This dataset contains the “GapMap Frontal I” in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. In order to provide whole-brain coverage for the cortex within the Julich-Brain Atlas, yet uncharted parts of the frontal cortex have been combined to the brain region “GapMap Frontal I”. The distributions were modeled so that probabilistic gap maps were computed in analogy to other maps of the Julich-Brain Atlas. The probabilistic map of “GapMap Frontal I” is provided in NifTi format for each hemisphere in the reference space. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. New maps are continuously replacing parts of “GapMap Frontal I” with progress in mapping.

GapMaps Live is a simple to use location intelligence platform available in over 25 countries globally which allows you to visualise your own data integrated with the best Map Data available so your team can make faster, smarter and more confident retail location decisions.

GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate demographic datasets at 150m grid levels across Asia and MENA. Understand who lives in a catchment, where they work and their spending potential to make informed business decisions.

No description was included in this Dataset collected from the OSF

Sourcing accurate and up-to-date map data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly.

GapMaps Map Data uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent demographics data across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities.

GapMaps Map Data also includes the latest Point-of-Interest (POI) Data for leading retail brands across a range of categories including Fast Food/ QSR, Health & Fitness, Supermarket/Grocery and Cafe sectors which is updated monthly.

With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to:

• Better understand your customers
• Identify optimal locations to expand your retail footprint
• Define sales territories for franchisees
• Run targeted marketing campaigns.

GapMaps Map Data for Asia and MENA can be utilized in any GIS platform and includes the latest estimates (updated annually) on:

1. Population (how many people live in your local catchment)
2. Demographics (who lives within your local catchment)
3. Worker population (how many people work within your local catchment)
4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers)
5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category.

Primary Use Cases for GapMaps Map Data:

1. Retail Site Selection - identify optimal locations for future expansion and benchmark performance across existing locations.
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential
3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics
4. Target Marketing: Develop effective marketing strategies to acquire more customers.
5. Integrate GapMaps demographic data with your existing GIS or BI platform to generate powerful visualizations.
6. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)
7. Customer Profiling
8. Target Marketing
9. Market Share Analysis

This protocol outlines methods for creating India’s first Evidence Gap Map (EGM) on postpartum depression (PPD), following PRISMA-EGM standards. It details search strategies, inclusion criteria, and plans to visualize research gaps for policymakers and researchers working on maternal mental health in India.

GapMaps Mobile Location Data by Azira provides actionable insights on consumer travel patterns at a global scale empowering Marketing and Operational Leaders to confidently reach, understand, and market to highly targeted audiences and optimize their business results.

This Evidence Gap Map (EGM) aims to identify and visualize the existing academic research on the intersection of sustainable and regenerative agriculture with the sexual identity of practitioners. The study focuses on marginalized communities, aiming to make the research socially relevant. The EGM seeks to guide future research, inform more inclusive policies, and help agricultural organizations understand the importance of inclusivity and a sense of belonging by mapping out thematic and geographical gaps.

Evidence and Gap Map 3.Publication: Theroux et al., 2025. A systematic review and evidence gap map evaluation of rhythmic and/or complex movement interventions and child cognitive outcomes. Clinical Child and Family Psychology Review.

Objective: To support evidence-informed decision-making, we created an evidence gap map (EGM) to characterise the evidence base on the effectiveness of interventions in improving routine childhood immunisation outcomes in low- and middle-income countries (LMICs). Methods: We developed an intervention-outcome matrix with 38 interventions and 43 outcomes. We searched academic databases and grey literature sources for relevant impact evaluations (IEs) and systematic reviews (SRs). Search results were screened on title/abstract. Those included in the title/abstract were retrieved for a full review. Studies meeting the eligibility criteria were included and data were extracted for each included study. All screening and data extraction was done by two independent reviewers. We analysed these data to identify trends in the geographic distribution of evidence, the concentration of evidence across intervention and outcome categories, and attention to vulnerable populations in the literature. Results: We identified 309 studies, comprising 226 completed IEs, 58 completed SRs, 24 ongoing IEs, and 1 ongoing SR. Evidence from IEs is heavily concentrated in a handful of countries in Sub- Saharan Africa and South Asia. Among interventions, the most frequently evaluated are those related to education and material incentives for caregivers or health workers. There are gaps in the study of non-material incentives and outreach to vulnerable populations. Among outcomes, those related to vaccine coverage and health are well covered. However, evidence on intermediate outcomes related to health system capacity or barriers faced by caregivers is much more limited. Conclusions: There is valuable evidence available to decision-makers for use in identifying and deploying effective strategies to increase routine immunisation in LMICs. However, additional research is needed to address gaps in the evidence base. Methods These data were manually extracted by trained reviewers from published research reports.

Additional file 5: STEP 2 - Study characteristics of implementation intervention studies that performed contextual analyses.

This database contains data from 406 papers included in the systematic review A Systematic Review of Research Gaps in the Built Environment of Inpatient Healthcare Settings. The study that led to this database employed the evidence-gap map method to critically examine the scope, methodologies, and focus of research investigating the influence of the built environment on inpatient healthcare settings over a decade (2010–2021). It followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and analyzed 406 articles, primarily from North America and Europe.

The dataset includes details on the author(s), year, journal, title, DOI/URL, type of inpatient healthcare setting, research design, methods used, data collection instruments, and study aim. It also specifies per the study which health-related outcomes are adressed including person-centered care, shared decision-making, self-care support, patient participation, safety, timeliness, equity, efficiency, or effectiveness. Additionally, it records the main findings, study summary, country, region, study quality, addressed built environment features (ambient, architectural, interior, social-spatial, nature), and the populations involved (patients, visitors, staff).

The dataset has been used to identify research gaps. It also allows for further analysis of the entire set or specific subsections. Filters can be applied to focus on particular subsets based on inpatient settings, regions/countries, health-related outcomes, populations, or design features. For example, it allows filtering for studies on ICU departments, studies examining visitors' interaction with nature, or both. Additionally, the database can support ongoing analysis using the same search strings to track developments in this research domain.

We only ask that you acknowledge the use of this dataset (possibly alongside the accompanying paper) as a foundation for further research.

Sourcing accurate and up-to-date geodemographic data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly.

GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent geodemographic datasets across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities.

With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to:

• Better understand your customers
• Identify optimal locations to expand your retail footprint
• Define sales territories for franchisees
• Run targeted marketing campaigns.

Premium geodemographics data for Asia and MENA includes the latest estimates (updated annually) on:

1. Population (how many people live in your local catchment)
2. Demographics (who lives within your local catchment)
3. Worker population (how many people work within your local catchment)
4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers)
5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category.

Primary Use Cases for GapMaps Geodemographic Data:

1. Retail (eg. Fast Food/ QSR, Cafe, Fitness, Supermarket/Grocery)
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential
3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics
4. Site Selection: Identify optimal locations for future expansion and benchmark performance across existing locations.
5. Target Marketing: Develop effective marketing strategies to acquire more customers.

6. Integrate GapMaps demographic data with your existing GIS or BI platform to generate powerful visualizations.

7. Commercial Real-Estate (Brokers, Developers, Investors, Single & Multi-tenant O/O)

8. Tenant Recruitment

9. Target Marketing

10. Market Potential / Gap Analysis

11. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)

12. Customer Profiling

13. Target Marketing

14. Market Share Analysis

No description was included in this Dataset collected from the OSF

GapMaps Foot Traffic Data uses location data on mobile phones sourced by Azira which is collected from smartphone apps when the users have given their permission to track their location. It can shed light on consumer visitation patterns (“where from” and “where to”), frequency of visits, profiles of consumers and much more.

Businesses can utilise foot traffic data to answer key questions including: - What is the demographic profile of customers visiting my locations? - What is my primary catchment? And where within that catchment do most of my customers travel from to reach my locations? - What points of interest drive customers to my locations (ie. work, shopping, recreation, hotel or education facilities that are in the area) ? - How far do customers travel to visit my locations? - Where are the potential gaps in my store network for new developments?
- What is the sales impact on an existing store if a new store is opened nearby? - Is my marketing strategy targeted to the right audience? - Where are my competitor's customers coming from?

Foot Traffic data provides a range of benefits that make it a valuable addition to location intelligence services including: - Real-time - Low-cost at high scale - Accurate - Flexible - Non-proprietary - Empirical

Azira have created robust screening methods to evaluate the quality of Foot Traffic data collected from multiple sources to ensure that their data lake contains only the highest-quality mobile location data.

This includes partnering with trusted location SDK providers that get proper end user consent to track their location when they download an application, can detect device movement/visits and use GPS to determine location co-ordinates.

Data received from partners is put through Azira's data quality algorithm discarding data points that receive a low quality score.

Use cases in Europe will be considered on a case to case basis.

The GapMaps Consumer Behavior database sourced from Applied Geographic Solutions (AGS) is derived from an analysis of the MRI surveys using Panorama. Each of the approximately 40,000 records in the MRI survey is geocoded then assigned the Panorama code of the block group. The results are then summarized for each variable over the sixty-eight segments, in effect providing the average value for each Panorama segment. For example, a variable such as “Shopped at Macy’s” is computed by summarizing the records for each segment as a yes/no response, then finding the average percentage of households in each segment who shopped at Macy’s. This is often referred to as a profile.

The profile is then applied to geographic areas by making the assumption that households in demographically similar neighborhoods will tend to have similar consumption patterns as a result of their similar economic means, life stage, and other characteristics. The result is a series of estimates for geographic areas which measure the relative propensity of consumers in each geographic area to shop at particular stores, own various household items, and engage in activities.

In most cases, these should be considered as relative indicators, since local differences may result in different behavior. In addition, in some cases, variables must be considered as potential only, since the activity or store may not be locally available.

GapMaps GIS Data by Azira provides actionable insights on consumer travel patterns at a global scale empowering Marketing and Operational Leaders to confidently reach, understand, and market to highly targeted audiences and optimize their business results.

Sourcing accurate and up-to-date demographic data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly.

GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent demographic datasets across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities.

With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to:

• Better understand your customers
• Identify optimal locations to expand your retail footprint
• Define sales territories for franchisees
• Run targeted marketing campaigns.

Premium demographics data for Asia and MENA includes the latest estimates (updated annually) on:

1. Population (how many people live in your local catchment)
2. Demographics (who lives within your local catchment)
3. Worker population (how many people work within your local catchment)
4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers)
5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category.

Primary Use Cases for GapMaps Demographic Data:

1. Retail (eg. Fast Food/ QSR, Cafe, Fitness, Supermarket/Grocery)
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential
3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics
4. Site Selection: Identify optimal locations for future expansion and benchmark performance across existing locations.
5. Target Marketing: Develop effective marketing strategies to acquire more customers.

6. Integrate GapMaps demographic data with your existing GIS or BI platform to generate powerful visualizations.

7. Commercial Real-Estate (Brokers, Developers, Investors, Single & Multi-tenant O/O)

8. Tenant Recruitment

9. Target Marketing

10. Market Potential / Gap Analysis

11. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)

12. Customer Profiling

13. Target Marketing

14. Market Share Analysis

No description was included in this Dataset collected from the OSF

GapMaps curates up-to-date and high-quality Business Location Data tracking store openings and closures for leading retail brands across Asia and MENA. Get the insights you need to make more accurate and informed business decisions.