Towards a Framework for Open Data Related Innovation Contests

Open data is considered as a promising resource for innovation, in particular in light of the ongoing digitization of society and economy. Currently, organizations lack of knowledge and skills to make efficient use of this resource. Based on the theoretical underpinning of absorptive capacity, the paper investigates how organizations could be supported by using open data for innovation. Following the design science research paradigm, a morphological box for open data related innovation contests is designed by means of an extensive literature review as well as an empirical investigation of an academic analytics challenge. The resulting artifact guides the design of open data related innovation contests by illustrating the main design elements and their options

Hackathons and Libraries: The Evolving Landscape 2014-2020

Libraries foster a thriving campus culture and function as “third space,” not directly tied to a discipline. Libraries support both formal and informal learning, have multipurpose spaces, and serve as a connection point for their communities. For these reasons, they are an ideal location for events, such as hackathons, that align with library priorities of outreach, data and information literacy, and engagement focused on social good. Hackathon planners could find likely partners in either academic or public libraries as their physical spaces accommodate public outreach events and many are already providing similar services, such as makerspaces. Libraries can act solely as a host for events or they can embed in the planning process by building community partnerships, developing themes for the event, or harnessing the expertise already present in the library staff. This article, focusing on years from 2014 to 2020, will highlight the history and evolution of hackathons in libraries as outreach events and as a focus for using library materials, data, workflows, and content.Publisher allows immediate open acces

Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections

Digital archives are transforming the Humanities and the Sciences. Digitized collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digital Humanities have moved from the fringe to the center of academia. Yet, the path from the appraisal of records to their analysis is far from smooth. This book explores crossovers between various disciplines to improve the discoverability, accessibility, and use of born-digital archives and other cultural assets

Archives, Access and Artificial Intelligence

Digital archives are transforming the Humanities and the Sciences. Digitized collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digital Humanities have moved from the fringe to the center of academia. Yet, the path from the appraisal of records to their analysis is far from smooth. This book explores crossovers between various disciplines to improve the discoverability, accessibility, and use of born-digital archives and other cultural assets

Archives, Access and Artificial Intelligence

Digital archives are transforming the Humanities and the Sciences. Digitized collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digital Humanities have moved from the fringe to the center of academia. Yet, the path from the appraisal of records to their analysis is far from smooth. This book explores crossovers between various disciplines to improve the discoverability, accessibility, and use of born-digital archives and other cultural assets

NEMISA Digital Skills Conference (Colloquium) 2023

The purpose of the colloquium and events centred around the central role that data plays today as a desirable commodity that must become an important part of massifying digital skilling efforts. Governments amass even more critical data that, if leveraged, could change the way public services are delivered, and even change the social and economic fortunes of any country. Therefore, smart governments and organisations increasingly require data skills to gain insights and foresight, to secure themselves, and for improved decision making and efficiency. However, data skills are scarce, and even more challenging is the inconsistency of the associated training programs with most curated for the Science, Technology, Engineering, and Mathematics (STEM) disciplines. Nonetheless, the interdisciplinary yet agnostic nature of data means that there is opportunity to expand data skills into the non-STEM disciplines as well.College of Engineering, Science and Technolog

Marine Data Fusion for Analyzing Spatio-Temporal Ocean Region Connectivity

This thesis develops methods to automate and objectify the connectivity analysis between ocean regions. Existing methods for connectivity analysis often rely on manual integration of expert knowledge, which renders the processing of large amounts of data tedious. This thesis presents a new framework for Data Fusion that provides several approaches for automation and objectification of the entire analysis process. It identifies different complexities of connectivity analysis and shows how the Data Fusion framework can be applied and adapted to them. The framework is used in this thesis to analyze geo-referenced trajectories of fish larvae in the western Mediterranean Sea, to trace the spreading pathways of newly formed water in the subpolar North Atlantic based on their hydrographic properties, and to gauge their temporal change. These examples introduce a new, and highly relevant field of application for the established Data Science methods that were used and innovatively combined in the framework. New directions for further development of these methods are opened up which go beyond optimization of existing methods. The Marine Science, more precisely Physical Oceanography, benefits from the new possibilities to analyze large amounts of data quickly and objectively for its exact research questions. This thesis is a foray into the new field of Marine Data Science. It practically and theoretically explores the possibilities of combining Data Science and the Marine Sciences advantageously for both sides. The example of automating and objectifying connectivity analysis between marine regions in this thesis shows the added value of combining Data Science and Marine Science. This thesis also presents initial insights and ideas on how researchers from both disciplines can position themselves to thrive as Marine Data Scientists and simultaneously advance our understanding of the ocean