Enabling Industrial Data Space Architecture for Seaport Scenario

Industrial data ecosystems are inter-organizational forms of cooperation emerging around sharing data. They arise from a digital infrastructure, giving data providers and data users a platform to share and (re-)use data. Data spaces are among the digital infrastructures frequently associated with data ecosystems, as they supply a shared digital space for its participants to share data in a sovereign way. Data spaces aim to close a gap in the digital infrastructure landscape, addressing concerns of organizations when sharing data, such as data misappropriation or a lack of control of shared data. They do this by implementing data sovereignty—typically through Usage Control Policies—that give data providers the means to formalize semantically and technically how data users are allowed to use their data. In this fundamentals article, we address the following issues: (1) contextualizing and demarcating data spaces and data ecosystems, (2) systematizing data spaces in the research and policy landscape, and (3) elaborating on a research agenda for Information Systems (IS) research.

GeoNode is a web-based application and platform for developing geospatial information systems (GIS) and for deploying spatial data infrastructures (SDI).The World Bank, the European Commission and the UN World Food Programme are among the major contributors and sustainers of the GeoNode project and they are using it for spatial data sharing and management projects.Being extremely active in the field of Humanitarian Crisis and Risk Reduction they have deployed custom GeoNode instances to support risk reduction and post crisis need assessment.During this talk three customized GeoNode instances will be presented, focusing the attention on their technology, usage for emergency preparedness and response, their federation and the added value provided by Open Source technologies for geospatial data sharing.

The availability of large and complex data sets has shifted the focus of pattern recognition toward developing techniques that can efficiently handle these types of data sets. Multiple classifier systems have the promise of reducing the error and complexity by partitioning the data space and combining classifier predictions. However, difficulties arise in ways of generating these various partitions and using them effectively. In this paper, several methods of partitioning is studied and compared, by examining implicit and explicit sharing of the training patterns among multiple classifiers. We implemented several partitioning techniques using random and a more intelligent approach, clustering, to obtain more insight into the effect of shared and disjoint data representation across the training subsets. Improved classification accuracy suggests that implicit sharing of training patterns is always beneficial, while explicit sharing is useful for small size training data.

Poland is characterised by a relatively high variety of living organisms attributed to terrestrial and water environments. Currently, close to 57.000 species of living organisms are described that occur in Poland (Symonides 2008), including lowland and mountain species, those attributed to oceanic and continental areas, as well as species from forested and open habitats. Poland comprehensively represents biodiversity of living organisms on a continental scale and thus, is considered to have an important role for biodiversity maintenance. The Mammal Research Institute of Polish Academy of Sciences (MRI PAS), located in Białowieża Forest, a UNESCO Heritage Site, has been collecting biodiversity data for 90 years. However, a great amount of data gathered over the years, especially old data, is gradually being forgotten and hard to access. Old catalogues and databases have never been digitalized or publicly shared, and not many Polish scientists are aware of the existence of such resources, not to mention the rest of the scientific world. Recognizing the need for an online, interoperable platform, following FAIR data principles (findable, accessible, interoperable, reusable), where biodiversity and scientific data can be shared, MRI PAS took a lead in creation of an Open Forest Data (OFD) repository. OpenForestData.pl (Fig. 1) is a newly created (2020) digital repository, designed to provide access to natural sciences data and provide scientists with an infrastructure for storing, sharing and archiving their research outcomes. Creating such a platform is a part of an ongoing development of life sciences in Poland, aiming for an open, modern science, where data are published as free-access. OFD also allows for the consolidation of natural science data, enabling the use and processing of shared data, including API (Application Programming Interface) tools. OFD is indexed by the Directory of Open Repositories (OpenDOAR) and Registry of Research Data Repositories (re3data). The OFD platform is based entirely on reliable, globally recognized open source software: DATAVERSE, an interactive database app which supports sharing, storing, exploration, citation and analysis of scientific data; GEONODE, a content management geospatial system used for storing, publicly sharing and visualising vector and raster layers, GRAFANA, a system meant for storing and analysis of metrics and large scale measurement data, as well as visualisation of historical graphs at any time range and analysis for trends; and external tools for database storage (Orthanc) and data visualisation (Orthanc plugin Osimis Web Viewer and Online 3D Viewer (https://3dviewer.net/), which were integrated with the system mechanism of Dataverse. Furthermore, according to the need for specimen description, Darwin Core (Wieczorek et al. 2012) metadata schema was decided to be the most suitable for specimen and collections description and mapped into a Dataverse additional metadata block. The use of Darwin Core is based on the same file format, the Darwin Core Archive (DwC-A) which allows for sharing data using common terminology and provides the possibility for easy evaluation and comparison of biodiversity datasets. It allows the contributors to OFD to optionally choose Darwin Core for object descriptions making it possible to share biodiversity datasets in a standardized way for users to download, analyse and compare. Currently, OFD stores more than 10.000 datasets and objects from the collections of Mammal Research Institute of Polish Academy of Sciences and Forest Science Institute of Białystok University of Technology. The objects from natural collections were digitalized, described, catalogued and made public in free-access. OFD manages seven types of collection materials: 3D and 2D scans of specimen in Herbarium, Fungarium, Insect and Mammal Collections, images from microscopes (including stereoscopic and scanning electron microscopes), morphometric measurements, computed tomography and microtomography scans in Mammal Collection, mammal telemetry data, satellite imagery, geospatial climatic and environmental data, georeferenced historical maps. 3D and 2D scans of specimen in Herbarium, Fungarium, Insect and Mammal Collections, images from microscopes (including stereoscopic and scanning electron microscopes), morphometric measurements, computed tomography and microtomography scans in Mammal Collection, mammal telemetry data, satellite imagery, geospatial climatic and environmental data, georeferenced historical maps. In the OFD repository, researchers have the possibility to share data in standardized way, which nowadays is often a requirement during the publishing process of a scientific article. Beside scientists, OFD is designed to be open and free for students and specialists in nature protection, but also for officials, foresters and nature enthusiasts. Creation of the OFD repository supports the development of citizen science in Poland, increases visibility and access to published data, improves scientific collaboration, exchange and reuse of data within and across borders.

We study the General Data Protection Regulation (GDPR)’s opt-in requirement in a model with a firm that provides a digital service and consumers who are heterogeneous in their valuations of the firm’s service and the privacy costs incurred when sharing personal data with the firm. We show that the GDPR boosts demand for the service by allowing consumers with high privacy costs to buy the service without sharing data. The increased demand leads to a higher price but a smaller quantity of shared data. If the firm’s revenue is largely usage based rather than data based, then both the firm’s profit and consumer surplus increase after the GDPR, implying that the GDPR can be welfare improving. But if the firm’s revenue is largely from data monetization, then the GDPR can reduce the firm’s profit and consumer surplus. This paper was accepted by D. J. Wu, information systems. Funding: The authors gratefully acknowledge financial support from the Australian Research Council [Grant DP210102015], the Japan Society for the Promotion of Science [KAKENHI Grants JP20H05631, JP21H00702, JP21K01452, JP21K18430, JP23H00818, JP23K20593, and JP23K25515], the Nomura Foundation, the International Joint Research Promotion Program at Osaka University, and the program of the Joint Usage/Research Center for “Behavioral Economics” at the ISER, Osaka University. Although N. Matsushima serves as a member of the Competition Policy Research Center at the Japan Fair Trade Commission (JFTC), the views expressed in this paper are solely ours and should not be attributed to the JFTC. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2024.06653 .

Security of Organizations' Information Systems (IS) and the Auditors: A Schematic Study

Information security is one of the key areas of consideration to assure reliable and dependable information systems (IS). Achieving an appropriate level of IS security requires concurrent consideration of the technical aspects of IS and the human aspects related to the end users of IS. These aspects can be described in the form of information security requirements. We propose an approach that helps select and balance information security software requirements (iSSR) and information security training requirements (iSTR) according to the information security performance of end users. The approach was tested in an experiment involving 128 IS professionals. The results showed that using the proposed approach helps IS professionals with limited experience in information security make significantly better decisions regarding iSSR and iSTR.

PurposeThe initiative to develop integrated information systems (IIS) for the construction industry has been a strategic focus in various countries. However, the absence of a framework to plan, develop and manage IS has led to various challenges and prevented these IIS from achieving their objectives. The purpose of this paper is to propose the conceptual framework of IIS for the Indonesian construction industry.Design/methodology/approachData were collected through a questionnaire survey and then validated through the focus group discussion conducted by 14 experts whom we selected rigorously. The content and descriptive analyses were adopted to determine the level of importance and concerns for each component and factor expressed by respondents.FindingsThe conceptual framework of IIS for the Indonesian construction industry consists of five components: business environment, organization environment, information systems (IS) integration, alignment of IS with business and impact on organization or industry. By integrating business and organization environments, IS integration and alignments with business and impact, the framework offers a comprehensive systems approach to IS integration that is both practical and theoretically sound.Originality/valueThe paper offers a perspective on IIS in developing countries, focusing on Indonesia. This study provides valuable insights for construction practitioners to understand the implications of IS integration and serves as a tool to design and develop more effective information technology (IT) solutions. Additionally, it aids governmental bodies in formulating policies to support the Integrated Construction Services Information System (ICSIS) program to realize the Indonesian One Data Initiative (IODI).

Cloud Storage services are increasingly adopted by users to outsource their data. These services tend essentially to synchronize data across user's devices and to share them between different users. Two issues raise when dealing with synchronizing shared data. First, synchronizing data that are already encrypted by users to multiple destinations may clearly introduce key and access control management challenges. Second, it is essential to deal with the states constrains of the owner and the consumer. In fact, neither the owner who shared the data nor the consumer are usually connected at the same time. In the context of probative value storage of sensitive data, we focus mainly on the security requirements while considering a timely-file sharing. The shared data are synchronized for the legitimate user only for a specified period of time. A Synchronization Protocol for Digital Safe (SyncDS) is proposed and the Attribute Based Encryption (CP-ABE) is adapted to meet the data sharing requirements. In fact, a formal security validation is provided to demonstrate the safety of the proposed protocol. In addition, an implementation of the timely-file sharing is performed on the CP-ABE toolkit and integrated into the digital safe synchronization framework.

Use of CYP3Ai and impact on outcomes in patients with acute myeloid leukemia treated with venetoclax plus azacitidine in the VIALE-A study.

The European Commission has a program to accelerate the Digital Transition and is putting forward a vision based on cloud, common European Data Spaces and AI. As the data space paradigm unfolds across Europe, the Green Deal Data Space emerges. Its foundational pillars are to be built by the GREAT project. Data Spaces will be built over federated data infrastructures with common technical requirements (where possible) taking into account existing data sharing initiatives. Services and middleware developed to enable a federation of cloud-to-edge capacities will be at the disposal of all data spaces.GREAT, the Green Deal Data Space Foundation and its Community of Practice, has the ambitious goal of defining how data with the potential to help combat climate and environmental related challenges, in line with the European Green Deal, can be shared more broadly among many stakeholders, sectors and boundaries, according to European values such as fair access, privacy and security. The project will consider and incorporate community defined requirements and use case analyses to ensure that the resulting data space infrastructure is designed and built with and for the users. An implementation roadmap will guide the efforts of multiple actors to converge toward a blueprint technical architecture, a data governance scheme that enables innovative business cases, and an inventory of high value datasets, that will enable proof of concept, implementation and scale-up of a minimum viable green deal data space.This roadmap will identify the resources and other key ingredients needed for the Green Deal Data Space to be successful. Data sharing by design and data sovereignty are some of the main principles that will apply from the early stages ensuring cost effective and sustainable infrastructures that will drive Europe towards a single data market and green economic growth. This talk will present how to engage with the project, the design methodology, progress towards the roadmap for deployment and the collaborative approach to building data spaces in conjunction with all the sectoral data spaces and the Data Space Support Centre.

Evaluation of information systems in the health domain goes beyond exclusively technological considerations but also includes evaluation of human and organizational dimensions. The information system evaluation model frequently health used is called HOT-Fit (Human Organization Technology-Fit). This model considers the complex interactions between human, organizational, and technological elements in the context of health information systems. This research aims to analyze the implementation of the Laboratory Information System using the HOT Fit method at the Maxima Clinical Laboratory. The research method used is quantitative with a cross-sectional research design using a survey approach. Research subjects include laboratory managers, laboratory staff, information system users, and patients. Primary data was collected through questionnaires and interviews, while secondary data was obtained from related documents. The data analysis technique used is descriptive analysis and Partial Least Square ( PLS ). The research results show that there is a significant influence between system quality (p-value = 0.041), information quality (p-value = 0.003), service quality (p-value = 0.003), and user satisfaction (p-value = 0.041). Research findings can be used as evaluation and improvement material for laboratory managers to increase the effectiveness and efficiency of health services by optimizing the use of information systems.

The deployment of Share Data Spaces in open, possibly hostile, environments arises the need of protecting the confidentiality of the data space content. Existing approaches focus on access control mechanisms that protect the data space from untrusted agents. The basic assumption is that the hosts (and their administrators) where the data space is deployed have to be trusted. Encryption schemes can be used to protect the data space content from malicious hosts. However, these schemes do not allow searching on encrypted data. In this paper we present a novel encryption scheme that allows tuple matching on completely encrypted tuples. Since the data space does not need to decrypt tuples to perform the search, tuple confidentiality can be guaranteed even when the data space is deployed on malicious hosts (or an adversary gains access to the host). Our scheme does not require authorised agents to share keys for inserting and retrieving tuples. Each authorised agent can encrypt, decrypt, and search encrypted tuples without having to know other agents' keys. This is beneficial inasmuch as it simplifies the task of key management. An implementation of an encrypted data space based on this scheme is described and some preliminary performance results are given.

There are many methodologies that have been proposed in the literature for identifying the security and privacy requirements that must be satisfied by an information system in order to protect its users. At the same time, there are several “privacy principles” that have been considered as equally important for the avoidance of privacy violation incidents. However, to the best of our knowledge, there is no methodology that can cover both the identification of the security and privacy requirements and at the same time to take into account the main privacy principles. The consequence is that the designers of an information system usually follow an ad hoc approach for the identification of security/privacy requirements, thus failing to protect users in an effective way. This paper introduces the main idea behind a methodology that integrates the basic steps of well-established risk analysis methodologies with those of methodologies used for the identification of privacy requirements, considering, at the same time, the most well-known privacy principles. The proposed methodology aims to assist information system designers to come up with a complete and accurate list of all security and privacy requirements that must be satisfied by the system.

Contemporary information systems (IS) development within organizations involves multiple interconnected systems, a variety of development practices and also outsources responsibilities to third parties. It hence introduces new threats, new vulnerabilities and in consequence new security problems for the IS. In this paper we propose a theoretical framework to facilitate the implementation of secure IS into this contemporary, particularly complex, organisational environment. We start our study by examining organisational and systems development issues, such as the involved stakeholders and their security requirements. We then relate this theory to practice by identifying all those concepts that materialise the stakeholders' security understanding to specific security objectives and the tools in which they are manifested. Finally, we inspect various published cases in order to examine the use of these tools within organisations, so as to realise our theoretical design and prescribe its further use.