This paper discusses many of the issues associated with formally publishing data in academia, focusing primarily on the structures that need to be put in place for peer review and formal citation of datasets. Data publication is becoming increasingly important to the scientific community, as it will provide a mechanism for those who create data to receive academic credit for their work and will allow the conclusions arising from an analysis to be more readily verifiable, thus promoting transparency in the scientific process. Peer review of data will also provide a mechanism for ensuring the quality of datasets, and we provide suggestions on the types of activities one expects to see in the peer review of data. A simple taxonomy of data publication methodologies is presented and evaluated, and the paper concludes with a discussion of dataset granularity, transience and semantics, along with a recommended human-readable citation syntax.

Software preservation has not had detailed consideration as a research topic or in practical application. In this paper, we present a conceptual framework to capture and organise the main notions of software preservation, which are required for a coherent and comprehensive approach.  This framework has three main aspects. Firstly a discussion of what it means to preserve software via a performance model which considers how a software artefact can be rebuilt from preserved components and can then be seen to be representative of the original software product. Secondly the development of a model of software artefacts, describing the basic components of all software, loosely based on the FRBR model for representing digital artefacts and their history within a library context. Finally, the definition and categorisation of the properties of software artefacts which are required to ensure that the software product has been adequately preserved. These are broken down into a number of categories and related to the concepts defined in the OAIS standard. We also discuss our experience of recording these preservation properties for a number of BADC software products, which arose from a series of case studies conducted to evaluate the software preservation framework, and also briefly describe the SPEQS toolkit, a tool to capture software preservation properties within a software development.

The Subject and Institutional Repositories Interactions Study (SIRIS) was undertaken for JISC in 2008 with a brief to produce a set of practical recommendations to improve interactions between institutional and subject repositories in the UK in respect to scholarly articles. The study was based on interviews with stakeholders and a questionnaire distributed to institutional repository managers. The different types of repository and their functional requirements are defined. The authors consider the reasons repositories interact and the types of interaction they might engage in. The current situation in the UK repository system is described. Key findings that emerged from the study concern achievement of critical mass, collection priorities, metadata, identifiers and versions, and the issue of trust as it affects engagement on the part of community members. The authors develop a number of scenarios for possible evolutions in repository interactions in the near future, organized around four key drivers: population of repositories, statistics and metrics, preservation, and aggregation of research outputs. The study's final report addressed seven recommendations to various stakeholder groups within the repository community: JISC, research funders, repository managers, publishers, content creators, and software developers. These recommendations concern standardization, best practice, and community engagement and dialogue.

Great strides have been made to encourage researchers to archive data created by research and provide the necessary systems to support their storage. Additionally it is recognised that data are meaningless unless their provenance is preserved, through appropriate meta-data. Alongside this is a pressing need to ensure the quality and archiving of the software that generates data, through simulation, control of experiment or data-collection and that which analyses, modifies and draws value from raw data. In order to meet the aims of reproducibility we argue that data management alone is insufficient: it must be accompanied by good software practices, the training to facilitate it and the support of stakeholders, including appropriate recognition for software as a research output.

An evaluation of enhancing social tagging with a knowledge organization system. ASLIB Proceedings AbstractTraditional subject indexing and classification are considered infeasible in many digital collections. Automated means and social tagging are often suggested as the two possible solutions. Both, however, have disadvantages and, depending on the purpose of use or context, require additional manual input. This study investigates ways of enhancing social tagging via knowledge organization systems, with a view to improving the quality of tags for increased information discovery and retrieval performance. Benefits of using both social tags and controlled terms are also explored, including enriching knowledge organization systems with new concepts.