Making It Up as We Go Along: How We Built Our Digital Collections Platform

Wayne State University Libraries is currently implementing a new digital collections interface based around Fedora Commons, the open-source digital repository software. Consequently, we have learned much about interface design, workflow management, evaluating pre-existing tools and systems, as well as building and using APIs to our advantage. At this session, we will explore these topics, as we share knowledge gained from our project, including lessons learned, failures lamented, victories celebrated. Let our insights help you to build your own digital collections platform

Unremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processes

Clinical decision support tools (DST) promise improved healthcare outcomes by offering data-driven insights. While effective in lab settings, almost all DSTs have failed in practice. Empirical research diagnosed poor contextual fit as the cause. This paper describes the design and field evaluation of a radically new form of DST. It automatically generates slides for clinicians' decision meetings with subtly embedded machine prognostics. This design took inspiration from the notion of "Unremarkable Computing", that by augmenting the users' routines technology/AI can have significant importance for the users yet remain unobtrusive. Our field evaluation suggests clinicians are more likely to encounter and embrace such a DST. Drawing on their responses, we discuss the importance and intricacies of finding the right level of unremarkableness in DST design, and share lessons learned in prototyping critical AI systems as a situated experience

Computerization of workflows, guidelines and care pathways: a review of implementation challenges for process-oriented health information systems

There is a need to integrate the various theoretical frameworks and formalisms for modeling clinical guidelines, workflows, and pathways, in order to move beyond providing support for individual clinical decisions and toward the provision of process-oriented, patient-centered, health information systems (HIS). In this review, we analyze the challenges in developing process-oriented HIS that formally model guidelines, workflows, and care pathways. A qualitative meta-synthesis was performed on studies published in English between 1995 and 2010 that addressed the modeling process and reported the exposition of a new methodology, model, system implementation, or system architecture. Thematic analysis, principal component analysis (PCA) and data visualisation techniques were used to identify and cluster the underlying implementation ‘challenge’ themes. One hundred and eight relevant studies were selected for review. Twenty-five underlying ‘challenge’ themes were identified. These were clustered into 10 distinct groups, from which a conceptual model of the implementation process was developed. We found that the development of systems supporting individual clinical decisions is evolving toward the implementation of adaptable care pathways on the semantic web, incorporating formal, clinical, and organizational ontologies, and the use of workflow management systems. These architectures now need to be implemented and evaluated on a wider scale within clinical settings

A Survey on Evaluation Factors for Business Process Management Technology

Estimating the value of business process management (BPM) technology is a difficult task to accomplish. Computerized business processes have a strong impact on an organization, and BPM projects have a long-term cost amortization. To systematically analyze BPM technology from an economic-driven perspective, we are currently developing an evaluation framework in the EcoPOST project. In order to empirically validate the relevance of assumed evaluation factors (e.g., process knowledge, business process redesign, end user fears, and communication) we have conducted an online survey among 70 BPM experts from more than 50 industrial and academic organizations. This paper summarizes the results of this survey. Our results help both researchers and practitioners to better understand the evaluation factors that determine the value of BPM technology

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1-the summer 2015 and winter 2016 growing seasons-of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project's goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs

Report of the user requirements and web based access for eResearch workshops

The User Requirements and Web Based Access for eResearch Workshop, organized jointly by NeSC and NCeSS, was held on 19 May 2006. The aim was to identify lessons learned from e-Science projects that would contribute to our capacity to make Grid infrastructures and tools usable and accessible for diverse user communities. Its focus was on providing an opportunity for a pragmatic discussion between e-Science end users and tool builders in order to understand usability challenges, technological options, community-specific content and needs, and methodologies for design and development. We invited members of six UK e-Science projects and one US project, trying as far as possible to pair a user and developer from each project in order to discuss their contrasting perspectives and experiences. Three breakout group sessions covered the topics of user-developer relations, commodification, and functionality. There was also extensive post-meeting discussion, summarized here. Additional information on the workshop, including the agenda, participant list, and talk slides, can be found online at http://www.nesc.ac.uk/esi/events/685/ Reference: NeSC report UKeS-2006-07 available from http://www.nesc.ac.uk/technical_papers/UKeS-2006-07.pd

Lessons Learned from a Decade of Providing Interactive, On-Demand High Performance Computing to Scientists and Engineers

For decades, the use of HPC systems was limited to those in the physical sciences who had mastered their domain in conjunction with a deep understanding of HPC architectures and algorithms. During these same decades, consumer computing device advances produced tablets and smartphones that allow millions of children to interactively develop and share code projects across the globe. As the HPC community faces the challenges associated with guiding researchers from disciplines using high productivity interactive tools to effective use of HPC systems, it seems appropriate to revisit the assumptions surrounding the necessary skills required for access to large computational systems. For over a decade, MIT Lincoln Laboratory has been supporting interactive, on-demand high performance computing by seamlessly integrating familiar high productivity tools to provide users with an increased number of design turns, rapid prototyping capability, and faster time to insight. In this paper, we discuss the lessons learned while supporting interactive, on-demand high performance computing from the perspectives of the users and the team supporting the users and the system. Building on these lessons, we present an overview of current needs and the technical solutions we are building to lower the barrier to entry for new users from the humanities, social, and biological sciences.Comment: 15 pages, 3 figures, First Workshop on Interactive High Performance Computing (WIHPC) 2018 held in conjunction with ISC High Performance 2018 in Frankfurt, German

DIDET: Digital libraries for distributed, innovative design education and teamwork. Final project report

The central goal of the DIDET Project was to enhance student learning opportunities by enabling them to partake in global, team based design engineering projects, in which they directly experience different cultural contexts and access a variety of digital information sources via a range of appropriate technology. To achieve this overall project goal, the project delivered on the following objectives: 1. Teach engineering information retrieval, manipulation, and archiving skills to students studying on engineering degree programs. 2. Measure the use of those skills in design projects in all years of an undergraduate degree program. 3. Measure the learning performance in engineering design courses affected by the provision of access to information that would have been otherwise difficult to access. 4. Measure student learning performance in different cultural contexts that influence the use of alternative sources of information and varying forms of Information and Communications Technology. 5. Develop and provide workshops for staff development. 6. Use the measurement results to annually redesign course content and the digital libraries technology. The overall DIDET Project approach was to develop, implement, use and evaluate a testbed to improve the teaching and learning of students partaking in global team based design projects. The use of digital libraries and virtual design studios was used to fundamentally change the way design engineering is taught at the collaborating institutions. This was done by implementing a digital library at the partner institutions to improve learning in the field of Design Engineering and by developing a Global Team Design Project run as part of assessed classes at Strathclyde, Stanford and Olin. Evaluation was carried out on an ongoing basis and fed back into project development, both on the class teaching model and the LauLima system developed at Strathclyde to support teaching and learning. Major findings include the requirement to overcome technological, pedagogical and cultural issues for successful elearning implementations. A need for strong leadership has been identified, particularly to exploit the benefits of cross-discipline team working. One major project output still being developed is a DIDET Project Framework for Distributed Innovative Design, Education and Teamwork to encapsulate all project findings and outputs. The project achieved its goal of embedding major change to the teaching of Design Engineering and Strathclyde's new Global Design class has been both successful and popular with students