According to a survey in September 2025, most organizations say AI has broadened the role of privacy, with ** percent reporting that their privacy programs have expanded because of AI. Nearly **** also said privacy spending increased in the past year, and ** percent plan to allocate more resources to privacy and data governance over the next two years.

The Knight Alzheimer Disease Research Center (ADRC) Data Freeze Ending 2026-03-31 is a longitudinal compilation of harmonized, processed research data collected from August 1, 1979 through March 31, 2026. This Data Freeze represents a fixed, versioned snapshot of curated datasets maintained by the ADRC and is intended to support reproducible secondary analyses under approved data use agreements.

The Data Freeze includes data contributed by multiple ADRC Cores, including clinical assessments, cognitive testing, neuropsychological measures, neuroimaging data summaries, fluid biomarker data, neuropathology variables, and related research measures. Modules are compiled, quality controlled, and integrated according to ADRC Data Management and Sharing procedures prior to freeze finalization.

This dataset reflects the full longitudinal structure of ADRC participant data available as of the official cutoff date (March 31, 2026). No data collected after this date are included in this release. Each subsequent Data Freeze constitutes a new versioned dataset with its own DOI.

The purpose of this Data Freeze is to: 1. Provide a stable, citable dataset snapshot for approved secondary analyses 2. Support NIH Data Management and Sharing (DMS) policy compliance 3. Enable transparency, reproducibility, and longitudinal tracking of dataset versions

This repository record provides metadata describing the Data Freeze and assigns a persistent DOI to this version. The underlying human subject data are stored in a secure Research Infrastructure Services (RIS) environment and are not publicly downloadable.

Access to this dataset is controlled and requires submission of a formal data request through the Knight ADRC Request Center. Approved investigators must complete the appropriate Data Use Agreement prior to receiving access. Upon approval, access to the static dataset corresponding to this DOI will be granted through ADRC-managed secure infrastructure.

Investigators using this Data Freeze must cite this dataset DOI in all resulting publications and acknowledge Knight ADRC funding as specified in the Data Use Agreement.

This dataset was generated and curated by the Knight ADRC Data Management and Statistics Core in collaboration with contributing ADRC Cores.

For information about submitting a data request, please visit: https://knightadrc.wustl.edu/professionals-clinicians/request-center-resources/submit-a-request/

According to a survey of young healthcare professionals worldwide carried out in 2020, ** percent of respondents reported that training on how to use new technologies would enable them to use digital patient data effectively. Furthermore, over half of the healthcare workers surveyed reported that support staff for either data management or data entry would allow them to use patient digital data efficiently.

The Knight Alzheimer Disease Research Center (ADRC) Data Freeze Ending 2025-09-30 is a longitudinal compilation of harmonized, processed research data collected from August 1, 1979 through September 30, 2025. This Data Freeze represents a fixed, versioned snapshot of curated datasets maintained by the ADRC and is intended to support reproducible secondary analyses under approved data use agreements.

The Data Freeze includes data contributed by multiple ADRC Cores, including clinical assessments, cognitive testing, neuropsychological measures, neuroimaging data summaries, fluid biomarker data, neuropathology variables, and related research measures. Modules are compiled, quality controlled, and integrated according to ADRC Data Management and Sharing procedures prior to freeze finalization.

This dataset reflects the full longitudinal structure of ADRC participant data available as of the official cutoff date (September 30, 2025). No data collected after this date are included in this release. Each subsequent Data Freeze constitutes a new versioned dataset with its own DOI.

The purpose of this Data Freeze is to: 1. Provide a stable, citable dataset snapshot for approved secondary analyses 2. Support NIH Data Management and Sharing (DMS) policy compliance 3. Enable transparency, reproducibility, and longitudinal tracking of dataset versions

This repository record provides metadata describing the Data Freeze and assigns a persistent DOI to this version. The underlying human subject data are stored in a secure Research Infrastructure Services (RIS) environment and are not publicly downloadable.

Access to this dataset is controlled and requires submission of a formal data request through the Knight ADRC Request Center. Approved investigators must complete the appropriate Data Use Agreement prior to receiving access. Upon approval, access to the static dataset corresponding to this DOI will be granted through ADRC-managed secure infrastructure.

Investigators using this Data Freeze must cite this dataset DOI in all resulting publications and acknowledge Knight ADRC funding as specified in the Data Use Agreement.

This dataset was generated and curated by the Knight ADRC Data Management and Statistics Core in collaboration with contributing ADRC Cores.

For information about submitting a data request, please visit: https://knightadrc.wustl.edu/professionals-clinicians/request-center-resources/submit-a-request/

The Knight Alzheimer Disease Research Center (ADRC) Data Freeze Ending 2025-03-31 is a longitudinal compilation of harmonized, processed research data collected from August 1, 1979 through March 31, 2025. This Data Freeze represents a fixed, versioned snapshot of curated datasets maintained by the ADRC and is intended to support reproducible secondary analyses under approved data use agreements.

The Data Freeze includes data contributed by multiple ADRC Cores, including clinical assessments, cognitive testing, neuropsychological measures, neuroimaging data summaries, fluid biomarker data, neuropathology variables, and related research measures. Modules are compiled, quality controlled, and integrated according to ADRC Data Management and Sharing procedures prior to freeze finalization.

This dataset reflects the full longitudinal structure of ADRC participant data available as of the official cutoff date (March 31, 2025). No data collected after this date are included in this release. Each subsequent Data Freeze constitutes a new versioned dataset with its own DOI.

The purpose of this Data Freeze is to: 1. Provide a stable, citable dataset snapshot for approved secondary analyses 2. Support NIH Data Management and Sharing (DMS) policy compliance 3. Enable transparency, reproducibility, and longitudinal tracking of dataset versions

This repository record provides metadata describing the Data Freeze and assigns a persistent DOI to this version. The underlying human subject data are stored in a secure Research Infrastructure Services (RIS) environment and are not publicly downloadable.

Access to this dataset is controlled and requires submission of a formal data request through the Knight ADRC Request Center. Approved investigators must complete the appropriate Data Use Agreement prior to receiving access. Upon approval, access to the static dataset corresponding to this DOI will be granted through ADRC-managed secure infrastructure.

Investigators using this Data Freeze must cite this dataset DOI in all resulting publications and acknowledge Knight ADRC funding as specified in the Data Use Agreement.

This dataset was generated and curated by the Knight ADRC Data Management and Statistics Core in collaboration with contributing ADRC Cores.

For information about submitting a data request, please visit: https://knightadrc.wustl.edu/professionals-clinicians/request-center-resources/submit-a-request/

Global Professional Services Automation Software market size was $13625.49 million in 2025 and is reach $42590.71 million by 2034, a CAGR of 13.5%.

This dataset contains survey materials and responses collected to assess institutional stakeholder perceptions of water governance in the Santa Ana River Watershed (SARW), southern California, USA. The assessment was conducted using the Governance and Stakeholders component of the Freshwater Health Index (FHI). The survey was administered between February 2024 and January 2025 to 35 professionals involved in water resources management, environmental regulation, planning, research, consulting, and ecological conservation. The questionnaire consists of 51 perception-based questions organized into 12 governance sub-indicators and four major indicators: Enabling Environment, Stakeholder Engagement, Effectiveness, and Vision and Adaptive Governance. The supporting Excel workbook contains question-level survey responses, skipped responses, question-level descriptive statistics, and calculated respondent-level governance scores. The accompanying PDF includes the informed consent statement and complete survey questionnaire. These materials support research examining variation in governance perceptions across management dimensions and geographic areas of the SARW. The data were previously included in the supplementary materials accompanying the doctoral dissertation of Qin (2026), University of California, Riverside.

IntroductionTeaching climate change requires teachers to have the educational resources that will facilitate teaching this content and visualize how a global problem has various local implications. In Chile, the capacity for environmental data collection and use at the school level remains limited, hindering evidence-based and context-aware climate education.MethodsThis study follows a Design-Based Research (DBR) approach and comprises three main phases: (1) the participatory design of an environmental monitoring station based on the needs identified by in-service teachers for teaching climate change; (2) the development and implementation of a professional development course to support teachers in the appropriation of the technological resource; and (3) the analysis of learning experiences designed by teachers who integrated the technology into their pedagogical practices.ResultsTeachers successfully designed active learning experiences that incorporated local environmental data. These experiences promoted the development of scientific skills and 21st-century competencies, contextualized within local territories and cultures, with the potential of opening new spaces for learning beyond the classroom.DiscussionThe integration of the monitoring station transformed teachers’ views of technology, shifting from an instrumental perspective to one linked to key scientific inquiry processes. It also supported the design of active and contextualized learning experiences that promote scientific and 21st-century skills. The relevance and low cost of the resource make it a viable option for scaling, although challenges remain in teacher training related to basic statistics and environmental data management.

In 2024, the top way in which HR departments used artificial intelligence (AI) in supporting performance management was to assist managers in providing more comprehensive or actionable feedback to their employees. Almost ** percent of HR professionals said this was the case within their department. Bottom of the list was to identify potential areas of bias within performance evaluations, where only **** percent of respondents gave this as their answer.

IntroductionTeaching climate change requires teachers to have the educational resources that will facilitate teaching this content and visualize how a global problem has various local implications. In Chile, the capacity for environmental data collection and use at the school level remains limited, hindering evidence-based and context-aware climate education.MethodsThis study follows a Design-Based Research (DBR) approach and comprises three main phases: (1) the participatory design of an environmental monitoring station based on the needs identified by in-service teachers for teaching climate change; (2) the development and implementation of a professional development course to support teachers in the appropriation of the technological resource; and (3) the analysis of learning experiences designed by teachers who integrated the technology into their pedagogical practices.ResultsTeachers successfully designed active learning experiences that incorporated local environmental data. These experiences promoted the development of scientific skills and 21st-century competencies, contextualized within local territories and cultures, with the potential of opening new spaces for learning beyond the classroom.DiscussionThe integration of the monitoring station transformed teachers’ views of technology, shifting from an instrumental perspective to one linked to key scientific inquiry processes. It also supported the design of active and contextualized learning experiences that promote scientific and 21st-century skills. The relevance and low cost of the resource make it a viable option for scaling, although challenges remain in teacher training related to basic statistics and environmental data management.

The Indian Institute of Management (IIMA) in Ahmedabad ranked first with a score of 83.32, followed by IIM in Bangalore, in 2024 among management institutes. IIMA, a public business school, offers postgraduate, doctoral, and executive education programs. The scoring for the institute ranking is based on parameters such as teaching, learning, resources, research and professional practice, graduation outcomes, outreach, inclusivity, and perception.

In 2024, the top way in which HR departments used artificial intelligence (AI) in learning and development (L&D) was to *************************************************************************************. *********** of HR professionals said this was the case within their department. Bottom of the list was to provide immersive learning experiences (e.g. virtual reality or augmented reality), where only ** percent of respondents gave this as their answer.