Abstract
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.
Highlights
Digital data, commonly referred to as data, have a ubiquitous influence in the contemporary information-intensive age, as vast quantities of data are created every second, if not microsecond
Association (DAMA), the term “data governance” is viewed as “the allocation of authority and control and shared decision making over the management of data assets” [21]
It is important to note that the principal concept behind data governance brings to the forefront the need for the comprehension of the inherent dichotomy that lies between personal and non-personal data, since any given data could be a combination of different datasets and transformed into “personal data” in cases where there is processing power and data availability (Mattoo and Meltzer, 2018; Chatzimichali and Chyrostomou, 2019) [26,27]
Summary
Commonly referred to as data, have a ubiquitous influence in the contemporary information-intensive age, as vast quantities of data are created every second, if not microsecond. The term data has found itself being defined in a myriad of ways. It is further observed that each individual definition of data can be characterized as being discipline-oriented. Economy, or law, scholars have put forth respective definitions from the prism, and to the extent, the term data has interacted with the subject matter of respective disciplines [1]. The quintessential definition of data, is found in the common lexicon, i.e., the Cambridge English Dictionary which defines the term as “information, especially facts or numbers, collected to be examined and considered and used to help decision-making, or information in an electronic form that can be stored and used by a computer” [2]. All-embracing in content and ambit, the above definition found in the common lexicon reflects the essence of the varying definitions, to all intents, construction, and purposes, propounded by various subject matter experts, e.g., Senn (1982), Clare and Loucopoulos (1987), and Avison and Fitzgerald (1995) [3,4,5]
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