Conference PaperPDF Available

Towards a Harmonized Framework for Vessel Inspection via Remote Techniques

  • World Maritime University-Sasakawa Global Ocean Institute


Remote inspection techniques (RIT) for performing inspections on the steel structure of ships are changing the landscape of ship inspection and hull cleaning. Patently, unmanned aerial vehicles (UAV) perform global visual inspections, ultrasonic thickness measurements and close-up surveys for ships undergoing intermediate and renewal surveys; magnetic crawlers can conduct ultrasonic thickness measurements and perform hull cleaning; remotely operated vehicles (ROV) can perform underwater surveys. Moving forward, efforts to maintain good environmental stewardship, especially at the European Union (EU) level will require not only the seamless integration of RIT, but also a guarantee that all techno-regulatory elements vital the semi-autonomous platform are streamlined into a cohesive policy framework materialized through multi-stakeholder cooperation. The aim of this extended abstract is to present some of the findings from research conducted by the World Maritime University-Sasakawa Global Ocean Institute (GOI) within the framework of the European Union H2020 BugWright2 project. The findings mirrored through this piece derives from research pertaining to: the qualitative assessment of international regime related to ship's safety, environmental control of pollution and survey standards; and comparative analysis from case studies regarding the regulation of robotics covering six leading maritime nations. To this end, discussed herewith are the techno-regulatory elements --- those that bolster support to a harmonized regulatory blueprint for semi-autonomous platforms in the maritime domain.
Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)
Edited by Maria Chiara Leva, Edoardo Patelli, Luca Podofillini, and Simon Wilson
©2022 ESREL2022 Organizers. Published by Research Publishing, Singapore.
doi: 10.3850/978-981-18-5183-4_J03-07-636-cd
Towards a Harmonized Framework for Vessel Inspection via Remote Techniques
Aspasia Pastra
World Maritime University (WMU)-Sasakawa Global Ocean Institute, Sweden. E-mail:
Tafsir Joha nnson
World Maritime University (WMU)-Sasakawa Global Ocean Institute, Sweden, Sweden. E-mail:
Remote inspection techniques (RIT) for performing inspections on the steel structure of ships are changing the
landscape of ship inspection and hull cleaning. Patently, unmanned aerial vehicles (UAV) perform global visual
inspections, ultrasonic thickness measurements and close-up surveys for ships undergoing intermediate and renewal
surveys; magnetic crawlers can conduct ultrasonic thickness measurements and perform hull cleaning; remotely
operated vehicles (ROV) can perform underwater surveys. Moving forward, efforts to maintain good environmental
stewardship, especially at the European Union (EU) level will require not only the seamless integration of RIT, but
also a guarantee that all techno-regulatory elements vital the semi-autonomous platform are streamlined into a
cohesive policy framework materialized through multi-stakeholder cooperation. The aim of this extended abstract
is to present some of the findings from research conducted by the World Maritime University-Sasakawa Global
Ocean Institute (GOI) within the framework of the European Union H2020 BugWright2 project. The findings
mirrored through this piece derives from research pertaining to: the qualitative assessment of international regime
related to ship’s safety, environmental control of pollution and survey standards; and comparative analysis from
case studies regarding the regulation of robotics covering six leading maritime nations. To this end, discussed
herewith are the techno-regulatory elements --- those that bolster support to a harmonized regulatory blueprint for
semi-autonomous platforms in the maritime domain.
Keywords: Remote Inspection Techniques, Ship inspection, Maritime Policy, Drones, Remote Operated Vehicles,
Magnetic Crawlers.
3407Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)
Automated technologies have transfor med the
global economy and industries. The industry is
witnessing a shift from manual assistance to
progressive automaton --- one that could
inevitably lead to full autonomy in the not-so-
distant future. With cascade of innovative
advancements, service robots become smarter,
smaller, and cheaper, paving the way for a service
revolution where service innovations have the
potential to dramatically improve customer
experience, service quality and productivity
(Wirtz and Zeithaml, 2018).
The maritime industry is embracing automation
which may be the pathway forward for the sector
to achieve environmental compliance as well as a
sustainable maritime future. Electrification,
remote technologies, digitalization, and
connectivity have been immersed in a continuous
evolutionary process that converges the sector in
a powerful combination destined to transform the
way the industry moves people and cargo on the
Relevantly, over the last years, several maritime
administrations have approved remote inspection
techniques for inspecting vessels on a case-by-
case basis, and when recognized organizations
(ROs) have had a rationale to endorse that a
specific survey could be conducted remotely.
Remote inspections, as it seems, could be
conducted through UAV, ROV and Magnetic
Crawlers. The demand for unmanned vehicles
capable of replacing traditional manual-based
surveys is increasing as we speak (Nex et al.
Although the global commercial shipping fleet is
rising, reaching 99.800 ships of 100 gross tons
and above, the ageing of the fleet constitutes an
environmental concern since older ships generate
higher emissions (UNCTAD, 2021). RIT has the
potential to contribute substantially to mitigating
hull-fouling through regular cleaning of marine
plants and animals on the submerged structures of
a ship (Alexandropoulou et al. 2021, McClay et
al. 2015). Moreover, shipowners could gain
tremendous annual financial benefits of 190
million euros as the direct and indirect costs (i.e.,
the means of accessibility and the opportunity
cost) are diminishing substantially (Robins,
2021). Other substantial advantages of RIT entail
x Improvement of safety at sea as RIT
minimize dangerous tasks for inspection
personnel, such as entering confined
spaces and working at height;
x Reduction of the number of hours spent
on board by inspection personnel that
might facilitate the operation of the ship;
x Provision of high-quality data and
images, making it easier for ship
operators to follow up on hull
maintenance and create a maintenance
plan that can predict the requirements of
individual vessels;
x Enhancement of the survey report that
inspectors submit to ship
owners/operators by accessing
consolidated data for survey preparation
and reporting; and
x Potential that the increased availability
of digital data will contribute to the
development of other Artificial
Intelligence (AI) models and
applications for improving survey time
and quality.
3408 Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)
Despite the various guidelines issued by the
respective classification societies (i.e., ABS, and
DNV), there are currently no standard agreed-
upon procedures at the international level for the
execution of class and/or statutory surveys by
remo te mea ns . T he i nt e r na ti o na l ma r i ti me RIT
governance framework is fragmented, to say the
least, and shrouded with both grey areas that
impede the integration of RIT alternatives at both
the regional and national levels (Johansson e t al.
The quintuple helix is urged to cooperate at the
international level and adopt both policies that can
stimulate beneficial innova tion, and measures that
could safeguard people from risks emanating
from automated technologies (Smuha, 2021).
Therefore, it is recommended that a new output
on the “development of a blueprint for remote
inspections’’ be added to the work programme of
the S ub-Committee on Imple menta tion of
Inter national Ma ritime Or ga nizati on ( IM O)
Instruments. Against the above backdrop, a set of
strands constituting a regulatory blueprint was
developed by the researchers of the GOI within
the overarching framework of the European
Union H2020 BugWright2 project that aims to
change the European landscape of robotics for
infrastructure inspection and maintenance.
2. Elements Integral to the Regulatory
The focus of the proposed blueprint considers, in
tandem, barriers, dynamic governance, techno-
regulatory rules and requirements, policy
framework i mpacts with regards to service
robotics, mobile platforms and individual RIT. To
that end, researchers have reviewed international
agreements relevant to the ocean tec hnology and
climate change regime, intellectual property
rights, and the certification requirements and
standards pursuant to the International
Organization for Standardization (ISO)
framework. Subsequentl y, a state-of-the-art cross
comparative evaluation on selected case studies
regarding the regulation of robotics in the United
States of America, the Netherlands, Canada,
Norway, China and Singapore has been
conducted with a view to carving out how leading
maritime countries are paving the way to
autonomous operations, more specifically
inspections and cleaning through remote
platforms. To satisfy the goals of the above
evaluation, sixty (60) in-depth interviews
conducted with policymakers, classification
societies and subject matter experts engaged in
the field of automation and remote inspection
All the key take-aways from the two individual
strands of assessment have been carefully
conceptualized to illustrate a set of current needs
in the for m of a draft regulatory blueprint, which
could be fully exploited by concerned regulatory
bodies, as well as national and international
agencies that deal with RIT i n Europe and across
the world. A synthesis of the main elements is
provided in the following section.
2.1 Element one: Stakeholder Cooperation
In the field of autonomy and robotics,
engagement with stakeholders is crucial to
responsible innovation practices (Leenes et al.
2017). Despite asymmetries, RIT calls for a
‘participatory tur n’ of stakeholder involvement
and a continuous process of learning and
Partnerships between and a mong stakeholders are
needed to increase the s uccessful deployment of
RIT. At the governance level, there are non-
human actors that interact with pol icies and
regulations, and participate in effecti ng a
sustainable transformation in relation to RIT
(Johansson et al. 2021). These actors include the
IMO, IACS, various Standard Setting
Organizations and Patent Organizations --- all of
which set the safety, environmental and security
governance framework of shipping. At the
operational level, the human-element includes
manufacturers, service providers, classification
societies, asset owners and insurance companies,
which are directly or indirectly involved in the
application of the policies implemented at the
governance level (Johansson et al. 2021).
A policy regime that can adequately balance out
the different needs of stakeholders could ideally
3409Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)
ensure “trust” in the technology and facilitate its
uptake (Smuha, 2021).
2.2 Element two: Uniform Definitions for
Diffe re nt Rypes of RIT and Degree of
Uniform definitions are the common language for
setting a solid foundation for understanding the
various types, features and limitations of RIT. An
effort to conceptualize RIT has been made by
IACS (2016, Recommendations 42, Section 1.1).
According to the provisions, RIT may include the
‘use of: Divers, Unmanned robot arm, Remote
Operated Vehicles (ROV), Climbers, Drones and
Other means acceptable to the Society’ (IACS,
2016, p.1). Therefore, while a common minimum
standard developed by IACS has been developed,
evide ntl y, no mini mum s ta nda rd d efi ni ti o ns on
UAV, ROV or Crawler are provided. Despite the
amalgamated placement of all types under the
common ter m “Remote Inspection Techniques”,
technological and other differences will stay
discernable since each technique differs in terms
of task, outcomes and environmental conditions
(Johansson et al. 2022).
Another term that should be clarified is one that
relates to ‘close-up survey’, i.e., survey where the
details of structural components are within the
close visual inspection range of the s urveyor and
normally within reach of ha nd. Nowadays.
classification societies approve service suppliers
to p rovi de clos e- up sur ve ys usi ng RIT, s uch as
drones, climbers or remotely operated vehicles
(ROVs). That said, when using RIT, the surveyor
attends the details of the close-up inspection
through a live video stream and the structural
components that are not within hands reach. A
revision of the definition of close-up survey is in
The “degree of autonomy” o f these systems is
also in need of conceptualization. The current
stage of RIT is subject to “supervised autonomy
or “semi-autonomygiven that an operator shall
remotely operate the technology in question. Over
time, RIT might be fully autonomous and capable
of functi oni ng without human i nter ference. The
“degree of autonomy” is a stress on carving out
the level of the autonomous systems in a fashion
similar to what has been done for Maritime
Autonomous Surface Ships (IMO Doc. MSC
100/20/Add. 1, Annex 2). Such a categorization
could help keep track of the adva ncements toward
autonomy, assisting classification societies with
future potential revisions (Johansson et al. 2022).
2.2 Element 3: Proof of Concept
RIT will need to be considered with the objective
of achieving at least equivalency with a traditional
survey, with safety always being the primary
consideration. This verification should be carried
out in controlled environments where repeatable
tests can be performed (Poggi et al. 2020; Pastra
et al. 2022). Classification societies should get
involved in extensive testing and establish the so-
called “proof of concept” to ensure that these
technologies provide safer and even higher -
quality evidence in the survey process whilst
offering equivalent benefits to shipowners and
operators. To boost the rob ustness of these
systems, more test-based statistics and data
comparison is required to prove that the new
technology is adequately safe and reliable for
mass deployment (Pastra et al. 2022). For
example, classification societies should conduct
trial inspections on the same vessel using an ROV
and cross-checking the data gathered against that
which has been obtained by a diver. Cracks
identified by airborne or underwater images
should be compared to traditional counterparts for
further chec k and balance.
2.3 Element 4: Risk Asse ssment Frameworks
During inspections, several safety issues, such as
cleaning, ventilating, lighting and setting up of
structures, are considered before an onboard
survey is initiated (Poggi et al. 2020).
A risk assessment process that includes a flow
chart could assist classification societies in
determining whether a physical inspection is
necessary. A common risk assessme nt framework
for ship eligibility for remote inspection should be
developed based on the age of the vessel, hull
condition, severity of corrosion, type of survey,
areas to be inspected, ship location,
environmental conditions in the area and
approved service suppliers. Classification
societies should consider remote surveys on a
case-by-case basis. If the classification society’s
3410 Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)
risk assessment enables the remote survey, the
organization executing the remote inspection
should conduct another round of risk assessment
to identi fy any po tential hazards to the planned
inspection and subsequently, provide mitigation
measures. This risk assessment should include
risks associated with hazardous areas, payload of
the machine, battery storage, operational
accidents, dropped object risks, collision,
unexpected interruption of the pilot operation and
communication control links (ABS, 2019; CCS,
2.4 Element 5: Data Governance and
“Data governa nce” is deemed as the allocation of
responsibility and shared decision- making over
the manageme nt of data assets (Earley et al.
2017). In other words, data governance concerns
policy-making decisions for corporate data, while
data management is the tactical execution and
monitoring of governance-related decisions
(Khatri and Brown 2010, Johansson e t al. 2021).
A data gover nance framework is essential to set
the processes which safeguard critical data asset
and how they are formally managed throughout
the enterprise and between enterprises (Sarsfield,
2009; Al-Badi et al. 2018).
Good data governance and manageme nt boost
“trustworthiness” within the ecosystem
comprised of technology and the human-element,
i.e., the ship owner, service provider, and
classification societie (Pastra et al. 2022). Clear
terms about data quality, ownership, copyright,
collection, preservation entity, storage, security
measures and data post-processing should be
included in the form of a contract signed by the
ship operator, class society, and service supplier
(Johansson et al. 2021). The roles and
responsibilities related to data ownership, quality,
storage, security and sharing of information
require an in-depth review of all private contracts
developed by service suppliers. What is
conclusive is the need for reliable mechanisms
that ought to be forged by service suppliers to
ensure long-term usability of data and metadata
that belongs to an asset (the ship) that is involved
in commercial activities (Johansson et al. 2021).
2.6 Element 6: The human element
Autonomous RIT will grow in the future broadly
owing to advanced algorithms, collision
avoidance systems, mi niaturization of onboard
sensors and concurrent work in the domains of
robotics and computer vision (Nex et al. 2022).
Nonetheless, at its current stage, inspection using
RIT is conducted in the presence of the attending
surveyor. Human oversight remains as a safety-
net throughout the deployment lifecycle of the
RIT. Ergo, the human-element cannot be ignored.
Human presence is the common denominator in
all existing technologies and until technological
developments reach the stages of “full
autonomy,” human intervention will remain as a
part and parcel of the operational system (Pastra
et al. 2022). The survey inspection procedures,
and most importantly, the training schemes of
surveyors must be adequa tel y aligned to match
the level of sophistication required to carry out
services using respective RITs (Pastra et al.
2.7 Element 7: Safety and Liability
Robots are products ; RIT are products; they are
not “person” or “beings” from an ontoligcal
sense. A legal framework, therefore, should be
applied to govern the usage of products
(Alexandropoulou et al. 2021). In short, products
must be regulated. Risks ranging from dropped
object, collision or lost link, and defective
products, inter alia, call the need to solve RIT-
induced liability issues through existing regional
or national policies (Johansson et al. 2022). RIT
are operated using (battery-produced)
“electricity, which is viewed as a product in
accordance with Article 2 of Directive
85/374/EEC (Johansson et al. 2022). According
to Article 1 of the Directive, the producer shall be
liable for damages caused by a defect in product
so developed. Article 7 of the Directive renders
the producer/manufacturer the opportunity to
resort to the defense mechanism under specific
The Original Equipment Manufacturers (OEMs)
of remote technologies should follow
internationally agreed and accepted requirements
for safe commercial operations (i.e., ISO
3411Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)
Standards). Whether a manufacturer is concretely
liable will depend on relevant international or
industry standards and w hether the product
specifications have successfully followed those
standards. Manufacturers for RIT, during the
design phases should ensure that connectivity will
not directly compro mise data accuracy and safety
of the product. In parallel, manufacturers should
ensure transparency, accountability,
responsibility for all the intelligent information
technological systems they develop. Certified
products according to international standards
should be provided by manufacturers and utilized
by service providers. Service providers should
ensure the safety sta ndards of the equipment,
including hardware and software, during the
selection and maintenance phases. These syste ms
should be rated for their inte nded operational
environment (intrinsically safe in hazardous
areas, operational wind speed, etc.).
The growing degree of autonomy inevitably
raises the question of who is responsible if an RIT
“violates” a contractual obligation; therefore,
clarity is needed with respect to the
responsibilities incurred in connection with the
usage of remote systems. Clear provisions in the
form of a contract should specify the liable party
(manufacturers, developer of the AI system or
pilot of the drone) in different scenarios when a
remote system operated by a pilot crash and
consequently, causes damage. Different scenarios
include but are not limited to collisions with asset
structures and animals, collisions due to
malfunction of the equipment or cases where
visual line of sight ( VLOS) is not maintained.
The service suppliers should secure third-party
public liability insurance and/or professional
indemnity insurance to protect themselves against
legal liability for property damage or injur y.
National flag state authorities, classification
societies and ship owners are steadily adapting to
RIT-based solutions, especially during the
COVID-19 pandemic due to the special
challenges caused by restricting human-presence
on board ships (Johansson et al. 2022). However,
the absence of a uniform international framework
for remote inspections has led to their approval,
and as mentioned before, on a case-by case basis.
Intro d ucing new techno lo gi es in the mari ti me
sector requires the cooperation of various
stakeholders to carry out a comprehensive process
to amend existing instruments or develop new
In the field of robotics, “soft law” approaches and
codes of conduct enhance the level of
acceptability for all the different stakeholders,
increase the chance of self-enforcement and
enable a shift from classic or responsive
regulation to smart regulation ( Lee nes et al .
This paper identifies a framework with seven
main elements that could be taken into
consideration whe n developing a blueprint or
guidelines in the form of Code of Conduct. As
IMO member states are gearing up for dialogue
and discussion for guidelines, it would be worth
considering the basic elements that need
consideration at the international level. These
elements are robust stake holder cooperation,
uniform definitions, extensive testing,
establishment of a risk assessment process, data
governance, human element and liability, serving
as a plinth for regulating maritime robotic and
autonomous systems before unleashing.
Otherwise, full potentials of the system ma y be
impaired due to both foreseen and unforeseen
bottlenecks. The elements discussed in this paper
are consistent with the strategic direction of the
IMO, which aims to implement and enforce the
provisions of its regulatory instruments and
integrate tec hnolo gies withi n its environmental
and safety framework in an effective and efficient
3412 Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)
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Full-text available
The article contributes to the discussion concerning the role of trust in robotic and autonomous systems (RAS), with a sharp focus on remote inspection technologies (RITs) for vessel inspection, survey and maintenance. To this end, the article provides a first-hand insight into one of the major findings from BUGWRIGHT2—a collaborative project co-funded by the European Union’s Horizon 2020 Research and Innovation programme that aims to change the European vessel-structure maintenance landscape. In doing so, this article explores trust from a psychological perspective, reflecting on its characteristics and predictors, followed by a discussion on the AI-trust ecosystem as envisaged by the European Commission. Structured interviews with thirty-three subject matter experts guide the main analysis revealing that trust is an essential precondition for integrating RITs into the current manual-driven inspection system. A synoptic overview of the vital trust elements is provided before carving out the ways forward for developing a trustworthy environment governed by Human-Robot Interaction.
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The use of Unmanned Aerial Vehicles (UAVs) has surged in the last two decades, making them popular instruments for a wide range of applications, and leading to a remarkable number of scientific contributions in geoscience, remote sensing and engineering. However, the development of best practices for high quality of UAV mapping are often overlooked representing a drawback for their wider adoption. UAV solutions then require an inter-disciplinary research, integrating different expertise and combining several hardware and software components on the same platform. Despite the high number of peer-reviewed papers on UAVs, little attention has been given to the interaction between research topics from different domains (such as robotics and computer vision) that impact the use of UAV in remote sensing. The aim of this paper is to (i) review best practices for the use of UAVs for remote sensing and mapping applications and (ii) report on current trends-including adjacent domains-for UAV use and discuss their future impact in photogrammetry and remote sensing. Hardware developments , navigation and acquisition strategies, and emerging solutions for data processing in innovative applications are considered in this analysis. As the number and the heterogeneity of debated topics are large, the paper is organized according to very specific questions considered most relevant by the authors.
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Vessel hull inspection is a regulatory obligation. Adherence to procedural requirements forged by classification societies helps avoid numerous adverse consequences. In this era of technological innovation, drones, crawlers and underwater submersibles, aptly known as Remote Inspection Technologies, represent emerging technologies, and are being tested to conduct surveys and inspections that will gradually replace human presence on board ships and in-water. However, counter arguments have also emerged against the usage of these AI-based alternatives. Liability is one crucial drawback that could potentially discourage innovation and market growth, especially at the European Union level. Ship owners require a ”safety net” as they are a part and parcel of global commerce. Then again, survey and inspection via technologies require the involvement of multiple actors, which makes it difficult to apportion liability. Solutions are required, especially at the European Union level, so that member states could move forward in a spirit of partnership, and nurture and foster technological innovation through partnership. Against the foregoing, this article delves into the European Union liability landscape and outlines some of the critical challenges and strategic ways forward for consideration.
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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.
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The recent explosion in ICT and digital data has led organizations, both private and public, to efficient decision-making. Nowadays organizations can store huge amounts of data, which can be accessible at any time. Big Data governance refers to the management of huge volumes of an organization’s data, exploiting it in the organization’s decision-making using different analytical tools. Big Data emergence provides great convenience, but it also brings challenges. Nevertheless, for Big Data governance, data has to be prepared in a timely manner, keeping in view the consistency and reliability of the data, and being able to trust its source and the meaningfulness of the result. Hence, a framework for Big Data governance would have many advantages. There are Big Data governance frameworks, which guide the management of Big Data. However, there are also limitations associated with these frameworks. Therefore, this study aims to explore the existing Big Data governance frameworks and their shortcomings, and propose a new framework. The proposed framework consists of eight components. As a framework validation, the proposed framework has been compared with the ISO 8000 data governance framework.
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This article integrates relevant literature to develop a conceptual model on the potential avenues to achieve service excellence at low unit costs, which we term cost-effective service excellence (CESE). To gain a deeper understanding of these strategies, their applicability and interrelatedness, we analyze how 10 organizations have achieved CESE. Our findings show that CESE can be achieved through three core strategies. First, a dual culture strategy provides a comprehensive set of high-quality services at low cost, largely driven by leadership ambidexterity and contextual ambidexterity. Second, an operations management approach reduces process variability and thereby allows the increased use of systems and technology to achieve CESE. Third, a focused service factory strategy can enable CESE through a highly specialized operation, typically delivering a single type of service to a highly focused customer segment. The use of the three approaches ranges from “pure” (e.g., mostly pursuing a dual culture strategy) to combinations of the latter two approaches with the dual culture strategy (e.g., a focused service factory strategy combined with dual culture). Our conceptual model provides an integrated view of the strategic options available to organizations that aim to pursue a strategy of CESE.
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Robots are slowly, but certainly, entering people’s professional and private lives. They require the attention of regulators due to the challenges they present to existing legal frameworks and the new legal and ethical questions they raise. This paper discusses four major regulatory dilemmas in the field of robotics: how to keep up with technological advances; how to strike a balance between stimulating innovation and the protection of fundamental rights and values; whether to affirm prevalent social norms or nudge social norms in a different direction; and, how to balance effectiveness versus legitimacy in techno-regulation. The four dilemmas are each treated in the context of a particular modality of regulation: law, market, social norms, and technology as a regulatory tool; and for each, we focus on particular topics – such as liability, privacy, and autonomy – that often feature as the major issues requiring regulatory attention. The paper then highlights the role and potential of the European framework of rights and values, responsible research and innovation, smart regulation and soft law as means of dealing with the dilemmas.
Against a background of global competition to seize the opportunities promised by Artificial Intelligence (AI), many countries and regions are explicitly taking part in a ‘race to AI’. Yet the increased visibility of the technology’s risks has led to ever-louder calls for regulators to look beyond the benefits, and also secure appropriate regulation to ensure AI that is ‘trustworthy’ – i.e. legal, ethical and robust. Besides minimising risks, such regulation could facilitate AI’s uptake, boost legal certainty, and hence also contribute to advancing countries’ position in the race. Consequently, this paper argues that the ‘race to AI’ also brings forth a ‘race to AI regulation’. After discussing the regulatory toolbox for AI and some of the challenges that regulators face when making use thereof, this paper assesses to which extent regulatory competition for AI – or its counterpart, regulatory convergence – is a possibility, a reality and a desirability.
Inspection is a key aspect of any structural maintenance programme, including that of ship and offshore structures with a long-lasting history of service failures. Ship surveys for construction, verification, repair and conversion are intrinsically hazardous that are mainly performed by human surveyors. The ROBINS project (ROBotics technology for INspection of Ships) is an EU Horizon 2020 collaborative project aimed at addressing possible advantages of robotic technologies for ship inspections and facing corresponding challenges. Within the project framework, gaps and drawbacks in the application of robotic technologies were identified, from both technological and regulatory viewpoints. Solutions were suggested and developed through laboratory and field trials. Results indicate that cost-effective robotic assistants can be successfully introduced in the marine structure maintenance routine, if appropriate assessments of technologies and application procedures are carried out in advance according to validation schemes, such as the standard verification process recommended in this paper.
Introduction Organizations are becoming increasingly serious about the notion of "data as an asset" as they face increasing pressure for reporting a "single version of the truth." In a 2006 survey of 359 North American organizations that had deployed business intelligence and analytic systems, a program for the governance of data was reported to be one of the five success "practices" for deriving business value from data assets. In light of the opportunities to leverage data assets as well ensure legislative compliance to mandates such as the Sarbanes-Oxley (SOX) Act and Basel II, data governance has also recently been given significant prominence in practitioners' conferences, such as TDWI (The Data Warehousing Institute) World Conference and DAMA (Data Management Association) International Symposium. The objective of this article is to provide an overall framework for data governance that can be used by researchers to focus on important data governance issues, and by practitioners to develop an effective data governance approach, strategy and design. Designing data governance requires stepping back from day-to-day decision making and focusing on identifying the fundamental decisions that need to be made and who should be making them. Based on Weill and Ross, we also differentiate between governance and management as follows: • Governance refers to what decisions must be made to ensure effective management and use of IT ( decision domains ) and who makes the decisions ( locus of accountability for decision-making ). • Management involves making and implementing decisions. For example, governance includes establishing who in the organization holds decision rights for determining standards for data quality. Management involves determining the actual metrics employed for data quality. Here, we focus on the former. Corporate governance has been defined as a set of relationships between a company's management, its board, its shareholders and other stakeholders that provide a structure for determining organizational objectives and monitoring performance, thereby ensuring that corporate objectives are attained. Considering the synergy between macroeconomic and structural policies, corporate governance is a key element in not only improving economic efficiency and growth, but also enhancing corporate confidence. A framework for linking corporate and IT governance (see Figure 1) has been proposed by Weill and Ross. Unlike these authors, however, we differentiate between IT assets and information assets: IT assets refers to technologies (computers, communication and databases) that help support the automation of well-defined tasks, while information assets (or data) are defined as facts having value or potential value that are documented. Note that in the context of this article, we do not differentiate between data and information. Next, we use the Weill and Ross framework for IT governance as a starting point for our own framework for data governance. We then propose a set of five data decision domains, why they are important, and guidelines for what governance is needed for each decision domain. By operationalizing the locus of accountability of decision making (the "who") for each decision domain, we create a data governance matrix, which can be used by practitioners to design their data governance. The insights presented here have been informed by field research, and address an area that is of growing interest to the information systems (IS) research and practice community.