Information Management Approaches Research Articles

Ensemble neural models for ICD code prediction using unstructured and structured healthcare data

Disease coding is the process of assigning one or more standardized diagnostic codes to clinical notes that are maintained by health practitioners (e.g. clinicians) to track patient condition. Such a coding process is often expensive and error-prone, as human medical coders primarily perform it. Automating diagnostic coding using Artificial Intelligence is seen as an essential solution in Hospital Information Management Systems and approaches built on Convolutional Neural Networks currently perform best. In this work, a neural model built on unstructured clinical text for enabling automatic diagnostic coding for given patient discharge summaries is proposed. We incorporate a structured self-attention mechanism designed to boost learning of label-specific vectors and the significant clinical text snippets associated with a certain label for this purpose. These vectors are then combined with a novel code description pipeline leveraging the descriptions provided for each standardized diagnostic code. The proposed model achieved best performance in terms of standard metrics over the MIMIC-III dataset, outperforming models based on Longformers and Knowledge graphs. Furthermore, to leverage structured clinical data to enhance the proposed model, and to enable improved diagnostic code prediction, model ensembling is considered. A neural model built on structured data by leveraging supervised machine learning algorithms such as random forest and boosting, is designed for multi-class code classification. Experimental results revealed that the proposed ensemble models show promising performance compared to traditional models that rely solely on unstructured or structured clinical data, emphasizing their suitability for real-world deployment.

Enhancing Open BIM Interoperability: Automated Generation of a Structural Model from an Architectural Model

Building information modelling (BIM) is an appreciated technology in the field of architecture and construction management. Collaboration of information in BIM has not been fully utilized in the structural engineering stream as many engineers keep on working with previous prevailing design approaches. Failure to adequately facilitate automation in design could lead to structural defects, construction rework, or even structural clashes, with major financial implications. Given the inherent complexity of large-scale construction projects, the ‘manual design and detailing’ of structure is a challenging task and prone to human errors. Against this backdrop, this study developed a 4D building information management approach to facilitate automated structural models for professionals designing all the elements required in reinforced concrete (RC) structures like slabs, beams, and columns. The main contribution of this study is to obtain structural models directly from architecture models automatically, which reduces effort and possible errors in the previous prevailing approaches. The framework enables execution of all the model design works automatically through coding. This is achieved by executing a script which is beneficial for integrated project delivery (IPD). The 3D structural model in BIM software presented in this study extracts and transfers the geometrical data and links these data in Industry Foundation Classes (IFC) files using integration facilitated by Python 3.6 and IFCopenshell. The developed automated programme framework offers a cost-effective and accurate methodology to address the limitations and inefficiencies of traditional methods of structural modelling, which had been carried out manually. The authors have developed a novel tool to extract structural models from architectural models without proprietary software, greatly benefiting BIM managers by enhancing 3D BIM models. This advancement toward Open BIM, crucial for the architecture, engineering, and construction (AEC) industry’s future, is accessible to educators and beginners and highlights BIM’s effectiveness in improving structural analysis and productivity. The core finding of this study is to generate a structural model from an architecture model by automating the script with Python integration of IFC and IFCopenshell. The merits of the developed framework are reduced clashes, more economical structural modelling, and fully automated smart work as functions of the IPD.

Shaping Baltimore’s urban forests: past insights for present-day ecology

ContextLand use history of urban forests impacts present-day soil structure, vegetation, and ecosystem function, yet is rarely documented in a way accessible to planners and land managers.ObjectivesTo (1) summarize historical land cover of present-day forest patches in Baltimore, MD, USA across land ownership categories and (2) determine whether social-ecological characteristics vary by historical land cover trajectory.MethodsUsing land cover classification derived from 1927 and 1953 aerial imagery, we summarized present-day forest cover by three land cover sequence classes: (1) Persistent forest that has remained forested since 1927, (2) Successional forest previously cleared for non-forest vegetation (including agriculture) that has since reforested, or (3) Converted forest that has regrown on previously developed areas. We then assessed present-day ownership and average canopy height of forest patches by land cover sequence class.ResultsMore than half of Baltimore City’s forest has persisted since at least 1927, 72% since 1953. About 30% has succeeded from non-forest vegetation during the past century, while 15% has reverted from previous development. A large proportion of forest converted from previous development is currently privately owned, whereas persistent and successional forest are more likely municipally-owned. Successional forest occurred on larger average parcels with the fewest number of distinct property owners per patch. Average tree canopy height was significantly greater in patches of persistent forest (mean = 18.1 m) compared to canopy height in successional and converted forest patches (16.6 m and 16.9 m, respectively).ConclusionsHistorical context is often absent from urban landscape ecology but provides information that can inform management approaches and conservation priorities with limited resources for sustaining urban natural resources. Using historical landscape analysis, urban forest patches could be further prioritized for protection by their age class and associated ecosystem characteristics.

Analysis of the Impact of Globalization Trends in the Digital Economy on Business Management and Administration Systems of Enterprises

Aim. This study aims to investigate the impact of globalization trends on the business management and administration systems. Methodology. The scoping review of the literature included 123 articles through desk research and in-house material. Upon categorizing typologies as qualitative, quantitative, or mixed, an assessment was made regarding the performance and consequences of globalization from 1990 to 2022. Results. Developing country managers are more likely to depend on international sales as a means to augment revenue, due to the greater saturation of sales in developed markets. Developed economies focus on advanced, possibly automated production methods, whereas developing nations employ the digital economy to compete in less automated industries. This creates a more specialized global market..E-commerce in the digital economy makes it easier for developing nations to enter the global market and reach a global audience. In their pursuit of financial gain, corporations based in affluent nations are more likely to employ sophisticated production methods, while those situated in developing countries are more likely to utilize less advanced ones. A number of prevalent issues and trends—including economics, politics, emerging markets, corporate social responsibility, and emerging markets—were recognized as critical for the development of global markets. While past research has focused on globalization's effects on developed economies, this study examines emerging country managers' unique difficulties and opportunities. The emphasis on expanding international sales and potential manufacturing process reduction can inform management approaches in similar situations. Conclusion. The recommendations underscore the critical necessity for further investigation into the aforementioned impacts across diverse economies, ranging from developing to developed. Although this study encountered difficulties due to inconsistent and limited data, it established a strong foundation for subsequent investigations in the field through the application of operationalization, methodologies, and analyses discovered in the business literature.

Smart Factory Hub – Towards a Data Mesh in Smart Manufacturing

The transition of a company towards a data-oriented organisation is a process where several key aspects must be considered. Available data must be readable and interpretable so that useful information can be extracted from it, but also data governance must be implemented with the use of an appropriate information management approach. Handling data at scale is important in this system, as well as ensuring its quality, but also agility and ease of management when new data functionalities have to be developed. New paradigms in the design of analytical architectures have emerged in recent times to respond to these challenges, as is the case of the data mesh concept. This work describes the approach followed in the design of a data information system at Tekniker Research Centre called "Smart Factory Hub" using data mesh principles in the context of a smart manufacturing environment. Decentralisation by use cases, the orientation to data products, or the use of a semantic data catalogue for data discoverability, are some of the foundations used to build this platform to allow the coordination of different teams to create faster insights and value for the organisation.

Integrating Early Warning Systems with Customer Segmentation: An Information Management Approach to Identifying Business Opportunities for Commercial Customers in the Financial Industry

Integrating Early Warning Systems with Customer Segmentation: An Information Management Approach to Identifying Business Opportunities for Commercial Customers in the Financial Industry

Prevalence of Latent Tuberculosis Infection Among Rheumatology Patients and Management Practices in the United Arab Emirates: A Single-Center Retrospective Cohort Study.

Introduction Prior to immunosuppression, rheumatology patients are routinely screened for latent tuberculosis (TB) infection using interferon-gamma release assays (IGRAs). Variability in the management of latent and indeterminate IGRA results across institutionslimited long-term outcome data. A retrospective study was conducted at Tawam Hospital, United Arab Emirates, to investigate the incidence and management protocols associated with positive and indeterminate IGRAresults, as well as TBinfection, among patients with rheumatic conditions. Methods A single-center retrospective observational study was performed at Tawam Hospital, Abu Dhabi, UAE. Ethical approval for this study was obtained from the Tawam Human Research Ethics Committee. Laboratory records and the hospital's electronic medical system were used to obtain information about IGRA results over a 12-year period (April 2010-April 2022). The hospital's electronic medical system was used to obtain patient information and subsequent management approaches of positive and indeterminate IGRAs.Moreover, long-term follow-up data were collected to determine the risk of TB reactivation in the cohort. Results We found a total of 1,012 positive and 223 indeterminate IGRA test results within the 12-year period. Within the rheumatology department, 123 positive and 39 indeterminate IGRA results were identified. In the indeterminate IGRA group, the majority were women (n = 24, 61.5%) and UAE nationals (n = 22, 56.4%), and their mean age was 38.6 years. Systemic lupus erythematosus was the most prevalent rheumatologic condition (n = 21, 53.8%). Thirteen (33.3%) were on disease-modifying anti-rheumatic drugs (DMARDs) and 26 (66.7%) were on corticosteroids during IGRA testing. A total of eight patients (20.5%) received anti-TB medications. In the positive IGRA group, the mean age was 55.7 years and the female-to-male ratio was 3:1. The most common rheumatologic condition was rheumatoid arthritis (n = 69, 56%). Sixty-five (52.8%) patients were on conventional DMARDs, 43 (34.9%) were on corticosteroids during IGRA testing, and 74 (60%) received anti-TB medications. Two cases (1.6%) of active TB infections were detected among patients with positive IGRA tests, both of whom were receiving anti-tumor necrosis factor alpha inhibitor treatment in combination with methotrexate. No cases of active TB infection were observed in the indeterminate IGRA group. Conclusion Long-term data on the risk of TB activation in positive and indeterminate IGRA results for rheumatological conditions are low. It is recommended to reassess the choice of using anti-TNF-α, with a positive IGRA result if no other feasible alternatives can be offered. Our findings stress the importance of age, underlying diseases, and immunosuppressive treatments in interpreting IGRA results and guiding patient management. A large multicenter study is needed to understand the differences and outcomes of such patients in TB endemic and nonendemic geographical areas.

Federated Data Modeling for Built Environment Digital Twins

The digital twin (DT) approach is an enabler for data-driven decision making in architecture, engineering, construction, and operations. Various open data models that can potentially support the DT developments, at different scales and application domains, can be found in the literature. However, many implementations are based on organization-specific information management processes and proprietary data models, hindering interoperability. This article presents the process and information management approaches developed to generate a federated open data model supporting DT applications. The business process modeling notation and transaction and interaction modeling techniques are applied to formalize the federated DT data modeling framework, organized in three main phases: requirements definition, federation, validation and improvement. The proposed framework is developed adopting the cross-disciplinary and multiscale principles. A validation on the development of the federated building-level DT data model for the West Cambridge Campus DT research facility is conducted. The federated data model is used to enable DT-based asset management applications at the building and built environment levels.

How typical is your project? The need for a no-model approach for information management in AEC

This paper discusses the merit of using a no-model approach (no common product models or ontologies, etc.) for managing information in the AEC. It proposes an option for such an approach through the generation and analysis of semantic and social networks of communication between project stakeholders. The proposed approach advocates for a bottom-up discovery of knowledge constructs from stakeholder communication. Knowledge constructs are mini two-mode networks containing, on the one hand, clusters of concepts that appear frequently in the semantic networks of stakeholder communication; and, on the other hand, the social networks of stakeholders discussing these concepts. Using common models (such as IFC) has several limitations, including inflexibility to recognize and accommodate project contexts (which vary constantly), inability to timely capture the emergence of knowledge, and the scope creep problem (the ever-existing need to add more concepts to the common model from within and outside ACE domain). The no-model approach presented here is meant to complement and not replace the established model-based approach. This approach is built on the belief in the ontological agency of project stakeholders: knowledge is a social phenomenon that emerges through interactions between people. It advocates a shift from a top-down format where experts or standards clearinghouses tell (force) practitioners what should be true about their project. In every project, stakeholders customize (the structure of) established knowledge and adopt elements from emerging knowledge to address project-specific needs. They use the more superior intelligence (the human one) to innovate a ‘model of what they know’ to guide the management of the project in a manner specific to its context. By studying projects’ communication, we tell (inform) project stakeholders what knowledge constructs can be found in their communication. Unlike generic/static models, the resulting knowledge constructs are by default sensitive to project conditions. We should re-design our information management systems to be able to recognize and adaptively use the constructs established by project teams to facilitate their sharing of data (along with the established scheme, such as IFC). Relatedly used constructs can be nominated as AEC-wide prototype constructs, representing what we know about a typical project. At the initiation of a new project, these can be the starting scheme used by information and communication systems. As the project evolves and the project's own constructs are generated, the project-specific constructs should guide the flow of information. Contrasting project constructs against prototypes should inform the stakeholders of not only what is factual about their view/model of knowledge, but also how unique are they (from generic/base knowledge). This approach to no-model thinking is advantageous for several reasons. First, addressing the model rigidity problem. Because of the increasing complexity of projects, no single/standardized model can capture all contexts. Second, the increasing need for handling project unstructured data. The proposed approach helps formalize knowledge constructs from such data using network science. Third, recognizing and tracking the evolutionary nature of knowledge. Fourth, supporting innovation: instead of forcing knowers (people) to comply with a static model of reality, the new approach encourages them to imagine new possible futures/ worlds—after all, the true essence of digital twinning is to virtualize futures not just to digitize the present.

Freelance information management agents: why information management is so hard on translational teams.

To conduct high-quality, rigorous research, and advance scientific knowledge, Translational Teams (TTs) engage in information behaviors, including seeking, using, creating, sharing, storing, and retrieving information, in ways specific to the translational context. Currently, little is known about TTs' approach to information management. This qualitative pilot study explored how TTs at the University of Wisconsin-Madison interact with information, as well as the scientific and organizational impact of their interactions. We conducted interviews with ten members of UW TTs. Interviews were transcribed and thematic analysis was conducted. Four themes emerged: (1) TT members did not recognize the centrality of information or information behaviors to their scientific work; (2) TT members engaged in similar information behaviors and used similar tools across disciplines and topics; (3) TT members did not receive support or guidance from their institution in managing information; and (4) Individualized choices of TT members conflicted at the team level, causing confusion and increasing the potential for data and information loss. Acting as freelance information management agents, TT members made individualized decisions about what tools to use and how to use them, often in a piecemeal manner and without communicating these decisions to other team members. Research institutions should both encourage teams to discuss their information management approaches at the beginning of a project and provide leaders with training on how to have these conversations and what topics should be included. Additionally, institutions can provide researchers with guidelines for using software platforms to help mitigate information management challenges.

A digital sustainability approach for effective knowledge and information management in education specific non-profit organizations: Culture Intelligent IS Solutions

Information and knowledge management plays a crucial role in the sustainable development of educational organizations with significant impacts on academic communities ‘behavioral patterns. Leveraging digital technologies into academic processes have been considered as a promising way for effective management of information and knowledge. However, superficial or ungrounded adoption of information systems without consideration of the academic and information culture of a given organization may result in ineffective or useless operations that will subsequently burden staff with irrelevant actions. In this regard, this paper aims to provide an approach for sustainable growth of educational organizations with culturally savvy Information System solutions in information and knowledge management challenges. By this approach, enhanced value systems and a better cycle of information\knowledge among the academic community are intended to be achieved. Stakeholder analysis, objective sampling, and literature review were applied for data collection procedures, which provided ultimate identification of information and academic culture patterns and factors on information and knowledge management. By these patterns and factors, we found effective Information System (IS) solutions that match well with generic features of academic and information cultures in Uzbekistan such as data-driven systems, decision support systems, and discourse analysis. Finally, we have drawn implications for educational institutions to manage information effectively and develop a healthy organizational information environment. Additionally, future research directions will be identified in the digital sustainability domain of effective information and knowledge environment.

Управління бізнес-інформацією та інноваційні підходи до оптимізації бізнес-процесів

The aim of this article is to demonstrate the current state and prospects for the use of innovative technologies for business information management to optimize business processes. The authors analyzed, systematized and generalized scientific works of many scholars, who consider the components of business process management, innovative methods of optimizing business management, which a significant number of companies are still forced to resort to. For a successful optimization, the head of the company needs to find a competent specialist who is familiar with all the complexities of optimization, who is directly participating in the process and personally controls all the actions of the employees involved. Innovative technologies make a fundamental contribution to the transformation of business process structures, business process changes, and modeling according to environmental requirements. Among them, in order to optimize business processes, special attention is paid to the technology of benchmarking the business processes. Benchmarking is an extremely useful tool, especially when it is necessary to review the internal performance of the company and identify new priorities. It is worth remembering that foreign investment also plays an important role in the optimization system. It is determined that the development of innovative technologies and the aggravation of competition require enterprises to effectively manage their processes, provide high-quality products or services and meet the needs of customers. The use of business process management systems can help companies achieve higher efficiency and productivity, reduce costs, improve product or service quality, and improve customer satisfaction. It is worth understanding that the use of innovative technologies should be synchronized with the strategic planning and budget system of the enterprise. It is necessary to create an effective mechanism for managing business processes, taking into account the possibilities and limitations of resources, so that the enterprise can reach a new level of quality. In the future, it is necessary to consider the issue of investment support for the introduction of innovative technologies in the management of business processes of the enterprise.

Board composition and textual attributes of non-financial disclosure in the banking sector: Evidence from the Italian setting after directive 2014/95/EU

More and more, the finance and the financial sector are used as a means of achieving social goals. Thus, the main financial market participants are required to change their ESG identity and to act no longer only as a seller of sustainable products, but also as sustainable actors themselves. For this purpose, banks and financial institutions are required to complement financial information with environmental, social, and governance (ESG) statements to provide a wider overview of the value creation process. Despite the banking sector being of utmost importance in the promotion of a transition towards sustainable economic development, the analysis of the attributes of their non-financial disclosure (NFD) has achieved little attention from scholars thus far. This paper aims at investigating the relationships between board composition and some textual attributes of NFDs by testing the incremental information vs. impression management approach in the Italian banking sector for the years 2017–2020, after the introduction of Directive (2014)/95/EU. The final sample is composed of 29 Italian banks. A two-step analysis was conducted. In the first stage, a content analysis was performed to assess the textual attributes of the disclosures, and in the second a multivariate regression model with panel data was run. Empirical findings found a significant impact of board composition and textual attributes on conciseness, completeness, positive tone, and the reading difficulty of NFDs. Results from this study contribute to the literature on disclosure strategies and theories by providing additional knowledge on the role of certain characteristics of corporate governance in explaining some textual attributes of NFDs in the financial sector. Managerial implications are related to the (re-)design of some governance features which are more suitable in providing a more transparent and comparable NFD. Policy implications are related to the development of policies and regulations at the international level that combine high-quality sustainability-related information and the governance features of financial institutions.

Freshwater microbial metagenomes sampled across different water body characteristics, space and time in Israel

Freshwater bodies are critical components of terrestrial ecosystems. The microbial communities of freshwater ecosystems are intimately linked water quality. These microbes interact with, utilize and recycle inorganic elements and organic matter. Here, we present three metagenomic sequence datasets (total of 182.9 Gbp) from different freshwater environments in Israel. The first dataset is from diverse freshwater bodies intended for different usages – a nature reserve, irrigation and aquaculture facilities, a tertiary wastewater treatment plant and a desert rainfall reservoir. The second represents a two-year time-series, collected during 2013–2014 at roughly monthly intervals, from a water reservoir connected to an aquaculture facility. The third is from several time-points during the winter and spring of 2015 in Lake Kinneret, including a bloom of the cyanobacterium Microcystis sp. These datasets are accompanied by physical, chemical, and biological measurements at each sampling point. We expect that these metagenomes will facilitate a wide range of comparative studies that seek to illuminate new aspects of freshwater microbial ecosystems and inform future water quality management approaches.

Effective Emergency Management: Scrutinizing the Malaysia Lead Responding Agency Planning and Information Management Approach During Disaster Exercise

The impact of a disaster is closely related to the response and recovery of the lead responding agency in managing the disaster effectively. Malaysia has established the MNSC20 policies for managing disasters. Unfortunately, the implementation of MNSC20 can only be evaluated through lead responding agency disaster exercises. Each responding agency’s responsibility is to identify and record the information as required to ensure effective emergency management; however, problems in terms of inaccurate and/or incomplete information may be many challenges that need to be addressed. Hence, this paper aims to propose several areas for improvement for planning and information management elements in effective emergency management theory by identifying its challenges through the FRDM, which may benefit Malaysia’s overall emergency management process. Four disaster exercises at the state and federal levels were observed using a structured checklist. The result indicates challenges were found in terms of proactivity in gaining information, disseminating critical information during emergencies, developing a specific incident action plan, and media management. A good area of improvement is suggested based on the evaluation. It is hoped that this paper could contribute to developing better disaster management by the lead responding agency in Malaysia.

Privacy Management in Service Systems

Problem definition: We study customer-centric privacy management in service systems. Academic/practical relevance: We explore the consequences of extended control over personal information by customers in such systems. Methodology: We adopt a stylized queueing model to capture a service environment that features a service provider and customers who are strategic in deciding whether to disclose personal information to the service provider—that is, customers’ privacy or information disclosure strategy. A customer’s service request can be one of two types, which affects service time but is unknown when customers commit to a privacy strategy. The service provider can discriminate among customers based on their disclosed information by offering different priorities. Results: Our analysis reveals that, when given control over their personal data, strategic customers do not always choose to withhold them. We find that control over information gives customers a tool they can use to hedge against the service provider’s will, which might not be aligned with the interests of customers. More importantly, we find that under certain conditions, giving customers full control over information (e.g., by introducing a privacy regulation) may not only distort already efficiently operating service system but might also backfire by leading to inferior system performance (i.e., longer average wait time), and it can hurt customers themselves. We demonstrate how a regulator can correct information disclosure inefficiencies through monetary incentives to customers and show that providing such incentives makes economic sense in some scenarios. Finally, the service provider itself can benefit from customers being in control of their personal information by enticing more customers joining the service. Managerial implications: Our findings yield insights into how customers’ individually rational actions concerning information disclosure (e.g., granted by a privacy regulation) can lead to market inefficiencies in the form of longer wait times for services. We provide actionable prescriptions, for both service providers and regulators, that can guide their choices of a privacy and information management approach based on giving customers the option of controlling their personal information.

Digitalization as a driver for supporting PV deployment and cost reduction

Digitalization is providing advantages to all sectors around the world and it can be of relevance also for the photovoltaic (PV) sector. As an example, the current value chain of the European PV sector is often characterized by analogue and fragmented processes that should be overcame to support greater PV deployment. The adoption of a more open and collaborative digital-based approach characterized by data-sharing among different stakeholders and more integrated information thread from the design till O&M can provide direct benefits in optimizing the PV process, increasing performances, and reducing of costs. Therefore, a novel PV Information Management (PIM) approach has been drawn within the European H2020 project “SuperPV”. In accordance with PIM objectives, a workflow for seamlessly transferring data along main PV work-stages has been developed, as well as new digital features to specifically address collaborative approach in the PV sector such as: (i) advanced functionalities introduced in the existing BIMSolar® software for improving the simultaneous design, performance simulation and cost assessment of medium and large PV systems, (ii) a proof-of-concept for aggregating all relevant information into a Digital Twin platform aimed at setting the ground for post-construction management and lifecycle assessment of the whole PV system.

An original Data, Information and Knowledge management approach for model-based engineering projects

Data, Information and Knowledge (DIK) problematics are of undeniable growing actuality; many efforts were made to explore and make progress in this domain. Therefore, these DIK have been defined by several characteristics conventionally studied such as volume, variety, variability… and a few solutions have been uncovered and revealed. In parallel, the systems Engineering (SE) and specifically Model-Based Systems Engineering (MBSE) approaches, that encourage, among other things, the use of models instead of documents in critical infrastructure engineering namely in the energy infrastructure domain, participate in the growing volume and complexity of DIK. In this particular context, it is important to enrich MBSE by adapting the existing DIK advances to the MBSE needs, which is initiated in this paper, first by providing DIK definition, second, by checking what are the main issues that shall be solved in order to help stakeholders use and manage them in large MBSE-driven projects, involving various business actors during more or less long periods. At last, this article proposes a methodological contribution bridging the supposed gap between MBSE and so-called data management fields of research.

Heuristic recommendation technique in Internet of Things featuring swarm intelligence approach

In smart environments, traditional information management approaches are often unsuitable to tackle with the needed elaborations due to the amount and the high dynamicity of entities involved. Smart objects (enhanced devices or IoT services belonging to a smart system) interact and maintain relations which need of effective and efficient selection/filtering mechanisms to better meet users’ requirements. Recommender systems provide useful and customized information, properly selected and filtered, for users and services. This paper proposes a heuristic method to build a recommender engine in IoT environment exploiting swarm intelligence techniques. Smart objects are represented using real-valued vectors obtained through the Doc2Vec model, a word embedding technique able to capture the semantic context representing documents and sentences with dense vectors. The vectors are associated to mobile agents that move in a virtual 2D space following a bio-inspired model - the flocking model - in which agents perform simple and local operations autonomously obtaining a global intelligent organization. A similarity rule, based on the assigned vectors, was designed so enabling agents to discriminate among them. A closer positioning (clustering) of only similar agents is achieved. The intelligent positioning allows easy identifying of similar smart objects, thus enabling a fast and effective selection operations. Experimental evaluations have allowed to demonstrate the validity of the approach, and on how the proposed methodology allows obtaining an increasing in performance of about 50%, in terms of clustering quality and relevance, compared to other existing approaches.

Zero trust computing through the application of information asset registers

It is proposed that information asset registers are a key enabler towards the implementation of zero trust computing (ZTC), which requires a detailed knowledge of the information being processed and especially a detailed, well-documented knowledge of the network and technical infrastructure in order to support a zero-trust environment. ZTC also requires detailed documentation to facilitate operational cyber resilience. Asset registers are a key resource to speed up incident response and recovery. Information asset registers are part of the information management, assurance and governance (IMAG) approach. It is proposed the information asset database is at the heart of the information assurance and ZTC ecosystem. This fact has been partially recognised through the Information Technology Infrastructure Library (ITIL) configuration management database (CMDB). We also explore issues related to hybrid infrastructures.