SPEEDY: An Eclipse-based IDE for invariant inference

SPEEDY is an Eclipse-based IDE for exploring techniques that assist users in generating correct specifications, particularly including invariant inference algorithms and tools. It integrates with several back-end tools that propose invariants and will incorporate published algorithms for inferring object and loop invariants. Though the architecture is language-neutral, current SPEEDY targets C programs. Building and using SPEEDY has confirmed earlier experience demonstrating the importance of showing and editing specifications in the IDEs that developers customarily use, automating as much of the production and checking of specifications as possible, and showing counterexample information directly in the source code editing environment. As in previous work, automation of specification checking is provided by back-end SMT solvers. However, reducing the effort demanded of software developers using formal methods also requires a GUI design that guides users in writing, reviewing, and correcting specifications and automates specification inference.Comment: In Proceedings F-IDE 2014, arXiv:1404.578

2011 Strategic roadmap for Australian research infrastructure

The 2011 Roadmap articulates the priority research infrastructure areas of a national scale (capability areas) to further develop Australia’s research capacity and improve innovation and research outcomes over the next five to ten years. The capability areas have been identified through considered analysis of input provided by stakeholders, in conjunction with specialist advice from Expert Working Groups   It is intended the Strategic Framework will provide a high-level policy framework, which will include principles to guide the development of policy advice and the design of programs related to the funding of research infrastructure by the Australian Government. Roadmapping has been identified in the Strategic Framework Discussion Paper as the most appropriate prioritisation mechanism for national, collaborative research infrastructure. The strategic identification of Capability areas through a consultative roadmapping process was also validated in the report of the 2010 NCRIS Evaluation. The 2011 Roadmap is primarily concerned with medium to large-scale research infrastructure. However, any landmark infrastructure (typically involving an investment in excess of $100 million over five years from the Australian Government) requirements identified in this process will be noted. NRIC has also developed a ‘Process to identify and prioritise Australian Government landmark research infrastructure investments’ which is currently under consideration by the government as part of broader deliberations relating to research infrastructure. NRIC will have strategic oversight of the development of the 2011 Roadmap as part of its overall policy view of research infrastructure

The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases.

Model organisms are essential experimental platforms for discovering gene functions, defining protein and genetic networks, uncovering functional consequences of human genome variation, and for modeling human disease. For decades, researchers who use model organisms have relied on Model Organism Databases (MODs) and the Gene Ontology Consortium (GOC) for expertly curated annotations, and for access to integrated genomic and biological information obtained from the scientific literature and public data archives. Through the development and enforcement of data and semantic standards, these genome resources provide rapid access to the collected knowledge of model organisms in human readable and computation-ready formats that would otherwise require countless hours for individual researchers to assemble on their own. Since their inception, the MODs for the predominant biomedical model organisms [Mus sp (laboratory mouse), Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Danio rerio, and Rattus norvegicus] along with the GOC have operated as a network of independent, highly collaborative genome resources. In 2016, these six MODs and the GOC joined forces as the Alliance of Genome Resources (the Alliance). By implementing shared programmatic access methods and data-specific web pages with a unified "look and feel," the Alliance is tackling barriers that have limited the ability of researchers to easily compare common data types and annotations across model organisms. To adapt to the rapidly changing landscape for evaluating and funding core data resources, the Alliance is building a modern, extensible, and operationally efficient "knowledge commons" for model organisms using shared, modular infrastructure

HaIRST: Harvesting Institutional Resources in Scotland Testbed. Final Project Report

The HaIRST project conducted research into the design, implementation and deployment of a pilot service for UK-wide access of autonomously created institutional resources in Scotland, the aim being to investigate and advise on some of the technical, cultural, and organisational requirements associated with the deposit, disclosure, and discovery of institutional resources in the JISC Information Environment. The project involved a consortium of Scottish higher and further education institutions, with significant assistance from the Scottish Library and Information Council. The project investigated the use of technologies based on the Open Archives Initiative (OAI), including the implementation of OAI-compatible repositories for metadata which describe and link to institutional digital resources, the use of the OAI protocol for metadata harvesting (OAI-PMH) to automatically copy the metadata from multiple repositories to a central repository, and the creation of a service to search and identify resources described in the central repository. An important aim of the project was to identify issues of metadata interoperability arising from the requirements of individual institutional repositories and their impact on services based on the aggregation of metadata through harvesting. The project also sought to investigate issues in using these technologies for a wide range of resources including learning, teaching and administrative materials as well as the research and scholarly communication materials considered by many of the other projects in the JISC Focus on Access to Institutional Resources (FAIR) Programme, of which HaIRST was a part. The project tested and implemented a number of open source software packages supporting OAI, and was successful in creating a pilot service which provides effective information retrieval of a range of resources created by the project consortium institutions. The pilot service has been extended to cover research and scholarly communication materials produced by other Scottish universities, and administrative materials produced by a non-educational institution in Scotland. It is an effective testbed for further research and development in these areas. The project has worked extensively with a new OAI standard for 'static repositories' which offers a low-barrier, low-cost mechanism for participation in OAI-based consortia by smaller institutions with a low volume of resources. The project identified and successfully tested tools for transforming pre-existing metadata into a format compliant with OAI standards. The project identified and assessed OAI-related documentation in English from around the world, and has produced metadata for retrieving and accessing it. The project created a Web-based advisory service for institutions and consortia. The OAI Scotland Information Service (OAISIS) provides links to related standards, guidance and documentation, and discusses the findings of HaIRST relating to interoperability and the pilot harvesting service. The project found that open source packages relating to OAI can be installed and made to interoperate to create a viable method of sharing institutional resources within a consortium. HaIRST identified issues affecting the interoperability of shared metadata and suggested ways of resolving them to improve the effectiveness and efficiency of shared information retrieval environments based on OAI. The project demonstrated that application of OAI technologies to administrative materials is an effective way for institutions to meet obligations under Freedom of Information legislation

Mining whole sample mass spectrometry proteomics data for biomarkers: an overview

In this paper we aim to provide a concise overview of designing and conducting an MS proteomics experiment in such a way as to allow statistical analysis that may lead to the discovery of novel biomarkers. We provide a summary of the various stages that make up such an experiment, highlighting the need for experimental goals to be decided upon in advance. We discuss issues in experimental design at the sample collection stage, and good practise for standardising protocols within the proteomics laboratory. We then describe approaches to the data mining stage of the experiment, including the processing steps that transform a raw mass spectrum into a useable form. We propose a permutation-based procedure for determining the significance of reported error rates. Finally, because of its general advantages in speed and cost, we suggest that MS proteomics may be a good candidate for an early primary screening approach to disease diagnosis, identifying areas of risk and making referrals for more specific tests without necessarily making a diagnosis in its own right. Our discussion is illustrated with examples drawn from experiments on bovine blood serum conducted in the Centre for Proteomic Research (CPR) at Southampton University

Deploying Virtual Machines on Shared Platforms

In this report, we describe mechanisms for secure deployment of virtual machines on shared platforms looking into a telecommunication cloud use case, which is also presented in this report. The architecture we present focuses on the security requirements of the major stakeholders’ part of the scenario we present. This report comprehensively covers all major security aspects including different security mechanisms and protocols, leveraging existing standards and state-of-the art wherever applicable. In particular, our architecture uses TCG technologies for trust establishment in the deployment of operator virtual machines on shared resource platforms. We also propose a novel procedure for securely launching and cryptographically binding a virtual machine to a target platform thereby protecting the operator virtual machine and its related credentials

Sharing practice, problems and solutions for institutional change

This chapter critiques the roles of different forms of representation of practice as part of an institutional change process. It discusses how these representations can be used both to design and to share learning activities at the various levels of decision-making in a university. We illustrate our arguments with empirical data gathered on change processes associated with an institution-wide change programme: the introduction of a new virtual learning environment (VLE). In particular, we describe a case study of the introduction of the VLE tools in a business course. We focus on two particular forms of representations to describe the essence of the innovation: a pedagogical pattern and a visual learning design. We argue that pedagogical patterns and learning design have emerged as parallel approaches to describing practice in recent years. Despite their very different origins, both provide complementary representations, which emphasize different aspects of the practice being described. We are attempting to combine these approaches. We briefly outline the Open University Learning Design initiative, of which this work is part, and describe its key underpinning philosophies. We believe our approach provides a vehicle for enabling a better articulation of design principles and the discussion of issues concerning the re-use of educational resources and activities

A posteriori metadata from automated provenance tracking: Integration of AiiDA and TCOD

In order to make results of computational scientific research findable, accessible, interoperable and re-usable, it is necessary to decorate them with standardised metadata. However, there are a number of technical and practical challenges that make this process difficult to achieve in practice. Here the implementation of a protocol is presented to tag crystal structures with their computed properties, without the need of human intervention to curate the data. This protocol leverages the capabilities of AiiDA, an open-source platform to manage and automate scientific computational workflows, and TCOD, an open-access database storing computed materials properties using a well-defined and exhaustive ontology. Based on these, the complete procedure to deposit computed data in the TCOD database is automated. All relevant metadata are extracted from the full provenance information that AiiDA tracks and stores automatically while managing the calculations. Such a protocol also enables reproducibility of scientific data in the field of computational materials science. As a proof of concept, the AiiDA-TCOD interface is used to deposit 170 theoretical structures together with their computed properties and their full provenance graphs, consisting in over 4600 AiiDA nodes