Maritime Robotics and Autonomous Systems Operations: Exploring Pathways for Overcoming International Techno-Regulatory Data Barriers

The current regulatory landscape that applies to maritime service robotics, aptly termed as robotics and autonomous systems (RAS), is quite complex. When it comes to patents, there are multifarious considerations in relation to vessel survey, inspection, and maintenance processes under national and international law. Adherence is challenging, given that the traditional delivery methods are viewed as unsafe, strenuous, and laborious. Service robotics, namely micro aerial vehicles (MAVs) or drones, magnetic-wheeled crawlers (crawlers), and remotely operated vehicles (ROVs), function by relying on the architecture of the Internet of Robotic Things. The aforementioned are being introduced as time-saving apparatuses, accompanied by the promise to acquire concrete and sufficient data for the identification of vessel structural weaknesses with the highest level of accuracy to facilitate decision-making processes upon which temporary and permanent measures are contingent. Nonetheless, a noticeable critical issue associated with RAS effective deployment revolves around non-personal data governance, which comprises the main analytical focus of this research effort. The impetus behind this study stems from the need to enquire whether “data” provisions within the realm of international technological regulatory (techno-regulatory) framework is sufficient, well organized, and harmonized so that there are no current or future conflicts with promulgated theoretical dimensions of data that drive all subject matter-oriented actions. As is noted from the relevant expository research, the challenges are many. Engineering RAS to perfection is not the end-all and be-all. Collateral impediments must be avoided. A safety net needs to be devised to protect non-personal data. The results here indicate that established data decision dimensions call for data security and protection, as well as a consideration of ownership and liability details. An analysis of the state-of-the-art and the comparative results assert that the abovementioned remain neglected in the current international setting. The findings reveal specific data barriers within the existing international framework. The ways forward include strategic actions to remove data barriers towards overall efficacy of maritime RAS operations. The overall findings indicate that an effective transition to RAS operations requires optimizing the international regulatory framework for opening the pathways for effective RAS operations. Conclusions were drawn based on the premise that policy reform is inevitable in order to push the RAS agenda forward before the emanation of 6G and the era of the Internet of Everything, with harmonization and further standardization being very high priority issues

A Holistic Framework for Complex Big Data Governance

Big data assets are large datasets that can be leveraged by organisations if the capabilities exist, but it also brings considerable challenges. Despite the benefits that can be realised, the lack of proper big data governance is a major barrier, making the processing and control of this data exceptionally difficult to execute correctly. More specifically, organisations reportedly struggle to incorporate big data governance into their existing structures and business models to derive value from big data initiatives. Big data governance is an emerging research domain, gaining attention from both Information Systems scholars and the practitioner community. Nonetheless, there appears to have been limited scientific research in the area and most existing data governance approaches were limited, given they do not address end-to-end aspects of how big data could be governed. Furthermore, no suitable framework for handling data governance against big data complexities was found to be available. Thus, the main contribution of the work presented in this thesis is to address this requirement; by advancing research in this field and designing a novel holistic big data governance framework capable of supporting global organisations to effectively manage big data as an asset, thereby obtaining value from their big data initiatives. An extensive systematic literature review was done in order to uncover the published content that reflects the current state of knowledge in big data governance. To facilitate the creation of the proposed framework a grounded theory methodology was used to analyse openly available parliamentary inquiry data sources, with particular focus on identifying the core criteria for big data governance. The resulting novel framework generated provides new knowledge by identifying several big data governance building blocks; which are classified as strategic goals, execution stages, enablers and 22 core big data governance components to ensure an effective big data governance programme. Moreover, thesis findings indicate that big data complexities extend to the ethical side of big data governance and this is taken into consideration in the framework design. An ‘ethics by design’ component is proposed to influence how this can be addressed in a structured way