected the largest Open Science network in the world. We recently took up a count, deduplicated, and identified over 40,000 people and groups across our social network.

We do not intend to be at the centre of the Open Science community per se, though analyses often place us there….A network can be stronger than any one organization, and a federation of networks, stronger still. Thus we share access to our social media accounts with many individuals and organisations….”

Short Course Spotlight: ICPSR – Machine Learning for the Analysis of Text as Data – The Odum Institute

“Quantitative analysis of digitized text represents an exciting and challenging frontier of data science across a broad spectrum of disciplines. From the analysis of physicians’ notes to identify patients with diabetes, to the assessment of global happiness through the analysis of speech on Twitter, patterns in massive text corpora have led to important scientific advancements.

In this course we will cover several central computational and statistical methods for the analysis of text as data. Topics will include the manipulation and summarization of text data, dictionary methods of text analysis, prediction and classification with textual data, document clustering, text reuse measurement, and statistical topic models….”

Qualitative Data Repository

“QDR selects, ingests, curates, archives, manages, durably preserves, and provides access to digital data used in qualitative and multi-method social inquiry.  The repository develops and publicizes common standards and methodologically informed practices for these activities, as well as for the reusing and citing of qualitative data.  Four beliefs underpin the repository’s mission: data that can be shared and reused should be; evidence-based claims should be made transparently; teaching is enriched by the use of well-documented data; and rigorous social science requires common understandings of its research methods….”

Data Access & Research Transparency (DA-RT)

“Working together, researchers, journal editors, publishers, and professional associations have made important progress on matters of data sharing and research transparency. Our hope is that these continuing conversations will increase the legitimacy, credibility, and openness of intellectually diverse research communities….DA-RT has no formal organization chart. It began in 2010, as an Ad Hoc Committee of the American Political Science Association. As of today, it has no formalized membership. DA-RT is more accurately concieved as an idea rather than an institution. If you want to be part of it, you are….”