Wellcome Trust Policy on Data Management and Sharing

The Wellcome Trust's policy statement on data management and sharing, which was originally published in January 2007 and revised in August 2010

Reasoning with Data Flows and Policy Propagation Rules

Data-oriented systems and applications are at the centre of current developments of the World Wide Web. In these scenarios, assessing what policies propagate from the licenses of data sources to the output of a given data-intensive system is an important problem. Both policies and data flows can be described with Semantic Web languages. Although it is possible to define Policy Propagation Rules (PPR) by associating policies to data flow steps, this activity results in a huge number of rules to be stored and managed. In a recent paper, we introduced strategies for reducing the size of a PPR knowledge base by using an ontology of the possible relations between data objects, the Datanode ontology, and applying the (A)AAAA methodology, a knowledge engineering approach that exploits Formal Concept Analysis (FCA). In this article, we investigate whether this reasoning is feasible and how it can be performed. For this purpose, we study the impact of compressing a rule base associated with an inference mechanism on the performance of the reasoning process. Moreover, we report on an extension of the (A)AAAA methodology that includes a coherency check algorithm, that makes this reasoning possible. We show how this compression, in addition to being beneficial to the management of the knowledge base, also has a positive impact on the performance and resource requirements of the reasoning process for policy propagation

Administrative Data and Economic Policy Evaluation

This paper looks at the strengths and weaknesses of using administrative data for economic policy evaluation. It does this by looking at how school administrative data has been used to assess school effectiveness and the impact of month of birth on educational outcomes with varying degrees of success. It concludes that if there is some natural experiment in the way the education is delivered or an education initiative is introduced, then schools’ administrative data offers the opportunity of answering questions of extreme policy interest in a robust way – even without rich background information on the students and their families.administrative data, evaluation methods, school league tables, month of birth, natural experiment

ASTRO Journals' Data Sharing Policy and Recommended Best Practices.

Transparency, openness, and reproducibility are important characteristics in scientific publishing. Although many researchers embrace these characteristics, data sharing has yet to become common practice. Nevertheless, data sharing is becoming an increasingly important topic among societies, publishers, researchers, patient advocates, and funders, especially as it pertains to data from clinical trials. In response, ASTRO developed a data policy and guide to best practices for authors submitting to its journals. ASTRO's data sharing policy is that authors should indicate, in data availability statements, if the data are being shared and if so, how the data may be accessed

BBSRC Data Sharing Policy

BBSRC recognizes the importance of contributing to the growing international efforts in data sharing. BBSRC is committed to getting the best value for the funds we invest and believes that making research data more readily available will reinforce open scientific inquiry and stimulate new investigations and analyses. BBSRC supports the view that data sharing should be led by the scientific community and driven by scientific need. It should also be cost effective and the data shared should be of the highest quality. Members of the community are expected and encouraged to practice and promote data sharing, determine standards and best practice, and create a scientific culture in which data sharing is embedded