Consumer behavior has changed due to digitization. Online shoppers now refer to user reviews containing comprehensive data produced in real-time, which can be used to determine users’ needs. This paper combines Kansei engineering and natural language processing techniques to extract information on users’ needs from online reviews and provide guidance for subsequent product improvements and development. A crawler tool was used to collect a large number of online reviews for a target product. Frequency analysis was then applied to the text to filter out the product components worth analyzing. The results were categorized and aggregated by experts before sentiment analysis was performed on statements containing the selected adjectives. Finally, the user needs identified could be inputted to Kansei engineering for further product design. This paper verifies the merit of the above method when applied to the mountain bike product category on Amazon. The method proved to be a quick and efficient way to attain accurate product evaluations from end-users and thus represents a feasible approach to intelligently determining user preferences.

Online Graphic Design Software Market 2025: Projected to hit USD 16.59B by 2029 at 11.3% CAGR. Access in-depth analysis on trends, market dynamics, and competitive landscape for data-driven decisions.

This dataset contains data collected during a study ("Towards High-Value Datasets determination for data-driven development: a systematic literature review") conducted by Anastasija Nikiforova (University of Tartu), Nina Rizun, Magdalena Ciesielska (Gdańsk University of Technology), Charalampos Alexopoulos (University of the Aegean) and Andrea Miletič (University of Zagreb)
It being made public both to act as supplementary data for "Towards High-Value Datasets determination for data-driven development: a systematic literature review" paper (pre-print is available in Open Access here -> https://arxiv.org/abs/2305.10234) and in order for other researchers to use these data in their own work.

The protocol is intended for the Systematic Literature review on the topic of High-value Datasets with the aim to gather information on how the topic of High-value datasets (HVD) and their determination has been reflected in the literature over the years and what has been found by these studies to date, incl. the indicators used in them, involved stakeholders, data-related aspects, and frameworks. The data in this dataset were collected in the result of the SLR over Scopus, Web of Science, and Digital Government Research library (DGRL) in 2023.

***Methodology***

To understand how HVD determination has been reflected in the literature over the years and what has been found by these studies to date, all relevant literature covering this topic has been studied. To this end, the SLR was carried out to by searching digital libraries covered by Scopus, Web of Science (WoS), Digital Government Research library (DGRL).

These databases were queried for keywords ("open data" OR "open government data") AND ("high-value data*" OR "high value data*"), which were applied to the article title, keywords, and abstract to limit the number of papers to those, where these objects were primary research objects rather than mentioned in the body, e.g., as a future work. After deduplication, 11 articles were found unique and were further checked for relevance. As a result, a total of 9 articles were further examined. Each study was independently examined by at least two authors.

To attain the objective of our study, we developed the protocol, where the information on each selected study was collected in four categories: (1) descriptive information, (2) approach- and research design- related information, (3) quality-related information, (4) HVD determination-related information.

***Test procedure***
Each study was independently examined by at least two authors, where after the in-depth examination of the full-text of the article, the structured protocol has been filled for each study.
The structure of the survey is available in the supplementary file available (see Protocol_HVD_SLR.odt, Protocol_HVD_SLR.docx)
The data collected for each study by two researchers were then synthesized in one final version by the third researcher.

***Description of the data in this data set***

Protocol_HVD_SLR provides the structure of the protocol
Spreadsheets #1 provides the filled protocol for relevant studies.
Spreadsheet#2 provides the list of results after the search over three indexing databases, i.e. before filtering out irrelevant studies

The information on each selected study was collected in four categories:
(1) descriptive information,
(2) approach- and research design- related information,
(3) quality-related information,
(4) HVD determination-related information

Descriptive information
1) Article number - a study number, corresponding to the study number assigned in an Excel worksheet
2) Complete reference - the complete source information to refer to the study
3) Year of publication - the year in which the study was published
4) Journal article / conference paper / book chapter - the type of the paper -{journal article, conference paper, book chapter}
5) DOI / Website- a link to the website where the study can be found
6) Number of citations - the number of citations of the article in Google Scholar, Scopus, Web of Science
7) Availability in OA - availability of an article in the Open Access
8) Keywords - keywords of the paper as indicated by the authors
9) Relevance for this study - what is the relevance level of the article for this study? {high / medium / low}

Approach- and research design-related information
10) Objective / RQ - the research objective / aim, established research questions
11) Research method (including unit of analysis) - the methods used to collect data, including the unit of analy-sis (country, organisation, specific unit that has been ana-lysed, e.g., the number of use-cases, scope of the SLR etc.)
12) Contributions - the contributions of the study
13) Method - whether the study uses a qualitative, quantitative, or mixed methods approach?
14) Availability of the underlying research data- whether there is a reference to the publicly available underly-ing research data e.g., transcriptions of interviews, collected data, or explanation why these data are not shared?
15) Period under investigation - period (or moment) in which the study was conducted
16) Use of theory / theoretical concepts / approaches - does the study mention any theory / theoretical concepts / approaches? If any theory is mentioned, how is theory used in the study?

Quality- and relevance- related information
17) Quality concerns - whether there are any quality concerns (e.g., limited infor-mation about the research methods used)?
18) Primary research object - is the HVD a primary research object in the study? (primary - the paper is focused around the HVD determination, sec-ondary - mentioned but not studied (e.g., as part of discus-sion, future work etc.))

HVD determination-related information
19) HVD definition and type of value - how is the HVD defined in the article and / or any other equivalent term?
20) HVD indicators - what are the indicators to identify HVD? How were they identified? (components & relationships, “input -> output")
21) A framework for HVD determination - is there a framework presented for HVD identification? What components does it consist of and what are the rela-tionships between these components? (detailed description)
22) Stakeholders and their roles - what stakeholders or actors does HVD determination in-volve? What are their roles?
23) Data - what data do HVD cover?
24) Level (if relevant) - what is the level of the HVD determination covered in the article? (e.g., city, regional, national, international)

***Format of the file***
.xls, .csv (for the first spreadsheet only), .odt, .docx

***Licenses or restrictions***
CC-BY

For more info, see README.txt

User Experience UX Research Software Market size was valued at USD 22.20 Million in 2023 and is projected to reach USD 77.70 Million by 2031, growing at a CAGR of 22.5% during the forecast period 2024-2031.

Global User Experience UX Research Software Market Drivers

The market drivers for the User Experience UX Research Software Market can be influenced by various factors. These may include:

Several market drivers contribute to the growth and expansion of the User Experience (UX) Research Software Market. Here are some of the key drivers:

Increasing Emphasis on Customer-Centric Approaches: Businesses are increasingly recognizing the importance of delivering exceptional user experiences to retain customers and maintain a competitive edge. This focus drives demand for UX research tools to better understand user behavior and preferences.

Growing Digital Transformation: As more companies embark on digital transformation journeys, there’s a rising need for effective UX research tools to ensure that the digital products and services being developed meet user expectations.

Rising Use of Mobile and Web Applications: The proliferation of mobile and web applications necessitates robust UX research to ensure usability and user satisfaction. This drives the demand for comprehensive UX research software.

Competitive Market Landscape: In highly competitive industries, companies strive to differentiate their products and services through superior user experiences. Effective UX research becomes a critical component of product development and marketing strategies.

Advancements in Technology: The development of new technologies, such as artificial intelligence (AI) and machine learning (ML), improves the capabilities of UX research software, making it more powerful and accessible. These advancements drive adoption rates.

Increased Awareness and Training: Growing awareness about the importance of UX design and the availability of more educational resources and training programs in UX research contribute to the broader adoption of UX research tools.

Regulatory and Compliance Requirements: In some industries, regulatory requirements mandate user feedback and usability testing, boosting the need for specialized UX research software to ensure compliance.

Cost Efficiency and ROI: Effective UX research can lead to significant cost savings by identifying potential issues early in the product development lifecycle, reducing the need for expensive post-launch fixes, and improving the overall return on investment (ROI).

Data-Driven Decision Making: Organizations are increasingly relying on data-driven insights to make informed decisions. UX research software provides detailed analytics and user feedback that support this approach.

Shift Toward Remote Work and Collaboration: The rise of remote work has revolutionized how teams collaborate on UX projects. UX research software that supports remote usability testing and collaboration has seen increased demand.

Consumer Demand for Personalization: Consumers expect personalized experiences, which necessitates in-depth UX research to tailor products and services to individual preferences and behaviors.

Expansion of E-Commerce: The growing e-commerce sector requires optimized user experiences to ensure high conversion rates and customer satisfaction, driving the adoption of UX research software. These drivers indicate a robust growth trajectory for the UX Research Software Market, as more organizations prioritize delivering exceptional user experiences and leverage advanced tools to achieve this goal.

According to Cognitive Market Research, the global Wireframe Tools market size is USD XX million in 2024. It will expand at a compound annual growth rate (CAGR) of 20.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 18.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD XX million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 22.5% from 2024 to 2031.
Latin America had a market share for more than 5% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 19.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 20.2% from 2024 to 2031.
The significant wireframe tools market segment by type is windows.

Market Dynamics of Wireframe Tools market

Key Drivers for Wireframe Tools market

Integration of AI and machine learning capabilities for enhanced prototyping and user testing

The integration of AI and machine learning (ML) capabilities in wireframe tools represents a significant advancement in enhancing prototyping and user testing processes. AI can analyze vast amounts of data to provide insights into user behavior, preferences, and interactions with prototypes. This data-driven approach enables designers to create more intuitive and user-friendly interfaces.ML algorithms can automate aspects of prototyping by generating design suggestions based on patterns identified from user data, thus speeding up the iterative design process. Additionally, AI-powered tools can simulate user interactions more accurately, predicting how users might navigate through an application or website, which aids in refining usability and functionality. Moreover, AI and ML enable dynamic adjustments to prototypes in real-time based on user feedback, improving the overall user experience.

Growing emphasis on accessibility and inclusivity in design, driving tool development for diverse user needs.

The growing emphasis on accessibility and inclusivity in design reflects a crucial shift towards ensuring digital products are usable by all individuals, including those with disabilities. This movement has spurred tool development in wireframing and design to accommodate diverse user needs. Designers are increasingly integrating features that cater to different abilities, such as screen readers for visually impaired users, keyboard navigation for those with motor impairments, and color contrast adjustments for users with low vision. Tools now offer accessibility guidelines and templates to help designers create interfaces that comply with accessibility standards like WCAG (Web Content Accessibility Guidelines). This trend not only supports ethical and legal considerations but also enhances user satisfaction and engagement across broader demographics.

Restraint Factor For The Wireframe Tools Market

Security concerns related to cloud-based wireframe tools and data privacy

Security concerns related to cloud-based wireframe tools and data privacy revolve around potential vulnerabilities in data transmission and storage. Storing sensitive design prototypes and user data on cloud servers raises fears of unauthorized access, data breaches, or leaks, compromising intellectual property and user confidentiality. Moreover, reliance on third-party cloud service providers introduces risks of service outages or data loss, impacting project timelines and continuity. Ensuring robust encryption protocols, compliance with data protection regulations like GDPR, and implementing strict access controls are critical to mitigate these risks. Despite the convenience and collaboration benefits of cloud-based tools, addressing these security concerns remains paramount to maintaining trust and safeguarding sensitive information in digital design workflows.

Impact of Covid-19 on the Wireframe Tools Market

The Covid-19 pandemic significantly influenced the wireframe tools market by accelerating the adoption of remote work and digital collaboration. With...

The global digital marketing consultancy market is experiencing robust growth, projected to be valued at $555.3 million in 2025. While the provided CAGR is missing, considering the rapid evolution of digital technologies and the increasing reliance of businesses on data-driven marketing strategies, a conservative estimate of the Compound Annual Growth Rate (CAGR) between 2025 and 2033 would be around 12%. This signifies a substantial expansion of the market, driven by factors such as the growing adoption of digital channels across diverse industries, the increasing need for specialized digital marketing expertise, and the rising demand for data analytics and performance measurement in marketing campaigns. The market is segmented by service type (SEO, PPC, Social Media Marketing, Web Design, and Others) and by client application (Small and Medium Enterprises (SMEs) and Large Enterprises). Large enterprises typically drive higher spending due to their greater marketing budgets and complex digital strategies, while SMEs represent a larger volume of clients seeking cost-effective solutions. Geographical distribution shows a significant concentration in North America and Europe, with Asia-Pacific exhibiting strong growth potential owing to increasing internet penetration and digitalization. Key players such as WPP Group, Publicis Groupe, and Omnicom Group dominate the landscape, although several mid-sized and niche consultancies are also making significant contributions. The market's growth is tempered by factors such as increasing competition, fluctuations in the global economy and the constant need for consultancies to adapt to evolving digital marketing trends and technologies. The projected market value for 2033, based on a 12% CAGR from the 2025 base, would be approximately $1,850 million, reflecting a substantial increase over the decade. This growth is expected to be fueled by continued innovation in areas like artificial intelligence (AI) in marketing, the rise of influencer marketing and the increasing sophistication of data analytics techniques used to improve campaign effectiveness. The competition is expected to intensify, with both established giants and new entrants vying for market share. Success will hinge on the ability of consultancies to offer specialized expertise, demonstrate strong ROI for clients, and adapt quickly to the ever-changing landscape of the digital marketing world.

According to Cognitive Market Research, the global Software Development market size will be USD 403615.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 11.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 161446.20 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 121084.65 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 92831.57 million in 2024 and will grow at a compound annual growth rate (CAGR) of 13.5% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 20180.78 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 8072.31 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.2% from 2024 to 2031.
BFSI sector is the dominant category in the Software Development Market due to the significant investment these institutions make in digital solutions to enhance their services

Market Dynamics of Software Development Market

Key Drivers for Software Development Market

Increasing Adoption of Cloud-Based Solutions to Boost Market Growth

The growing adoption of cloud-based solutions is a major driver in the Software Development Market. As businesses shift to cloud environments for their scalability, flexibility, and cost-effectiveness, the demand for cloud-based software development has surged. Cloud platforms allow organizations to deploy software applications with ease, reduce infrastructure costs, and scale resources on-demand. This trend is particularly beneficial for startups and small businesses, enabling them to access advanced software tools without heavy upfront investments. Moreover, the seamless integration of cloud-based applications across various devices and systems further accelerates the demand for software developers specializing in cloud-based solutions. For instance, October 2023, The ESDS Software Solution launched a low-code platform called "Low Code Magic." The platform redefines the application development landscape, making it faster, easier, and more efficient for businesses to create custom applications tailored to their needs

Integration of Artificial Intelligence and Machine Learning to Drive Market Growth

The integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies into software development is creating significant opportunities for innovation and efficiency. AI and ML are increasingly being leveraged to enhance the functionality of software products, offering smarter solutions for businesses and consumers. From predictive analytics and automation to natural language processing and image recognition, AI and ML are transforming how software applications are developed and used. This not only improves software performance but also enables companies to create more personalized and data-driven user experiences. As these technologies continue to evolve, the demand for AI and ML-driven software solutions is expected to drive growth in the software development market.

Restraint Factor for the Software Development Market

High Development Costs and Budget Constraints, will Limit Market Growth

One of the key restraints in the Software Development Market is the high development costs associated with creating advanced software solutions. The complexity of modern software applications, particularly those incorporating AI, cloud infrastructure, and data security features, requires substantial investment in skilled labor, technology, and infrastructure. Small to medium-sized enterprises (SMEs) often face challenges in allocating sufficient budget for software development, limiting their ability to compete in the market. Additionally, the ongoing maintenance and updates required for software applications add to the financial burden, making it difficult for businesses to maintain a sustainable development cycle.

Impact of Covid-19 on the Software Development Market

Covid-19 pandemic significantly impacted the Software Development Market, accelerating the digital transformat...

This is the supplementary document for the review paper titled “Comprehensive and Data-Driven Literature Review of Supernumerary Robotic Limbs,” which presents a comprehensive and data-driven review that offers a quantitative analysis of Supernumerary Robotic Limbs (SRLs), covering application areas, structural designs, control strategies, embodiments, and their interconnections. All the data analyzed in the review paper can be found in this document, including foundational data extracted from the Web of Science (sheet: All literature on SRLs, and Newly published) and in-depth data (sheet: SRLs design) collected by the authors.

*** DISCLAIMER - This web page is a public resource of general information. The Maryland Mass Transit Administration (MTA) makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the spatial data or database information provided herein. MTA and partner state, local, and other agencies shall assume no liability for errors, omissions, or inaccuracies in the information provided regardless of how caused; or any decision made or action taken or not taken by any person relying on any information or data furnished within. *** This dataset assesses rail station potential for different forms of transit oriented development (TOD). A key driver of increased transit ridership in Maryland, TOD capitalizes on existing rapid transit infrastructure. The online tool focuses on the MTA’s existing MARC Commuter Rail, Metro Subway, and Central Light Rail lines and includes information specific to each station. The goal of this dataset is to give MTA planning staff, developers, local governments, and transit riders a picture of how each MTA rail station could attract TOD investment. In order to make this assessment, MTA staff gathered data on characteristics that are likely to influence TOD potential. The station-specific data is organized into 6 different categories referring to transit activity; station facilities; parking provision and utilization; bicycle and pedestrian access; and local zoning and land availability around each station. As a publicly shared resource, this dataset can be used by local communities to identify and prioritize area improvements in coordination with the MTA that can help attract investment around rail stations. You can view an interactive version of this dataset at geodata.md.gov/tod. ** Ridership is calculated the following ways: Metro Rail ridership is based on Metro gate exit counts. Light Rail ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. MARC ridership is calculated using two (2) independent methods: Monthly Line level ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. This method of ridership calculation is used by the MTA for official reporting purposes to State level and Federal level reporting. Station level ridership is estimated by using person counts completed by the third party vendor. This method of calculation has not been verified by the FTA for statistical reporting and is used for scheduling purposes only. However, because of the granularity of detail, this information is useful for TOD applications. *Please note that the monthly level ridership and the station level ridership are calculated using two (2) independent methods that are not interchangeable and should not be compared for analysis purposes.

The digital marketing consultancy market is experiencing robust growth, projected to reach a market size of $270.6 million in 2025, exhibiting a Compound Annual Growth Rate (CAGR) of 10.8% from 2025 to 2033. This expansion is fueled by several key factors. The increasing reliance of small and medium-sized enterprises (SMEs) and large enterprises on digital channels for customer acquisition and brand building is a significant driver. Businesses are increasingly outsourcing their digital marketing needs to specialized consultancies to leverage expertise in SEO, PPC, web design, and other specialized areas like social media marketing and content strategy. Furthermore, the evolving digital landscape, characterized by advancements in AI-powered marketing tools and the emergence of new marketing channels, necessitates the expertise provided by these consultancies. The market's segmentation reflects this, with notable growth in demand for SEO and PPC services across both SME and large enterprise segments. While competitive pressures and the need for continuous upskilling within the industry present some challenges, the overall market trajectory remains highly positive, driven by the ongoing digital transformation of businesses worldwide. The geographical distribution of this market is diverse, with North America and Europe currently holding significant market shares. However, rapid digital adoption in Asia-Pacific regions like China and India suggests a potential shift in regional dominance in the coming years. Competition is fierce, involving both global giants like WPP Group, Publicis Groupe, and Omnicom Group, as well as specialized boutique consultancies. The success of individual firms hinges on their ability to offer specialized services tailored to specific industry niches, leverage data-driven strategies, and demonstrate measurable ROI for their clients. This market's continued growth is intrinsically linked to the ongoing expansion of digital technologies and the increasing sophistication of digital marketing strategies employed by businesses across various sectors.

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Website Builder Software Market Size 2024-2028

The website builder software market size is forecast to increase by USD 612.2 million at a CAGR of 5.1% between 2023 and 2028.

The market is experiencing significant growth due to the increasing importance of online branding for businesses. Functional websites have become essential for organizations to reach a wider audience and facilitate digital transformation. Cloud-based platforms and web development tools enable the creation of mobile-responsive designs, ensuring accessibility on various devices. AI applications integrated into website builders streamline various processes, such as big data analytics, media and entertainment, retail, and e-commerce. Website templates offer affordable website solutions, making it easier for businesses to establish an online presence. 
Moreover, the advancement of technology, including the AI revolution in website building, enhances the user experience. Open source options provide flexibility and customization opportunities. Website maintenance and security are crucial aspects, with cloud-based platforms offering reliable solutions to mitigate risks. In summary, the market is thriving, driven by the need for functional and secure online branding solutions.

What will be the Size of the Website Builder Software Market During the Forecast Period?

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Website builders have emerged as essential tools In the digital evolution, empowering businesses to create engaging websites and establish a strong online presence. These solutions facilitate digital adoption by individuals and organizations, enabling them to code and develop websites without extensive programming skills. In the context of the current business landscape, the integration of Artificial Intelligence (AI) infrastructure into website builders has become a significant trend. These applications include real-time data processing, NLP, video recognition, and parallel processing. By utilizing AI infrastructure, businesses can enhance their brand identity and optimize their online presence. Versatility and Sustainability: Website builders with AI capabilities offer versatility, allowing businesses to leverage advanced technologies without requiring specialized expertise. Moreover, the integration of AI chips and inference chips In these solutions ensures energy efficiency and reduced energy costs. Deep learning models and matrix multiplications are essential components of AI infrastructure. They enable website builders to provide advanced features such as personalized user experiences, predictive analytics, and automated content generation.
These capabilities can significantly improve user engagement and conversion rates. Cloud computing and parallel processing are essential technologies that support the integration of AI infrastructure into website builders. They facilitate efficient data-intensive computing and real-time processing, ensuring that businesses can quickly respond to market trends and customer demands. The integration of AI infrastructure into website builders has a profound impact on media, entertainment, retail, and e-commerce industries. For instance, media and entertainment companies can use AI to analyze user preferences and provide personalized content recommendations. Retailers can optimize their inventory management and offer personalized product recommendations based on user behavior. E-commerce platforms can leverage AI to enhance their search functionality and provide more accurate and relevant results. Website builders with AI infrastructure represent a significant advancement in digital evolution, enabling businesses to create engaging websites, optimize their online presence, and leverage advanced technologies without requiring specialized expertise. By integrating deep learning models, matrix multiplications, cloud computing, and parallel processing, these solutions offer versatility, sustainability, and significant improvements in user engagement and conversion rates. As businesses continue to adopt digital technologies, the role of AI-enabled website builders will become increasingly essential.

How is this Website Builder Software Industry segmented and which is the largest segment?

The website builder software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Deployment

  Cloud-based
  On-premises


End-user

  Commercial
  Individual


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France
    Italy


  APAC

    China
    India
    Japan


  South America

    Brazil


  Middle East and Africa

By Deployment Insights

The cloud-based segment is estimated to witness significant growth during the forecast period

The authors have developed a Web-based system that provides summary information about clinical trials being conducted throughout the United States. The first version of the system, publicly available in February 2000, contains more than 4,000 records representing primarily trials sponsored by the National Institutes of Health. The impetus for this system has come from the Food and Drug Administration (FDA) Modernization Act of 1997, which mandated a registry of both federally and privately funded clinical trials “of experimental treatments for serious or life-threatening diseases or conditions.” The system design and implementation have been guided by several principles. First, all stages of system development were guided by the needs of the primary intended audience, patients and other members of the public. Second, broad agreement on a common set of data elements was obtained. Third, the system was designed in a modular and extensible way, and search methods that take extensive advantage of the National Library of Medicine's Unified Medical Language System (UMLS) were developed. Finally, since this will be a long-term effort involving many individuals and organizations, the project is being implemented in several phases.

In view of the ubiquitous mobile-app concept that has taken hold over the past decade, whereby distinct, single purpose, modular applications are developed and deployed in a shared user interface (i.e. the phone in your pocket), we have created open source cyberinfrastructure that mimics this paradigm for developing and deploying environmental web applications using open source tools and cloud computing services. This cyberinfrastructure integrates HydroShare for cloud-based data storage and app cataloging, together with Tethys Platform for Python/Django based app development. HydroShare is an open source web-based data management system for climate and water data that is includes a web-services application programmer interface (API) to allow third party programmers to access and use its data resources. We have created a metadata management structure within HydroShare for cataloging, discovering, and sharing web apps. Tethys Platform is an open source software package based on the Django framework, Python programming language, Geoserver, PostgreSQL, OpenLayers and other open source technologies. The Tethys software development kit allows users to create web apps that are presented in a common portal for visualizing, analyzing and modelling environmental data. We will introduce this new cyberinfrastructure through a combination of architecture design and demonstration, and will provide attendees the essential concepts for building their own web apps using these tools.

We present a general data-driven strategy for the search for catalytic materials, focusing particularly on materials useful for the conversion of natural gas (methane) to ethane and ethylene (OCM: oxidative coupling of methane reaction). OCM facilitates the transportation of natural gas and provides a way to synthesize higher-value chemicals. Our strategy is based on consistent experimental measurements and includes ab initio thermodynamics calculations and active screening. Based on our experiments, which showed a volcano-type dependence of the performance on the stability of formed carbonates attributed to the site isolation concept, we developed a method for efficient and inexpensive DFT calculations of the formation energies of carbonates with a prediction accuracy of 0.2 eV based on the Boltzmann distribution of surface terminations. This method was implemented into a high-throughput screening scheme, which includes both general requirements for catalyst candidates and an actively performed artificial intelligence part. Guided by theoretical predictions, we have performed experimental validation of some of the candidates obtained during the screening which showed successful reproduction of the initial volcano dependence. Predicted in this way, materials were found to show in general comparable performance to well-known standard OCM catalysts, or even higher yields specifically at temperatures between 700 and 800 °C.

Market Overview: The global PC website builder market is projected to reach a value of USD XX million by 2033, exhibiting a CAGR of XX% during the forecast period. This growth is primarily driven by the increasing demand for user-friendly and cost-effective website creation solutions for businesses and individuals. The proliferation of e-commerce, digital marketing, and the growing number of online users have further contributed to the market expansion. Market Drivers and Trends: Key drivers of the market include the increasing accessibility of web development tools, advancements in artificial intelligence (AI) and machine learning (ML), and the growing adoption of mobile-responsive website design. Additionally, the shift towards remote work and hybrid work models has further increased the demand for website builders that offer flexibility and ease of use. Notable trends include the integration of AI-powered features, the emergence of cloud-based solutions, and the growing popularity of code-free website development platforms.

B2C Marketing Solutions Market Size And Forecast

B2C Marketing Solutions Market size was valued at USD 50.72 Billion in 2023 and is projected to reach USD 103.92 Billion by 2030, growing at a CAGR of 12.7% during the forecast period 2024-2030.

Global B2C Marketing Solutions Market Drivers

The market drivers for the B2C Marketing Solutions Market can be influenced by various factors. These may include:

Digital change: The adoption of B2C marketing solutions has been fueled by the continuous digital change occurring across many industries. Companies are using social media, internet platforms, and digital channels to connect and communicate with their target audience.
Data-Driven Marketing: Data-driven marketing tactics have been made easier by the growing availability of consumer data and sophisticated analytics technologies. Businesses may design more individualised and targeted campaigns by analysing consumer behaviour, preferences, and interactions with the help of B2C marketing tools.
Personalisation and Customer Experience: Businesses can provide customers with customised and personalised experiences by utilising B2C marketing solutions. Customer happiness and loyalty are increased by personalisation, which includes offers, recommendations, and tailored content.
Multichannel Marketing:Integrated multichannel marketing solutions are now required due to the proliferation of communication channels, such as social media, email, mobile apps, and websites. For a cohesive consumer experience, B2C marketing solutions facilitate coordinated campaigns across several channels.
E-Commerce Growth:The need for B2C marketing solutions has been exacerbated by the rise in online purchasing and e-commerce. Companies are searching for solutions that can maximise their online sales, raise conversion rates, and improve customers’ digital purchasing experiences in general.
Mobile Marketing:As smartphone usage rises, mobile marketing has emerged as a key factor. Businesses may connect with customers on their preferred devices with the support of B2C marketing solutions that emphasise mobile optimisation, SMS marketing, and mobile app engagement.
Social Media Marketing:B2C marketing heavily relies on social media networks. Businesses looking to maximise the power and reach of social networks are in need of solutions that facilitate influencer partnerships, social media marketing, and community involvement.
Automation and AI:Artificial intelligence (AI) and automation are frequently included in B2C marketing solutions. While AI improves personalisation, consumer segmentation, and predictive analytics for more successful campaigns, automation streamlines marketing operations.
Content Marketing:In B2C marketing, content is still a major motivator. Businesses may reach their target audiences with valuable and captivating content by utilising solutions that streamline content development, delivery, and measurement.
CRM (customer relationship management):Businesses can manage customer interactions more successfully by integrating with CRM technologies. CRM-aligned B2C marketing solutions support a comprehensive strategy for comprehending and interacting with clients.
Regulatory Compliance:Adherence to privacy and data protection rules, such as the General Data Protection Regulation (GDPR) and related statutes, has emerged as a critical factor. Businesses and customers are more likely to trust B2C marketing solutions that put data security first and abide by legal requirements.

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.