Data occupy a key role in our information society. However, although the amount of published data continues to grow and terms such as data deluge and big data today characterize numerous (research) initiatives, much work is still needed in the direction of publishing data in order to make them effectively discoverable, available, and reusable by others. Several barriers hinder data publishing, from lack of attribution and rewards, vague citation practices, and quality issues to a rather general lack of a data-sharing culture. Lately, data journals have overcome some of these barriers. In this study of more than 100 currently existing data journals, we describe the approaches they promote for data set description, availability, citation, quality, and open access. We close by identifying ways to expand and strengthen the data journals approach as a means to promote data set access and exploitation.

A part of a query that will never contribute data to the query answer should be regarded as an error. This principle has been recently accepted into mainstream XML query languages, but was still waiting for a complete treatment. We provide here a precise definition for this class of errors, and define a type system that is sound and complete, in its search for such errors, for a core language, under mild restrictions on the use of recursion in type definitions. In the process, we describe a dichotomy among existential and universal type systems, which is essential to understand some specific features of our type system.

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