myTea: Connecting the Web to Digital Science on the Desktop

Bioinformaticians regularly access the hundreds of databases and tools that are available to them on the Web. None of these tools communicate with each other, causing the scientist to copy results manually from a Web site into a spreadsheet or word processor. myGrids' Taverna has made it possible to create templates (workflows) that automatically run searches using these databases and tools, cutting down what previously took days of work into hours, and enabling the automated capture of experimental details. What is still missing in the capture process, however, is the details of work done on that material once it moves from the Web to the desktop: if a scientist runs a process on some data, there is nothing to record why that action was taken; it is likewise not easy to publish a record of this process back to the community on the Web. In this paper, we present a novel interaction framework, built on Semantic Web technologies, and grounded in usability design practice, in particular the Making Tea method. Through this work, we introduce a new model of practice designed specifically to (1) support the scientists' interactions with data from the Web to the desktop, (2) provide automatic annotation of process to capture what has previously been lost and (3) associate provenance services automatically with that data in order to enable meaningful interrogation of the process and controlled sharing of the results

Trustworthy repositories: Audit and certification (TRAC) Cline Library internal audit, spring 2014

Audit and Certification of Trustworthy Digital Repositories (TRAC) is a recommended practice developed by the Consultative Committee for Space Data Systems. The TRAC international standard (ISO 16363:2012) provides institutions with guidelines for performing internal audits to evaluate the trustworthiness of digital repositories, and creates a structure to support external certification of repositories. TRAC establishes criteria, evidence, best practices and controls that digital repositories can use to assess their activities in the areas of organizational infrastructure, digital object management, and technical infrastructure and risk management. The Cline Library at Northern Arizona University has undertaken an internal audit based on TRAC in order to evaluate the policies, procedures and workflows of the existing digital archives and to prepare for the development and implementation of the proposed institutional repository. The following document provides an overview of the results and recommendations produced by this internal audit

Enhancing Workflow with a Semantic Description of Scientific Intent

Peer reviewedPreprin

Recording provenance of workflow runs with RO-Crate

Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products.Several data models have been explored to address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing.However, existing approaches tend to lack interoperable adoption across workflow management systems.In this work we present Workflow Run RO-Crate, an extension of RO-Crate (Research Object Crate) and Schema.org to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.).The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects.Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems.We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems.Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain.A corresponding RO-Crate for this article is at https://w3id.org/ro/doi/10.5281/zenodo.1036898

Provenance explorer: Customized provenance views using semantic inferencing

This paper presents Provenance Explorer, a secure provenance visualization tool, designed to dynamically generate customized views of scientific data provenance that depend on the viewer's requirements and/or access privileges. Using RDF and graph visualizations, it enables scientists to view the data, states and events associated with a scientific workflow in order to understand the scientific methodology and validate the results. Initially the Provenance Explorer presents a simple, coarse-grained view of the scientific process or experiment. However the GUI allows permitted users to expand links between nodes (input states, events and output states) to reveal more fine-grained information about particular sub-events and their inputs and outputs. Access control is implemented using Shibboleth to identify and authenticate users and XACML to define access control policies. The system also provides a platform for publishing scientific results. It enables users to select particular nodes within the visualized workflow and drag-and-drop them into an RDF package for publication or e-learning. The direct relationships between the individual components selected for such packages are inferred by the rule-inference engine