The First Provenance Challenge

The first Provenance Challenge was set up in order to provide a forum for the community to help understand the capabilities of different provenance systems and the expressiveness of their provenance representations. To this end, a Functional Magnetic Resonance Imaging workflow was defined, which participants had to either simulate or run in order to produce some provenance representation, from which a set of identified queries had to be implemented and executed. Sixteen teams responded to the challenge, and submitted their inputs. In this paper, we present the challenge workflow and queries, and summarise the participants contributions

Crossing the Line - sustainability and large object conservation in musuems and heritage collections

Large working objects pose significant challenges for the heritage sector. The primary issues are concerned with interpretation, conservation and authenticity but underpinning all of these is the issue of sustainability. Decision making in large object conservation has always revolved around the tension between using it and losing it, or storing it and seeing it decay through neglect. An additional challenge is authenticity. At what point does an object lose its authenticity? How many replacement parts, panels or new paint jobs does it take to reduce an object to a construct? This paper examines these challenges in order to explore a set of ideas that will allow a sustainable approach to large working object conservation in museums and heritage collections to be developed. It will use as a basis for analysis and discussion ground breaking conservation projects at the Fleet Air Arm Museum in Yeovilton in the UK

Streamlining governmental processes by putting citizens in control of their personal data

Governments typically store large amounts of personal information on their citizens, such as a home address, marital status, and occupation, to offer public services. Because governments consist of various governmental agencies, multiple copies of this data often exist. This raises concerns regarding data consistency, privacy, and access control, especially under recent legal frameworks such as GDPR. To solve these problems, and to give citizens true control over their data, we explore an approach using the decentralised Solid ecosystem, which enables citizens to maintain their data in personal data pods. We have applied this approach to two high-impact use cases, where citizen information is stored in personal data pods, and both public and private organisations are selectively granted access. Our findings indicate that Solid allows reshaping the relationship between citizens, their personal data, and the applications they use in the public and private sector. We strongly believe that the insights from this Flemish Solid Pilot can speed up the process for public administrations and private organisations that want to put the users in control of their data

Sustainable Development Report: Blockchain, the Web3 & the SDGs

This is an output paper of the applied research that was conducted between July 2018 - October 2019 funded by the Austrian Development Agency (ADA) and conducted by the Research Institute for Cryptoeconomics at the Vienna University of Economics and Business and RCE Vienna (Regional Centre of Expertise on Education for Sustainable Development).Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc

Sustainable Development Report: Blockchain, the Web3 & the SDGs

This is an output paper of the applied research that was conducted between July 2018 - October 2019 funded by the Austrian Development Agency (ADA) and conducted by the Research Institute for Cryptoeconomics at the Vienna University of Economics and Business and RCE Vienna (Regional Centre of Expertise on Education for Sustainable Development).Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc

Scientific Workflow Repeatability through Cloud-Aware Provenance

The transformations, analyses and interpretations of data in scientific workflows are vital for the repeatability and reliability of scientific workflows. This provenance of scientific workflows has been effectively carried out in Grid based scientific workflow systems. However, recent adoption of Cloud-based scientific workflows present an opportunity to investigate the suitability of existing approaches or propose new approaches to collect provenance information from the Cloud and to utilize it for workflow repeatability in the Cloud infrastructure. The dynamic nature of the Cloud in comparison to the Grid makes it difficult because resources are provisioned on-demand unlike the Grid. This paper presents a novel approach that can assist in mitigating this challenge. This approach can collect Cloud infrastructure information along with workflow provenance and can establish a mapping between them. This mapping is later used to re-provision resources on the Cloud. The repeatability of the workflow execution is performed by: (a) capturing the Cloud infrastructure information (virtual machine configuration) along with the workflow provenance, and (b) re-provisioning the similar resources on the Cloud and re-executing the workflow on them. The evaluation of an initial prototype suggests that the proposed approach is feasible and can be investigated further.Comment: 6 pages; 5 figures; 3 tables in Proceedings of the Recomputability 2014 workshop of the 7th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2014). London December 201