The dataset comprises diverse sources collected across four research papers within a PhD thesis dissertation context. It includes:

Transcripts of Interviews: These transcripts capture conversations with various stakeholders, such as academics, government practitioners, NGOs, private companies and local residents. They provide insights into social dynamics, preferences, and challenges related to the management of public spaces, participatory practices and the use of ICTs for the planning, design and maintenance of public spaces.

Field Notes Observations: Researchers recorded detailed observations during fieldwork. These notes document physical aspects of the conducted interviews, human behavior, and interactions. They serve as valuable qualitative data for this research.

Geospatial Information: Geospatial data includes coordinates, boundaries, and spatial relationships. It enables spatial analysis, mapping, and visualization of public spaces. This information was created to develop thematic maps and to collect how residents perceive the needs and aspirations of their public spaces.

Purpose of the Dataset: The dataset aims to investigate the role of Information and Communication Technology (ICT) in enhancing social participation within public spaces. Researchers can analyze these diverse data sources to explore patterns, identify challenges, and propose ICT-based interventions for inclusive and vibrant public spaces.

The dataset includes information divided into 4 papers within the research project. Identifying each dataset is mentioned in the title of the paper. Paper 1, Paper 2, Paper 3 and Paper 4.

Please note that the dataset is anonymized to protect privacy and confidentiality. Nevertheless, the information can lead to identifying actors that participated in this research, for which access to the datasets required a request, such as photographs. Researchers interested in urban planning, social dynamics, and ICT applications can leverage this dataset for further studies.

Geographical data provides relevant insight for a wide scope of applications, providing a robust picture of multiple geographical layers to enhance geospatial analysis, segmentation, personalization and audience engagement.

Acxiom combines data from multiple reliable private and public sources, summarizing individual and household data attributes for a given geographic level to create robust unique estimates for each area. The use of proven granular data and multivariate procedures ensure the projections accurately reflect the area. Once aggregated, it is no longer possible to identify individuals and the data can be considered anonymous, protecting consumers’ privacy in accordance with local and EU privacy laws.
An extensive range of demographic and lifestyle attributes are available, including:  Lifestage Demographics  Household Composition  Daytime Population  Home and Property  Income and Employment  Affordability and expenditure  Lifestyles, Interest and Charity  Automotive  Finance and Credit  Media, Channel and Technology  Personicx Segmentation Attributes are a combination of proportions, mean values and scores for a range of demographic, income and lifestyle data at a postcode level.

Use cases & Benefits: Elevate your analysis and marketing with an improved understanding of local areas and market potential to:  Optimize strategic planning for site location and sales territories  Define the right mix of products and services to offer based on market characteristics.  Target individuals geographically with online and offline communications

Unlock the power of 43M+ verified locations across the USA with high-precision geospatial data. Featuring 50+ enriched attributes including coordinates, building type, and geometry. Our AI-powered dataset ensures unmatched accuracy through advanced deduplication and enrichment. With 30+ years of industry expertise, we deliver trusted, customizable data solutions for mapping, navigation, urban planning, and marketing, empowering smarter decision-making and strategic growth.

Key use cases of Geospatial data have helped our customers in several areas:

1. Gain a Competitive Edge with Smarter Mapping : Use geospatial data to analyse competitors, identify high-traffic zones, and optimize locations for maximum impact.
2. Enhance Navigation & Location-Based Engagement : Improve turn-by-turn navigation, EV charging station discovery, and real-time travel insights for seamless customer experiences.
3. Find High-Value Locations for Business Growth : Leverage geospatial intelligence to select profitable retail sites, franchise locations, and warehouses with precision.
4. Streamline Deliveries & Address Validation : Improve shipping accuracy, reduce failed deliveries, and optimize courier routes for better customer satisfaction.
5. Drive Smarter Decisions with Spatial Analysis : Utilize location intelligence for disaster risk assessment, public health campaigns, and agricultural planning.

Large linear transport infrastructure projects, such as highways connecting large metropolitan areas, are continuously under development in France. Although the economic and social benefits of such projects are often disputed, their impacts on the environment and local populations are multiple. These potential impacts almost systematically result in conflicts between decision-makers and planners on one side, and local actors with various profiles (e.g. farmers, residents, environmental associations) mobilised against the projects on the other. In the context of a citizen mobilisation against the A45 highway project in eastern France, this study aimed to analyse the social contributions of maps in terms of information reception. The study is based on the creation of maps representing combined spatial impacts (on mobility, housing, land, landscapes, agriculture, and ecosystems). These maps, created by researchers, were presented in the form of posters aimed at opening discussions with non-experts. The maps created an original medium for discussing and debating the impacts of a highway project through the participatory encounter. Under the lens of spatial and environmental justice, this study questions the discrepancies between who makes decisions on a project and who suffers its impacts, and also raises questions about the position of scientific research in citizen mobilisation.

Dataset description: This dataset contains the information needed to replicate the results presented in the article “Optimizing recruitment in an online environmental PPGIS—is it worth the time and costs?”. The data were collected as part of a study investigating recruitment strategies for a large-scale online public participation GIS (PPGIS) platform in coastal areas of northern Norway. To investigate different recruitment strategies, we reviewed previous environmental PPGIS studies using random sampling and methods to increase response rates. We compared the attained results with our large-scale PPGIS in northern Norway, where we used both random and volunteer (traditional and social media) sampling. The dataset includes response rates for the 5% of the population (13 regions in northern Norway) recruited by mail to participate in an online PPGIS survey, response rates from volunteers recruited through traditional and social media, synthetic demographic data, and the code necessary for processing demographic data to obtain the results presented in the article. Original demographic data is not shared due to privacy legislation. We furthermore calculated time spent and costs used for recruiting both randomly sampled persons and volunteers. Article abstract: Public participation GIS surveys use both random and volunteer sampling to recruit people to participate in a self-administered mapping exercise online. In random sampling designs, the participation rate is known to be relatively low and biased to specific segments (e.g., middle-aged, educated men). Volunteer sampling provides the opportunity to reach a large crowd at reasonable costs but generally suffers from unknown sampling biases and lower data quality. The low participation rates and the quality of mapping question the validity and generalizability of the results, limiting their use as a democratic tool for enhancing participation in spatial planning. We therefore asked: How can we increase participation in online environmental PPGIS surveys? Is it worth the time and costs? We reviewed environmentally related online PPGIS surveys (n=26) and analyzed the sampling biases and recruitment strategies utilized in a large-scale online PPGIS platform in coastal areas of northern Norway via both random (16978 invited participants) and volunteer sampling. We found that the time, effort, and costs required to increase participation rates yielded meager results. We discuss the time and cost efficiency of different recruitment methods and the implications of participation levels despite the recruitment methods used.

This is a complete dataset of all outputs produced from a survey assessing environmental knowledge (and knowledge gas) across local communities in the Iveragh peninsula, Co. Kerry, Ireland, during the first months of 2021. The dataset includes chart and figures, maps produced using GIS, mind maps, spreadsheets, and a supporting document containing all relevant metadata.

Public participation as a tool for integrating local knowledge into spatial planning : planning, participation, and knowledge is a book. It was written by Tal Berman and published by : Springer in 2016.

Unlock the power of 164M+ verified locations across 220+ countries with high-precision geospatial data. Featuring 50+ enriched attributes including coordinates, building type, and geometry. Our AI-powered dataset ensures unmatched accuracy through advanced deduplication and enrichment. With 30+ years of industry expertise, we deliver trusted, customizable data solutions for mapping, navigation, urban planning, and marketing, empowering smarter decision-making and strategic growth.

Key use cases of Geospatial data have helped our customers in several areas:

1. Gain a Competitive Edge with Smarter Mapping : Use geospatial data to analyse competitors, identify high-traffic zones, and optimize locations for maximum impact.
2. Enhance Navigation & Location-Based Engagement : Improve turn-by-turn navigation, EV charging station discovery, and real-time travel insights for seamless customer experiences.
3. Find High-Value Locations for Business Growth : Leverage geospatial intelligence to select profitable retail sites, franchise locations, and warehouses with precision.
4. Streamline Deliveries & Address Validation : Improve shipping accuracy, reduce failed deliveries, and optimize courier routes for better customer satisfaction.
5. Drive Smarter Decisions with Spatial Analysis : Utilize location intelligence for disaster risk assessment, public health campaigns, and agricultural planning.

Delaware County Office of Data and Mapping Innovation (ODMI), using a Geographic Information System, supports departments within the County with custom mapping, interactive applications, and authoritative data to be used in their workflows and engagement with the public. The office always supports and works with local governments, private companies, and the public. The open data site provides information in the form of interactive applications as well as a data inventory to download specific datasets for mapping purposes.

For more information or questions contact - Email: data_mapping@co.delaware.pa.us

This dataset was developed for the River Basin Management Plan for Ireland 2018 – 2021 (second cycle River Basin Management Plan). The Areas for Action are areas where action will be carried out in the second cycle. The data consists of polygon geometry representing the location and extent of the Areas for Action (waterbodies) and tabular attribute data describing the waterbody.

The Areas for Action were selected based on the priorities in the draft river basin management plan, the evidence from the Water Framework Directive characterisation process, and the expertise, data and knowledge of public body staff with responsibilities for water and the different pressure types.

Following the selection process, the Local Authorities Water and Communities Office (LAWCO) undertook public engagement and feedback sessions on the Areas for Action. These were considered in the drafting of the final River Basin Management Plan, which was published on April 17th 2018.

The Action Plan Start Year is the year the Local Authority Waters Programme (LAWPRO) plan to begin assessment work within the Area for Action.

This is not a final dataset and will likely change over the lifecycle of the River Basin Management Plan.

'Building Scholarly Resources for Wider Public Engagement' was a full day workshop that took place at the Radcliffe Observatory Quarter, Oxford University, Oxford, on Friday 13 June 2014. The hashtag for the event was #DHCOxf. It was organised by DHCrowdscribe, the online hub for the output of the AHRC-funded Collaborative Skills Project ‘Promoting Interdisciplinary Engagement in the Digital Humanities’. Speakers were: Matt Vitins and Anna Crowe ( Legal and Ethical Issues in the Digital Humanities), Dr Stuart Dunn (Crowdsourcing), Dr Robert Simpson (Zooniverse), Dr Ernesto Priego and Dr James Baker (Sharing Data from a Researcher’s Perspective), Michael Popham, Dr Ylva Berglund Prytz (Digitising the Humanities and Engaging with the Public), Judith Siefring (Early English Books Online Text Creation Partnership), David Tomkins (Bodleian Digital Library), Dr Robert Mcnamee (Electronic Enlightenment Project), Dr Stewart Brookes (‘GettingMedieval, Getting Palaeography: The DigiPal Database of Anglo-Saxon Manuscripts), Dr Michael Athanson (ArcGIS and Mapping the Humanities) Professor David de Roure (Scholarly Social Machines), and Professor Howard Hotson. This .XLS file contains Tweets tagged with #DHCOxf (case not sensitive). The archive shared here contains 692 Tweets dated 13 June 2014 (the day the event took place). There were definitely more Tweets tagged #DHCOxf, but this was the closest I got to compiling a more or less complete set dated 13 June 2014. The Tweets contained in this file were collected using Martin Hawksey’s TAGS 5.1. The file contains two sheets: Sheet 0. The 'Cite Me' sheet, including procedence of the file, citation information, information about its contents, the methods employed and some context. Sheet 1. The Archive containing 692 Tweets dated 13 June 2014. To avoid spam only users with at least 2 followers were included in the archive. Retweets have been included. Please note that both research and experience show that the Twitter search API isn't 100% reliable. Large tweet volumes affect the search collection process. The API might "over-represent the more central users", not offering "an accurate picture of peripheral activity" (González-Bailón, Sandra, et al. 2012). Therefore, it cannot be guaranteed this file contains each and every tweet tagged with #DHCOxf during the indicated period. Some deduplication and refining has been performed to avoid spam tweets and duplication. Some characters in some Tweets' text might not have been decoded correctly. Please note the data in this file is likely to require further refining and even deduplication. The data is shared as is. If you use or refer to this data in any way please cite and link back using the citation information above. All the data collected in this small dataset was willingly made freely, openly and publicly available online by users via Twitter and therefore was and still is openly and freely available through several other methods and services. It has been shared here in a curated form for educational and research use and no copyright or privacy infringement is intended or should be inferred. This file was created and shared by Ernesto Priego (Centre for Information Science, City University London) with a Creative Commons- Attribution license (CC-BY).

If you use or refer to this data in any way please cite and link back using the citation information above.

[Please make sure you are looking at the latest version of the file as earlier versions contained unfortunate typos].

Cities and urban green areas therein can be considered as complex social-ecological systems that provide various ecosystem services with different synergies and trade-offs among them. In this article, we show that multiple stakeholder perspectives and data sources should be used to capture key values for sustainable planning and management of urban green spaces. Using an urban forest in Helsinki, Finland as a case study, we incorporated data collected using public participation GIS, expert elicitation and forest inventories in order to investigate the guidance that the different types of data, and their integration, can provide for landscape planning. We examined the relationship and spatial concurrence between two social variables i.e. visitors’ perceived landscape values and green space use, and two ecological variables i.e. forest habitat quality and urban biodiversity, using hot/coldspot analysis. We found weak correlations and low mean spatial coincidence between the social and ecological data, indicating great complementary importance to multi-criteria decision-making. In addition, there was a higher level of spatial agreement between the ecological datasets than between the social datasets. Forest habitat quality and urban biodiversity were positively correlated and spatially coincided moderately, while we found a negative correlation and very low overlap between visitor use and landscape values. This highlights the conceptual and spatial distinction between the general preferences and values citizens assign to public green spaces and the realized everyday use of these areas and their services. The resulting maps can inform planners on overall social and environmental quality of the landscape, and point out potential threats to areas of high ecological value due to intensive recreational use, which is crucial information for natural resource management. In the end, we discuss different strategies for managing overlaps and discrepancies between the social and ecological values.

Abstract copyright UK Data Service and data collection copyright owner.

This research project analysed how public attitudes and community responses to shale gas unfold in space and time. Given that public protests about hydraulic fracturing ('fracking') have taken place in several countries including the UK, understanding public attitudes and community responses to shale gas development is a key social science research area, with relevance for UK policy and for developers' 'social license to operate'.

To date, cross-sectional research on public attitudes to shale gas has predominated, with little detail on how attitudes might vary across geographical areas or evolve over time. Moreover, little in-depth research has charted the lived experience of UK communities in places of shale gas development or the operator engagement that has taken place there.

To address these gaps, this project implemented a mixed-method approach combining spatial, qualitative and quantitative tools. A multi-scalar approach was undertaken with a particular interest in the evolution of public attitudes at the societal level, and the relations between stakeholder and community engagement around particular shale gas development projects at the local level. Informed by frameworks derived from research on other controversial energy technologies, the aims were to address the following questions:

• how do public attitudes to shale gas evolve over space and time in response to unfolding events and changing discourse?
• what is the lived experience of communities affected by shale gas site preparation, exploration and extraction?
• what rationales and practices are employed by shale gas stakeholders, including operators, to engage with communities and how is this engagement perceived and responded to?
  

The research project included three types of survey:

• four national longitudinal surveys were conducted over the course of the project in 2019, 2020, 2021 and 2022, respectively
• two surveys were conducted with samples on individuals living in very close proximity to prospective shale gas development sites – in Great Altcar (July/August 2020) and Woodsetts (June 2021)
• one additional national Omnibus survey data set, which included a small number of questions, was run a few days prior to the UK general election in December 2019

Overview: The Lower Nooksack Water Budget Project involved assembling a wide range of existing data related to WRIA 1 and specifically the Lower Nooksack Subbasin, updating existing data sets and generating new data sets. This Data Management Plan provides an overview of the data sets, formats and collaboration environment that was used to develop the project. Use of a plan during development of the technical work products provided a forum for the data development and management to be conducted with transparent methods and processes. At project completion, the Data Management Plan provides an accessible archive of the data resources used and supporting information on the data storage, intended access, sharing and re-use guidelines.

One goal of the Lower Nooksack Water Budget project is to make this “usable technical information” as accessible as possible across technical, policy and general public users. The project data, analyses and documents will be made available through the WRIA 1 Watershed Management Project website http://wria1project.org. This information is intended for use by the WRIA 1 Joint Board and partners working to achieve the adopted goals and priorities of the WRIA 1 Watershed Management Plan.

Model outputs for the Lower Nooksack Water Budget are summarized by sub-watersheds (drainages) and point locations (nodes). In general, due to changes in land use over time and changes to available streamflow and climate data, the water budget for any watershed needs to be updated periodically. Further detailed information about data sources is provided in review packets developed for specific technical components including climate, streamflow and groundwater level, soils and land cover, and water use.

Purpose: This project involves assembling a wide range of existing data related to the WRIA 1 and specifically the Lower Nooksack Subbasin, updating existing data sets and generating new data sets. Data will be used as input to various hydrologic, climatic and geomorphic components of the Topnet-Water Management (WM) model, but will also be available to support other modeling efforts in WRIA 1. Much of the data used as input to the Topnet model is publicly available and maintained by others, (i.e., USGS DEMs and streamflow data, SSURGO soils data, University of Washington gridded meteorological data). Pre-processing is performed to convert these existing data into a format that can be used as input to the Topnet model. Post-processing of Topnet model ASCII-text file outputs is subsequently combined with spatial data to generate GIS data that can be used to create maps and illustrations of the spatial distribution of water information. Other products generated during this project will include documentation of methods, input by WRIA 1 Joint Board Staff Team during review and comment periods, communication tools developed for public engagement and public comment on the project.

In order to maintain an organized system of developing and distributing data, Lower Nooksack Water Budget project collaborators should be familiar with standards for data management described in this document, and the following issues related to generating and distributing data: 1. Standards for metadata and data formats 2. Plans for short-term storage and data management (i.e., file formats, local storage and back up procedures and security) 3. Legal and ethical issues (i.e., intellectual property, confidentiality of study participants) 4. Access policies and provisions (i.e., how the data will be made available to others, any restrictions needed) 5. Provisions for long-term archiving and preservation (i.e., establishment of a new data archive or utilization of an existing archive) 6. Assigned data management responsibilities (i.e., persons responsible for ensuring data Management, monitoring compliance with the Data Management Plan)

This resource is a subset of the LNWB Ch03 Data Processes Collection Resource.

Unlock the power of 51M+ verified locations across Europe with high-precision geospatial data. Featuring 50+ enriched attributes including coordinates, building type, and geometry. Our AI-powered dataset ensures unmatched accuracy through advanced deduplication and enrichment. With 30+ years of industry expertise, we deliver trusted, customizable data solutions for mapping, navigation, urban planning, and marketing, empowering smarter decision-making and strategic growth.

Key use cases of Geospatial data have helped our customers in several areas:

1. Gain a Competitive Edge with Smarter Mapping : Use geospatial data to analyse competitors, identify high-traffic zones, and optimize locations for maximum impact.
2. Enhance Navigation & Location-Based Engagement : Improve turn-by-turn navigation, EV charging station discovery, and real-time travel insights for seamless customer experiences.
3. Find High-Value Locations for Business Growth : Leverage geospatial intelligence to select profitable retail sites, franchise locations, and warehouses with precision.
4. Streamline Deliveries & Address Validation : Improve shipping accuracy, reduce failed deliveries, and optimize courier routes for better customer satisfaction.
5. Drive Smarter Decisions with Spatial Analysis : Utilize location intelligence for disaster risk assessment, public health campaigns, and agricultural planning.

Unlock the power of 4.5M+ verified locations across Italy with high-precision geospatial data. Featuring 50+ enriched attributes including coordinates, building type, and geometry. Our AI-powered dataset ensures unmatched accuracy through advanced deduplication and enrichment. With 30+ years of industry expertise, we deliver trusted, customizable data solutions for mapping, navigation, urban planning, and marketing, empowering smarter decision-making and strategic growth.

Key use cases of Geospatial data have helped our customers in several areas:

1. Gain a Competitive Edge with Smarter Mapping : Use geospatial data to analyse competitors, identify high-traffic zones, and optimize locations for maximum impact.
2. Enhance Navigation & Location-Based Engagement : Improve turn-by-turn navigation, EV charging station discovery, and real-time travel insights for seamless customer experiences.
3. Find High-Value Locations for Business Growth : Leverage geospatial intelligence to select profitable retail sites, franchise locations, and warehouses with precision.
4. Streamline Deliveries & Address Validation : Improve shipping accuracy, reduce failed deliveries, and optimize courier routes for better customer satisfaction.
5. Drive Smarter Decisions with Spatial Analysis : Utilize location intelligence for disaster risk assessment, public health campaigns, and agricultural planning.

Unlock the power of 4.7M+ verified locations across the UK with high-precision geospatial data. Featuring 50+ enriched attributes including coordinates, building type, and geometry. Our AI-powered dataset ensures unmatched accuracy through advanced deduplication and enrichment. With 30+ years of industry expertise, we deliver trusted, customizable data solutions for mapping, navigation, urban planning, and marketing, empowering smarter decision-making and strategic growth.

Key use cases of Geospatial data have helped our customers in several areas:

1. Gain a Competitive Edge with Smarter Mapping : Use geospatial data to analyse competitors, identify high-traffic zones, and optimize locations for maximum impact.
2. Enhance Navigation & Location-Based Engagement : Improve turn-by-turn navigation, EV charging station discovery, and real-time travel insights for seamless customer experiences.
3. Find High-Value Locations for Business Growth : Leverage geospatial intelligence to select profitable retail sites, franchise locations, and warehouses with precision.
4. Streamline Deliveries & Address Validation : Improve shipping accuracy, reduce failed deliveries, and optimize courier routes for better customer satisfaction.
5. Drive Smarter Decisions with Spatial Analysis : Utilize location intelligence for disaster risk assessment, public health campaigns, and agricultural planning.

Welcome to the City of Bozeman Floodplain Data. The existing floodplain designations for Bozeman Creek and its tributaries are in the process of being changed by the Federal Emergency Management Agency (FEMA). The purpose of these data are to depict FEMA’s proposed floodplain designations and map changes. These data are intended to serve as an educational public engagement tool.You can find the City of Bozeman Floodplain webpage here. This floodplain map tool contains GIS information to help identify proposed and existing floodplain designations in the City of Bozeman established by the Federal Emergency Management Agency (FEMA). Contact the City Floodplain Administrator, Brian Heaston at 406-582-2280 or email bheaston@bozeman.net with questions. This GIS information does not imply that the subject property will or will not be free from flooding or damage. A property not in a designated floodplain may be damaged by a flood greater than predicted by FEMA or from a local drainage problem not shown on the floodplain map. Reliance on this GIS information does not create liability on the part of City of Bozeman or any officer or employee thereof from any damage that results from reliance on this information.

The Knowledge Exchange, Spatial Analysis and Healthy Urban Environment (KESUE) project has extended previous work from a project that examined the health impacts of a regeneration scheme in Belfast (the Physical Activity in the Regeneration of Conswater, PARC project) in order to develop evidence and policy tools that link features of the built environment with physical activity in the cities of Belfast and Derry-Londonderry in Northern Ireland. It has used this data to help shape policy decisions in areas such as physical activity, park management, public transport and planning. Working with a range of local partners who part-funded the project (City Councils in Belfast and Derry-Londonderry, Public Health Agency, Belfast Healthy Cities and Department of Regional Development), this project has mapped all the footpaths in the two cities (covering 37 per cent of the NI population) and employed this to develop evidence used in strategies related to healthy urban planning. Using Geographic Information Systems (GIS), the footpath network has been used as a basis for a wide range of policy-relevant analyses including pedestrian accessibility to public facilities, site options for new infrastructure and assessing how vulnerable groups can access services such as pharmacies. Key outputs have been Accessibility Atlases and maps showing how walkability of the built environment varies across the two cities. In addition to generating this useful data, the project included intense engagement with potential users of the research, which has led to its continued uptake in a number of policies and strategies, creating a virtuous circle of research, implementation and feedback.

The Town of Eastham opted to create a District of Regional Planning Concern (DCPC) for the North Eastham area. A DCPC allows for creation and adoption of special regulations. These special regulations direct how development and land use are regulated within a district. Once incorporated into the local zoning bylaw, Town agencies oversee development and land use within the district.Over the past seven months, the Town worked with the Cape CoD Commission to development Implementing Regulations for the North Eastham DCPC This process involved community engagement, including two public workshops, two public surveys, multiple Planning Board workshops, and several public hearings. The feedback from these meetings informed the development of the proposed regulations.