The biggest change brought about by the “era of big data” to health in general, and epidemiology in particular, relates arguably not to the volume of data encountered, but to its variety. An increasing number of new data sources, including many not originally collected for health purposes, are now being used for epidemiological inference and contextualization. Combining evidence from multiple data sources presents significant challenges, but discussions around this subject often confuse issues of data access and privacy, with the actual technical challenges of data integration and interoperability. We review some of the opportunities for connecting data, generating information, and supporting decision-making across the increasingly complex “variety” dimension of data in population health, to enable data-driven surveillance to go beyond simple signal detection and support an expanded set of surveillance goals.

Get involved in the initiative! The Open Geospatial Consortium (OGC) is issuing this call for participation and collecting proposals for the OGC Water Quality Interoperability Experiment (WQ IE). What’s it about?Clean water is a precious commodity and the basis of life for humans and animals. Contaminated groundwater can negatively impact entire ecosystems. It can be contaminated by bacteria, viruses or chemicals and make people ill. This makes it all the more important to monitor water quality on a regular basis. This is a complex process in which countless data are collected in various systems. In order to be able to react quickly to possible fluctuations in water quality, these systems and databases must be linked together. This is why the OGC is launching the Water Quality IE – WQ IE project. It will drive the development of the WaterML 2.0 suite of standards in the area of water quality data. The WaterML 2.0 standards suite facilitates the exchange of hydrologic data between different organizations, systems, and applications. The Water Quality IE will test the interoperability and connectivity of existing water quality data systems. Participants will identify how to support the development of WaterML 2.0 in the water quality domain. Taxonomies/ontologies related to water quality will be improved and interfaces (APIs) will be found and used. The OGC and the World Meteorological Organization want to develop and recognize an international standard and/or best practice for the exchange of water quality data.Applications of this standard include data exchange between local authorities and regional or national environmental agencies. Specific use cases such as the presentation of regularly collected water samples and measurement results are critical to the success of the IE and will be defined as part of the IE.ParticipationThis IE is open to the public. A requirement for participation is to provide resources. Technical experts from non-OGC organizations may be participants in the IE. Other individuals from non-OGC organizations may participate in the IE as observers. Any OGC member may register as an observer.Participants and observers will join the founding organizations of the IE. The founding organizations are:Bureau de Recherches Géologiques et Minières (BRGM), France.Centro de Investigación Ecológica y Aplicaciones Forestales (CREAF), SpainCenter for Spatial Solutions, Lincoln Institute of Land Policy (CGS), USAFederation University of Australia, AustraliaPole INSIDE – Research Center for Environmental Information Systems, FranceUnited Nations Environment Programme (UNEP) Global Environmental Monitoring System for Freshwater (GEMS/Water) Data Center, GermanyUnited States Geological Survey (USGS), USAUnited States Environmental Protection Agency (USEPA), USAUniversity of Tartu, EstoniaWorld Meteorological Organization (WMO) HydroHubScopeSince 2008, members of the OGC/WMO Hydrology Domain Working Group have been working to develop WaterML 2.0 standards for the transmission of a wide range of water information. Merging water quality data enables better management of water resources and depends on the use of common semantics (vocabularies/taxonomies) and technical scenarios.In addition, water quality data sharing at the global and national levels is currently limited. Common international standards and practices are lacking. In addition, there are different responsibilities between agencies at the national level. Some procedures already exist, mostly on a country-by-country basis (e.g., US WQX, French Sandre, etc.), with the exception of EU environmental water reporting (EU WFD/WISE and EIONET-related reporting). However, in most cases, these practices are not based on current internationally agreed semantic and technical interoperability practices (OGC, W3C, RDA).The establishment of international standards for water quality data will lead to a significant improvement in the availability of water quality information on a global scale. This will allow much more effective development actions to be taken to protect groundwater.The IE will build on the following elements:The experience and data assets available from existing systemsThe OGC Standards Baseline:Semantics: WaterML2.0 standards suite, Observations, Measurements and Samples (OMS),technical: OGC API – Functions, OGC SensorThings API, OGC API – EDR;Early attempts to apply best interoperability practices in this area (e.g., OGC WaterML-WQ Best practice, 14-003, EU API4INSPIRE project, “A Harmonized Vocabulary For Water Quality” DOI:10.13140/RG.2.1.2490.4404)W3C Best Practices: Best Practices for (Spatial) Data on the Web, JSON-LD, SOSA/SSN andThe Research Data Alliance’s (RDA) work on observable properties (I-ADOPT).Participants propose to review existing OGC standards for general use cases for water quality data exchange. Consensus will be reached with a broad community (WMO, RDA, others) on how to express observational and sampling information on water quality.The interoperability experiment will provide an engineering report that identifies opportunities to leverage existing technologies. WaterML2 best practices for water quality will be updated to set the stage for a WMO-supported water quality data exchange standard (including common variables).ObjectivesThe objectives of this IE include the following:Expand and complement the existing work of the HDWG with the goal of advancing the development of the WaterML 2.0 suite of standards for the water quality monitoring subset.Develop a common understanding of the dimensions of interoperability required for key use cases involving water quality data for surface and groundwater.Design and test data exchange mechanisms and vocabularies that meet the needs of participating organizations and systems.Finalize an ER in the form of a best practice or standard, depending on IE results.Improve interoperability between in situ and remotely sensed water quality data.Organizational Use CasesThe following initiatives form the basis for the organizational use cases to be considered in the IE:WMO Hydrologic Observing System Global Data Exchange.WMO Hydrologic Observing System global-scale data exchange.U.S. Water Quality Data Exchange and “Internet of Water”Water quality data portal Uniform data output formatInternational exchange of water quality data in the EUFrench legacy water quality system data made available to research institutionsInteroperability between continuous/sensor data and discrete/sample data.The above high-level organizational use cases provide the general framework for the IE, but ultimately the experiment will address specific water quality use cases. The specific definition of these use cases will be established as the first component of the experiment. Potential water quality use cases include:Surface water chemistry: primarily water sampling and chemical concentrationsHydrobiology and microbiology of surface waters: Occurrence of taxa, calculation of indicesHydromorphology of surface waters: Observation of categories (shape/type of bank, flow “morphology”, etc.)Groundwater chemistry: mainly water sampling and chemical concentrations andGroundwater microbiology: occurrence of taxa, calculation of indices.

Both the public and private sectors rely on intensive data use in the 21st century. While data is everywhere, accessing that data is difficult. Accessing that data then requires permission, the ability to access and receive the data, and finally, the ability to use that data to produce useful information for citizen servicing. Interoperability aims to resolve these challenges by ensuring coordination across different systems. Interoperability in e-Governance is defined as the ability of different systems from various stakeholders to work together, by communicating, interpreting and exchanging the information in a meaningful way. The Republic of Fiji is home to one of the most sophisticated economies in the Pacific Islands. The recent economic shocks triggered by Coronavirus (COVID-19) as well as several rounds of significant tropical weather events between 2020 and 2022 have highlighted critical systematic challenges in Fiji’s Social Protection (SP) system. The Government of Fiji (GoF) has initiated the social assistance policy reform agenda to address these challenges. In parallel, Technical Assistance (TA) was provided to the Ministry of Women, Children and Poverty Alleviation (MWCPA) and the Department of Social Welfare (DSW) by the World Bank, which includes an IT assessment with recommendations for enhancing the Social Protection IT infrastructure in the DSW and the SP sector in the country and a roadmap for the gradual introduction of an Integrated Social Protection Digital Platform (ISPDP) in Fiji. Interoperability is a key enabler of a more adaptive and gender-inclusive social protection system in Fiji.

The global radical interoperability market is projected to expand from USD 13.5 billion in 2023 to USD 43.8 billion by 2030, at a CAGR of 16.9%. Radical interoperability refers to the seamless exchange and sharing of health data between different healthcare systems and devices. It involves overcoming technical, organizational, and regulatory barriers to create a more connected and efficient healthcare ecosystem. The increasing adoption of electronic health records (EHRs), the rising prevalence of chronic diseases, and the growing demand for personalized medicine are key drivers of the radical interoperability market. Additionally, government initiatives and regulations promoting interoperability are also contributing to market growth. However, the lack of standardization, data privacy concerns, and cybersecurity risks pose challenges to market expansion. North America holds the largest share of the market, followed by Europe and Asia-Pacific. Key players in the market include Allscripts Healthcare Solutions, Cerner Corporation, Open Text Corporation, and Epic Corporation.

The report has identified 189 cases using Artificial Intelligence to support/facilitate data interoperability inside the public sector in Europe. These 189 cases are included in this dataset. These 189 cases are out of the 720 AI cases listed in the other dataset published with the same report and linked here after. The dataset is including specific metadata as described in the report. This dataset is associated with the JRC Technical Report "Artificial Intelligence for Interoperability in the European Public Sector: an exploratory study" (JRC134713).

The Electronic Health Records (EHR) market is experiencing robust growth, projected to reach a substantial size, driven by several key factors. The market's Compound Annual Growth Rate (CAGR) of 17.57% from 2019 to 2024 indicates significant expansion, fueled by increasing government mandates for electronic health record adoption, the rising demand for interoperability and data exchange between healthcare providers, and the growing focus on improving patient care through better data management. The shift towards value-based care models further incentivizes EHR adoption, as it enables more efficient tracking of patient outcomes and cost-effectiveness. Cloud-based EHR solutions are gaining significant traction due to their scalability, accessibility, and cost-effectiveness compared to on-premises systems. This trend is further amplified by the increasing adoption of mobile health technologies and telehealth services, which require seamless data integration provided by cloud-based platforms. The market is segmented into deployment (on-premises, cloud-based) and component (services, software, hardware), with the cloud-based and service segments exhibiting the highest growth rates. North America currently holds a dominant market share due to advanced healthcare infrastructure and higher adoption rates, followed by Europe and Asia, where significant growth potential exists. Competitive rivalry among major players like athenahealth, Epic Systems, and McKesson is intense, driving innovation and affordability. However, data security concerns, high implementation costs, and the need for robust technical support remain significant challenges for market expansion. The forecast period (2025-2033) anticipates continued expansion, with the cloud-based segment likely maintaining its leadership position. Growth will be fueled by advancements in Artificial Intelligence (AI) and machine learning applications within EHR systems, enabling predictive analytics, improved diagnostic accuracy, and personalized medicine. Furthermore, the integration of EHRs with other healthcare technologies like wearable devices and remote patient monitoring systems will drive further market expansion. While North America will remain a key market, emerging economies in Asia and the rest of the world present substantial growth opportunities, driven by increasing healthcare spending and government initiatives to modernize healthcare infrastructure. The market's long-term success hinges on addressing challenges related to data interoperability, standardization, and cybersecurity to ensure the seamless flow of patient information and maintain patient privacy and data security.

This is the pseudonymised dataset of the survey titled "Characterising the IIIF and Linked Art communities" that was conducted between 24 March and 7 May 2023. The survey explored the socio-technical characteristics of two prevalent community-driven initiatives in the cultural heritage domain, namely the International Image Interoperability Framework (IIIF) as well as Linked Art. The survey was carried out as part of the PhD Thesis titled "Linked Open Usable Data for Cultural Heritage: Perspectives on Community Practices and Semantic Interoperability" (see https://phd.julsraemy.ch).

The survey report is available at https://hal.science/hal-04162572

The dedicated GitHub repository is available at: https://github.com/julsraemy/loud-socialfabrics/

The Sassen BF1 soil moisture station is part of an agrometeorological test site and aims at supplying environmental data for algorithm development in remote sensing and environmental modelling, with a focus on soil moisture and evapotranspiration.The site is intensively used for practical tests of remote sensing data integration in agricultural land management practices. First measurement infrastructure was installed by DLR in 1999 and instrumentation was intensified in 2011 and later as the site became part of the TERENO-NE observatory. The soil moisture station station Sassen BF1 was installed in 2012. It is located next to a pylon on a crest of an undulating field. The station is equipped with sensor for measuring the following variables: ScemeSpadeSoilMoisture_Spade_2_Temperature, ScemeSpadeSoilMoisture_Spade_6_Temperature, ScemeSpadeSoilMoisture_Spade_1, ScemeSpadeSoilMoisture_Spade_2, ScemeSpadeSoilMoisture_Spade_3, ScemeSpadeSoilMoisture_Spade_4, ScemeSpadeSoilMoisture_Spade_5 and ScemeSpadeSoilMoisture_Spade_6. The current version of this dataset is 1.5. This version includes two additional years of data (from-year to-year)and a revised version of the data flags. New authors were added for this new version: Alice Künzel (GFZ Potsdam), Christian Budach (GFZ Potsdam), Nils Brinckmann (GFZ Potsdam), Max Wegener (DLR Neustrelitz) and Klemens Schmidt (DLR Neustrelitz).A detailed overview on all changes is provided in the station description file. Older versions are available in the 'previous_versions' subfolder via the Data Download link. A first version of this data was provided under http://doi.org/ containing the measured data only. The dataset is also available through the TERENO Data Discovery Portal. The datafile will be extended once per year as more data is acquired at the stations and the metadatafile will be updated. New columns for new variables will be added as necessary. In case of changes in data processing, which will result in changes of historical data, an new Version of this dataset will be published using a new doi. New data will be added after a delay of several months to allow manual interference with the quality control process. During October 2020 a Bug in the published data was detected and a new version of the datasets was released from beginning until mid 2020. Data processing was done using DMRP version: 1.8.4. Metadataprocessing was done using DMETA version: 1.2.0.

According to Cognitive Market Research, the global Data Integration Market size will be USD 15.24 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 12.31% from 2024 to 2031. Key Dynamics of

Data Integration Market

Key Drivers of

Data Integration Market

Explosion of Data Across Disparate Systems: Organizations are producing enormous quantities of data across various platforms such as CRMs, ERPs, IoT devices, social media, and third-party services. Data integration tools facilitate unified access, allowing businesses to obtain comprehensive insights by merging both structured and unstructured data—thereby enhancing analytics, reporting, and operational decision-making.

Demand for Real-Time Business Intelligence: Contemporary enterprises necessitate real-time insights to maintain their competitive edge. Real-time data integration enables the smooth synchronization of streaming and batch data from diverse sources, fostering dynamic dashboards, tailored user experiences, and prompt reactions to market fluctuations or operational interruptions.

Adoption of Hybrid and Multi-Cloud Environments: As organizations embrace a combination of on-premise and cloud applications, the integration of data across these environments becomes essential. Data integration solutions guarantee seamless interoperability, facilitating uninterrupted data flow across platforms such as Salesforce, AWS, Azure, SAP, and others—thereby removing silos and promoting collaboration.

Key Restraints for

Data Integration Market

Complexity of Legacy Systems and Data Silos: Many organizations continue to utilize legacy databases and software that operate with incompatible formats. The integration of these systems with contemporary cloud tools necessitates extensive customization and migration strategies—rendering the process laborious, prone to errors, and demanding in terms of resources.

Data Governance and Compliance Challenges: Achieving secure and compliant data integration across various borders and industries presents significant challenges. Regulations such as GDPR, HIPAA, and CCPA impose stringent requirements on data management, thereby heightening the complexity of system integration without infringing on privacy or compromising sensitive information.

High Cost and Technical Expertise Requirements: Implementing enterprise-level data integration platforms frequently demands considerable financial investment and the expertise of skilled professionals for ETL development, API management, and error resolution. Small and medium-sized enterprises may perceive the financial and talent demands as obstacles to successful adoption.

Key Trends in

Data Integration Market

The Emergence of Low-Code and No-Code Integration Platforms: Low-code platforms are making data integration accessible to non-technical users, allowing them to design workflows and link systems using intuitive drag-and-drop interfaces. This movement enhances time-to-value and lessens reliance on IT departments—making it particularly suitable for agile, fast-growing companies.

AI-Driven Automation for Data Mapping and Transformation: Modern platforms are increasingly utilizing machine learning to automatically identify schemas, propose transformation rules, and rectify anomalies. This minimizes manual labor, improves data quality, and accelerates integration processes—facilitating more effective data pipelines for analytics and artificial intelligence.

Heightened Emphasis on Data Virtualization and Federation: Instead of physically transferring or duplicating data, organizations are embracing data virtualization. This strategy enables users to access and query data from various sources in real time, without the need for additional storage—enhancing agility and lowering storage expenses. Introduction of the Data Integration Market Market

Data Integration Market is the increasing need for seamless access and analysis of diverse data sources to support informed decision-making and digital transformation initiatives. As organizations accumulate vast amounts of data from various systems, applications, and platforms, integrating this data into a unified view becomes crucial. Data integration solutions enable businesses to break down data silos, ensuring consistent, accurate, and real-time data availability...

The size of the Business Metaverse Market was valued at USD 19942.01 million in 2023 and is projected to reach USD 432524.73 million by 2032, with an expected CAGR of 55.20% during the forecast period.The Business Metaverse market has been a transformational force in the way companies engage with each other, collaborate, and operate their activities in virtual environments. This then brings together leading-edge technologies like AR, VR, blockchain, and AI, which are the drivers of immersive digital ecosystems where businesses will be able to simulate real-world operations, improve customer engagement, and make business processes much more efficient. Companies are using these virtual spaces for everything from training employees and collaborating with remote teams to hosting events and displaying products. As more and more digital transformation strategies get adopted, the Business Metaverse is most likely to rise in view of the rapid evolution of technologies, increasing internet penetration, and a growing demand for enhanced virtual experiences. This paper explores the potential of leading industries—retail, health care, manufacturing, and education—for efficiency improvement, cost optimization, and innovation in services. Challenges will remain because high development costs, information security concerns, and regulatory problems still exist. Ongoing R&D investment into these barriers continues to erode them, though. The potential of the Business Metaverse, in creating value and redefining operational models, is so overwhelming that it will surely be a cornerstone of the digital economy. Recent developments include: November 2021: Samsung made an acquisition of the American optics firm DigiLens with the aim of advancing a novel lens iteration named holographic waveguides. This technology boasts a broader Field of View (FoV) compared to other waveguides, signifying a significant enhancement in visual capabilities., January 2024: Futureverse, a prominent company specializing in AI and metaverse technology and content, supported by top-tier investors, reveals its most significant announcement to date. The company introduces Readyverse Studios, a groundbreaking studio co-founded by Shara Senderoff and Aaron McDonald, the Co-Founders of Futureverse, along with Ernest Cline, acclaimed author of the best-selling novel and creator of the innovative franchise Ready Player One, and Dan Farah, the film producer behind Ready Player One. This development marks a notable milestone in Futureverse's endeavors within the AI and metaverse landscape.. Key drivers for this market are: Technical limitations and interoperability issues in XR technologies Data privacy and security concerns related to virtual environments Need for standards and regulations governing metaverse experiences Limited accessibility and affordability of XR devices for mainstream adoption. Potential restraints include: Technical limitations and interoperability issues in XR technologies Data privacy and security concerns related to virtual environments Need for standards and regulations governing metaverse experiences Limited accessibility and affordability of XR devices for mainstream adoption. Notable trends are: Integration of artificial intelligence for personalized experiences and enhanced realism Blockchain-based metaverse platforms for secure and transparent transactions Rise of virtual workspaces and remote collaboration in the metaverse Convergence of physical and digital worlds through extended reality technologies.

A survey and comparative analysis of the technical provision of existing databases that provide for archival of data from molecular biophysics experiments and closely related areas has been carried out. The analysis demonstrates that for many methods provided by MOSBRI there is no specialist provision for data archival such as would adequately satisfy FAIR principles. In particular only a small number of databases containing molecular biophysics derived data use standard data formats with sufficiently rich metadata that enables interoperable data reuse. Where relevant molecular biophysics databases do exist, and in the closely related area of structural biology, there is a clear trend toward complete deposition of the experiment life cycle (i.e., primary experimental data, analysis procedure and interpretation), which will need to be incorporated into plans for the future MOSBRI data repository. The survey also highlights many resources that would have to be linked with any future MOSBRI data repository, to ensure findability and interoperability.

Internet of Things (IoT) Cloud Platform Market AnalysisThe global IoT cloud platform market is estimated to reach $33.58 billion by 2033 from $12.01 billion in 2025, with a compound annual growth rate of 11.52% during the forecast period. This growth would largely be because of the rising adoption of IoT devices, the real-time requirement for processing data, and increased complexity that will happen in IoT deployments.IoT platforms facilitate business in efficient collection, storage, and analysis of data from connected devices in order to help businesses improve their decision-making and operations.In such an instance, leading sectors among the end-users in implementing IoT solutions encompass the automotive and retail, along with manufacturing, healthcare. However, streamlined automation, predictive maintenance, and optimized use of resources ensure significant value across North America and Europe. Here again, with rapidly adapted emerging economy's adoption in the use of IoT technologies, huge growth in smart cities and industrial IoT would be seen together with connected health solution growth.. Recent developments include:

March 2022: T-Mobile, the industry leader in 5G and owner of the biggest and fastest countrywide 5G network in the United States, and Sierra Wireless, an MVNO and supplier of IoT solutions, have expanded their partnership. This will help Sierra Wireless' Smart Connectivity service, which offers worldwide Low Power Wide Area (LPWA) connectivity, become more competitive. As a result of the partnership, consumers in the US now have access to 5G connection from T-multi-band Mobile as well as 4G LTE ultra-high data offerings for fixed applications such as commercial security/video surveillance, healthcare services, digital vending, signs, and others that need high throughput and low latency.

November 2021: To digitally transform and construct sustainable factories of the future, L&T Technology Services Ltd.'s (LTTS) Energy & Sustainability Manager solution will be accessible on Microsoft Azure. The most recent agreement is a part of LTTS' expanding partnership with Microsoft to make its advanced manufacturing solution suite accessible to companies across the globe via Azure's enterprise cloud-first, mobile-first architecture.

. Key drivers for this market are: Increasing adoption of IoT devices Growth of cloud computing Need for data analytics Focus on security and privacy Emergence of new business models. Potential restraints include: Data privacy and security concerns Lack of standards and interoperability Technical complexity High cost of implementation. Notable trends are: Increasing adoption of IoT devices across various industries Growing need for data analytics to improve operational efficiency and decision-making Rise of edge computing and fog computing to reduce latency and improve data processing Focus on security and privacy to protect data and prevent cyberattacks.

The Medical Image Sharing Software market is experiencing robust growth, projected to reach $1318.6 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 6.3% from 2025 to 2033. This expansion is driven by several key factors. The increasing adoption of telehealth and remote patient monitoring necessitates secure and efficient image sharing solutions. Hospitals and healthcare providers are increasingly prioritizing interoperability and streamlined workflows, making medical image sharing software a crucial tool for improved efficiency and reduced operational costs. Furthermore, the rising prevalence of chronic diseases and the growing demand for advanced diagnostic imaging are fueling market growth. Stringent regulatory requirements related to data privacy and security are driving the adoption of sophisticated, compliant software solutions. Technological advancements such as AI-powered image analysis and cloud-based solutions further enhance the market's appeal. Competitive landscape is characterized by a mix of established players like GE Healthcare, Philips, and Siemens Healthineers, alongside innovative startups. This dynamic competition is driving innovation and fostering the development of more user-friendly, feature-rich software. The market segmentation, while not explicitly provided, can be reasonably inferred. The software is likely segmented by deployment mode (cloud-based, on-premise), imaging modality (radiology, cardiology, pathology), and end-user (hospitals, clinics, diagnostic centers). Geographical growth will likely be strongest in regions with developing healthcare infrastructure and increasing adoption of digital health technologies. Potential restraints include concerns about data security breaches, the high initial investment cost of implementation, and the need for ongoing technical support and training. However, the long-term benefits of improved efficiency, enhanced collaboration, and better patient care are expected to outweigh these challenges, contributing to sustained market growth throughout the forecast period.

The Water Data Exchange (WaDE) is a collaborative initiative led by the Western States Water Council (WSWC) aimed at improving the accessibility, interoperability, and standardization of water-related data across western U.S. states. By focusing on water rights, allocation, supply, and usage data, WaDE provides a centralized platform for stakeholders to access critical information needed for regional water management and policymaking.The program emphasizes data-sharing in standardized, machine-readable formats, which enables users to perform analyses and comparisons across state lines. This is particularly important for addressing challenges like drought management, interstate water agreements, and sustainable water resource planning. WaDE also supports collaboration between state agencies, federal entities, and private organizations, fostering an environment of innovation and shared knowledge.In addition to its data exchange capabilities, WaDE provides resources like workshops, technical webinars, and publications to enhance water data literacy and infrastructure. By offering these tools and fostering partnerships, WaDE strengthens the ability of states to manage their water resources effectively, ensuring that they are prepared to meet the demands of both present and future water challenges.

Ethical Data Management

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The phone-based authentication solutions market share is expected to increase by USD 4.98 billion from 2020 to 2025, and the market’s growth momentum will accelerate at a CAGR of 20.59%.

This phone-based authentication solutions market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers phone-based authentication solutions market segmentation by end-user (BFSI, PCI, government, and others) and geography (North America, Europe, APAC, South America, and MEA). The phone-based authentication solutions market report also offers information on several market vendors, including Broadcom Inc., Early Warning Services LLC, Entrust Datacard Corp., Fujitsu Ltd., HID Global Corp., IDEMIA, OneSpan Inc., SecureAuth Corp., Shearwater Group Plc, and Thales Group among others.

What will the Phone-based Authentication Solutions Market Size be During the Forecast Period?

Download the Free Report Sample to Unlock the Phone-based Authentication Solutions Market Size for the Forecast Period and Other Important Statistics

Phone-based Authentication Solutions Market: Key Drivers and Trends

The increasing number of smart connected devices is notably driving the phone-based authentication solutions market growth, although factors such as issues associated with system integration and interoperability may impede the market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the phone-based authentication solutions industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

Key Phone-based Authentication Solutions Market Driver

One of the key factors driving growth in the phone-based authentication solutions market is the increasing number of smart connected devices. The number of smart connected devices across the world is expected to increase during the forecast period. Hence, several organizations are focusing on maintaining, managing, and monitoring data, which will increase the demand for network communications. Education, retail, and BFSI organizations are improving their processes by adopting the Internet of Things (IoT) for analysis. The close monitoring of business processes necessitates the development of effective information security products and services in real-time. Though the use of smartphones improves productivity, it also creates additional risks for an organization's confidential data. Phone-based authentication solutions safeguard sensitive information against malware attacks. The growing number of connected devices increases the need to monitor, manage, and maintain the authenticity of users over the network. Hence, the demand for phone-based authentication solutions will grow during the forecast period.

Key Phone-based Authentication Solutions Market Challenge

The issues associated with system integration and interoperability will be a major challenge for the phone-based authentication solutions market during the forecast period. The increasing adoption of advanced technologies in many industries such as BFSI and telecommunication causes system integration and interoperability issues. Many organizations face integration issues when implementing phone-based authentication solutions. Technical issues during operations can incur costs to the organization and reduce operational efficiency. Technical defects, server errors, and other malfunctions caused by hacking are the key issues associated with phone-based authentication solutions. System integration and interoperability issues arise mostly when organizations update their IT systems or merge their IT infrastructure with their acquired companies. The integration of multiple IT systems on traditional IT infrastructure can create cross-platform system integration issues. Thus, the challenges associated with system integration and interoperability discourage organizations from implementing phone-based authentication solutions.

This phone-based authentication solutions market analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. The actionable insights on the trends and challenges will help companies evaluate and develop growth strategies for 2021-2025.

Who are the Major Phone-based Authentication Solutions Market Vendors?

The report analyzes the market’s competitive landscape and offers information on several market vendors, including:

Broadcom Inc.
Early Warning Services LLC
Entrust Datacard Corp.
Fujitsu Ltd.
HID Global Corp.
IDEMIA
OneSpan Inc.
SecureAuth Corp.
Shearwater Group Plc
Thales Group

This statistical study of the phone-based authentication solutions market encompasses successful

The ckanext-datagovmk extension appears to be designed to customize CKAN for use in a Macedonian government data catalog. It seems to focus on incorporating the Macedonian DCAT Application Profile (mk_dcatap) for metadata and includes support for repeatable fields via ckanext-repeating. This extension likely assists in making CKAN instances compliant with local data standards and interoperable with other systems using DCAT. Key Features: Macedonian DCAT-AP Support: It incorporates the Macedonian DCAT Application Profile (mk_dcatap), suggesting adherence to specific metadata standards relevant to Macedonia. Repeatable Fields: Utilizes ckanext-repeating, enabling datasets to have fields with multiple values, providing richer metadata capabilities. DCAT Standard Compliance: Leverages ckanext-dcat for processing and exporting metadata in accordance with the DCAT standard, facilitating interoperability. Database Initialization: Includes commands to initialize database tables and populate custom tables related to organizations and groups. SMTP Configuration: Provides configuration settings for SMTP, implying email functionality, potentially for notifications or user communications. Technical Integration: The extension requires several other extensions to be installed and configured in a specific order: ckanext-scheming, ckanext-repeating, ckanext-dcat, and ckanext-mk_dcatap. These extensions must be added to the CKAN configuration file (.ini) in the correct order within the ckan.plugins setting. The installation process also involves copying a Solr schema, suggesting customization of the search functionality. Specific paster commands are provided for initializing and populating related database tables. Benefits & Impact: Although not explicitly stated, this extension appears to help national governments provide structured and standardized governmental data catalogs that adhere to national and international data standards. This could lead to improved data discoverability, interoperability, and data exchange with other compliant platforms. Note: The documentation provides limited details regarding the specific features of the extension.

According to Cognitive Market Research, the global Long-term Care Software market size will be USD 5.8 billion in 2024 and will expand at the compound annual growth rate (CAGR) of 9.3% from 2024 to 2031. Market Dynamics of Long-term Care Software Market

Key Drivers for Long-term Care Software Market

Increasing Technological Advancements and Integration - The technological advancements has an important role in driving the long-term care software market. Innovations in cloud computing, artificial intelligence (AI), and telehealth have revolutionized how long-term care facilities operate. Cloud-based solutions offer scalability, flexibility, and remote access to patient data, allowing caregivers to provide timely and accurate care. AI-powered analytics enhance decision-making processes by predicting patient outcomes and identifying potential health risks. Telehealth services have gained prominence, especially during the COVID-19 pandemic, enabling remote consultations and continuous patient monitoring. Integration of long-term care software with other healthcare systems, such as hospital information systems and pharmacy management, ensures seamless data flow and interoperability.
The government initiatives and regulatory compliance are anticipated to drive the Long-term Care Software market's expansion in the years ahead.

Key Restraints for Long-term Care Software Market

The high implementation and maintenance costs can deter the adoption of long-term care software, limiting the Long-term Care Software industry growth.
The market also faces significant difficulties related to limited technical expertise.

Introduction of the Long-term Care Software Market

The Long-term Care Software Market is experiencing notable growth, driven by the surging demand for efficient management systems in care facilities catering to the elderly and chronically ill. This software includes a range of functionalities, including electronic health records (EHR), billing, scheduling, and compliance management, aimed at streamlining operations and improving patient care. As the aging population rises, the need for comprehensive care solutions becomes more critical, propelling the adoption of LTC software. Additionally, the advancements in technology and growing awareness about the benefits of digital solutions in healthcare contribute to market expansion. However, despite these positive trends, the market faces challenges such as high implementation costs and the need for specialized training for staff. Nevertheless, with continuous innovation and supportive government initiatives, the long-term care software market is assured for the significant growth, enhancing the efficiency and quality of care services offered to older people and those with chronic conditions.