Capturing interoperable reproducible workflows with Common Workflow Language

We present our ongoing work on integrating Research Object practices with Common Workflow Language, capturing and describing prospective and retrospective provenance.Accepted for talk at RO2018. Web version at http://s11.no/2018/cwl.htm

Evaluation of Application Possibilities for Packaging Technologies in Canonical Workflows

In Canonical Workflow Framework for Research (CWFR) “packages” are relevant in two different directions. In data science, workflows are in general being executed on a set of files which have been aggregated for specific purposes, such as for training a model in deep learning. We call this type of “package” a data collection and its aggregation and metadata description is motivated by research interests. The other type of “packages” relevant for CWFR are supposed to represent workflows in a self-describing and self-contained way for later execution. In this paper, we will review different packaging technologies and investigate their usability in the context of CWFR. For this purpose, we draw on an exemplary use case and show how packaging technologies can support its realization. We conclude that packaging technologies of different flavors help on providing inputs and outputs for workflow steps in a machine-readable way, as well as on representing a workflow and all its artifacts in a self-describing and self-contained way

The Oxford Common File Layout: A common approach to digital preservation

The Oxford Common File Layout describes a shared approach to filesystem layouts for institutional and preservation repositories, providing recommendations for how digital repository systems should structure and store files on disk or in object stores. The authors represent institutions where digital preservation practices have been established and proven over time or where significant work has been done to flesh out digital preservation practices. A community of practitioners is surfacing and is assessing successful preservation approaches designed to address a spectrum of use cases. With this context as a background, the Oxford Common File Layout (OCFL) will be described as the culmination of over two decades of experience with existing standards and practices

The openCARP CDE: Concept for and implementation of a sustainable collaborativedevelopment environment for research software

This work describes the setup of an advanced technical infrastructure for collabora-tive software development in large, distributed projects based on GitLab. We presentits customization and extension, additional features and processes like code review,continuous automated testing, DevOps practices, and sustainable life-cycle manage-ment including long-term preservation and citable publishing of software releasesalong with relevant metadata. The collaborative development environment (CDE) iscurrently used for developing the open cardiac simulation software openCARP and anevaluation showcases its capability and utility for collaboration and coordination ofsizeable heterogeneous teams. As such, it could be a suitable and sustainable infras-tructure solution for a wide range of research software projects

Methods Included:Standardizing Computational Reuse and Portability with the Common Workflow Language

A widely used standard for portable multilingual data analysis pipelines would enable considerable benefits to scholarly publication reuse, research/industry collaboration, regulatory cost control, and to the environment. Published research that used multiple computer languages for their analysis pipelines would include a complete and reusable description of that analysis that is runnable on a diverse set of computing environments. Researchers would be able to easier collaborate and reuse these pipelines, adding or exchanging components regardless of programming language used; collaborations with and within the industry would be easier; approval of new medical interventions that rely on such pipelines would be faster. Time will be saved and environmental impact would also be reduced, as these descriptions contain enough information for advanced optimization without user intervention. Workflows are widely used in data analysis pipelines, enabling innovation and decision-making for the modern society. In many domains the analysis components are numerous and written in multiple different computer languages by third parties. However, lacking a standard for reusable and portable multilingual workflows, then reusing published multilingual workflows, collaborating on open problems, and optimizing their execution would be severely hampered. Moreover, only a standard for multilingual data analysis pipelines that was widely used would enable considerable benefits to research-industry collaboration, regulatory cost control, and to preserving the environment. Prior to the start of the CWL project, there was no standard for describing multilingual analysis pipelines in a portable and reusable manner. Even today / currently, although there exist hundreds of single-vendor and other single-source systems that run workflows, none is a general, community-driven, and consensus-built standard

Lightweight data management with dtool

The explosion in volumes and types of data has led to substantial challenges in data management. These challenges are often faced by front-line researchers who are already dealing with rapidly changing technologies and have limited time to devote to data management. There are good high-level guidelines for managing and processing scientific data. However, there is a lack of simple, practical tools to implement these guidelines. This is particularly problematic in a highly distributed research environment where needs differ substantially from group to group and centralised solutions are difficult to implement and storage technologies change rapidly. To meet these challenges we have developed dtool, a command line tool for managing data. The tool packages data and metadata into a unified whole, which we call a dataset. The dataset provides consistency checking and the ability to access metadata for both the whole dataset and individual files. The tool can store these datasets on several different storage systems, including a traditional file system, object store (S3 and Azure) and iRODS. It includes an application programming interface that can be used to incorporate it into existing pipelines and workflows. The tool has provided substantial process, cost, and peace-of-mind benefits to our data management practices and we want to share these benefits. The tool is open source and available freely online at http://dtool.readthedocs.io

Software publications with rich metadata: state of the art, automated workflows and HERMES concept

To satisfy the principles of FAIR software, software sustainability and software citation, research software must be formally published. Publication repositories make this possible and provide published software versions with unique and persistent identifiers. However, software publication is still a tedious, mostly manual process. To streamline software publication, HERMES, a project funded by the Helmholtz Metadata Collaboration, develops automated workflows to publish research software with rich metadata. The tooling developed by the project utilizes continuous integration solutions to retrieve, collate, and process existing metadata in source repositories, and publish them on publication repositories, including checks against existing metadata requirements. To accompany the tooling and enable researchers to easily reuse it, the project also provides comprehensive documentation and templates for widely used CI solutions. In this paper, we outline the concept for these workflows, and describe how our solution advance the state of the art in research software publication

A Checklist to Publish Collections as Data in GLAM Institutions

Large-scale digitization in Galleries, Libraries, Archives and Museums (GLAM) created the conditions for providing access to collections as data. It opened new opportunities to explore, use and reuse digital collections. Strong proponents of collections as data are the Innovation Labs which provided numerous examples of publishing datasets under open licenses in order to reuse digital content in novel and creative ways. Within the current transition to the emerging data spaces, clouds for cultural heritage and open science, the need to identify practices which support more GLAM institutions to offer datasets becomes a priority, especially within the smaller and medium-sized institutions. This paper answers the need to support GLAM institutions in facilitating the transition into publishing their digital content and to introduce collections as data services; this will also help their future efficient contribution to data spaces and cultural heritage clouds. It offers a checklist that can be used for both creating and evaluating digital collections suitable for computational use. The main contributions of this paper are i) a methodology for devising a checklist to create and assess digital collections for computational use; ii) a checklist to create and assess digital collections suitable for use with computational methods; iii) the assessment of the checklist against the practice of institutions innovating in the Collections as data field; and iv) the results obtained after the application and recommendations for the use of the checklist in GLAM institutions

A checklist to publish collections as data in GLAM institutions

Purpose The purpose of this study is to offer a checklist that can be used for both creating and evaluating digital collections, which are also sometimes referred to as data sets as part of the collections as data movement, suitable for computational use. Design/methodology/approach The checklist was built by synthesising and analysing the results of relevant research literature, articles and studies and the issues and needs obtained in an observational study. The checklist was tested and applied both as a tool for assessing a selection of digital collections made available by galleries, libraries, archives and museums (GLAM) institutions as proof of concept and as a supporting tool for creating collections as data. Findings Over the past few years, there has been a growing interest in making available digital collections published by GLAM organisations for computational use. Based on previous work, the authors defined a methodology to build a checklist for the publication of Collections as data. The authors’ evaluation showed several examples of applications that can be useful to encourage other institutions to publish their digital collections for computational use. Originality/value While some work on making available digital collections suitable for computational use exists, giving particular attention to data quality, planning and experimentation, to the best of the authors’ knowledge, none of the work to date provides an easy-to-follow and robust checklist to publish collection data sets in GLAM institutions. This checklist intends to encourage small- and medium-sized institutions to adopt the collection as data principles in daily workflows following best practices and guidelines

Report on Enhancing Services to Preserve New Forms of Scholarship

This report describes preservation activities, methods, and context for the Enhancing Services to Preserve New Forms of Scholarship project. Digital preservation institutions, libraries, and university presses examined a variety of enhanced digital publications and identified which features can be preserved at scale using tools currently available.The Andrew W. Mellon Foundatio