Project Characteristics Research Articles

Identifying the characteristics of public-private partnership projects on green energy in developing countries with different incomes

The object of the study is public-private partnership projects in green energy in developing countries. The problematics of the study is based on the intersection of the current problems of improving energy efficiency and environmental friendliness of energy innovations. The problem of analyzing such projects was solved with the following results: The findings of the study indicate the importance of country income as a factor influencing investment in public-private partnership projects in green energy. The analysis indicates the importance of the country's income as a factor influencing the established technological structure of public-private partnership projects in the green energy sector. It is proved that energy efficiency significantly depends on the technological structure of public-private partnership projects in green energy. The obtained results are explained by assuming the dependence of public-private partnership projects in green energy on the income level of the economy, based on Wallis one-way analysis of variance and cross-tabulation. Mann-Whitney U test was used to explain the dependence of energy efficiency on the technological structure of such projects. The particularity of this study is the analysis of the technological structure of public-private partnership projects in green energy, taking into account the specifics of developing countries and the application of their clustering. This research is of practical significance in the possibility of applying the results obtained by the authorities for the creation and implementation of public-private partnership projects in the field of green energy, as well as by energy companies implementing new technologies using water, wind and solar energy.

Construction Cost-Influencing Factors: Insights from a Survey of Engineers in Saudi Arabia

Cost overruns represent a continuous challenge within the construction industry, frequently affecting the success of projects. This study explores the factors influencing cost during the construction phase in Saudi Arabia, utilizing data from a survey of 1076 engineers working in the Saudi construction industry. The results identify a number of cost-related factors, including inadequate project management, poor cost estimation, and design errors. Interestingly, some factors, such as currency exchange rate fluctuations and social and cultural influences, were found to have a limited impact on construction costs. Furthermore, the study highlights the role of experience and education level in shaping engineers’ perceptions of these cost factors. The study employs statistical analysis, including Pearson’s chi-squared test, to demonstrate associations between demographics, project characteristics, and cost-influencing factors. The findings suggest the need for refined project management practices, enhanced technical training, and the implementation of digital technologies such as Construction 4.0 to mitigate cost-related risks. This research provides significant insights for construction professionals and policymakers seeking to enhance cost management within the Saudi construction sector, thereby contributing to the ongoing development initiatives aligned with Saudi Arabia’s Vision 2030.

Innovative and Cost‐Effective Approaches to the Measurement of Sediment Levels in Small Water Reservoirs

ABSTRACTSedimentation in small water reservoirs poses a critical challenge with significant environmental, economic, and social implications. To address this issue, this study will employ three measurement techniques—GNSS RTK Trimble R8s, Echolot HDS LIVE 7 with Active Imaging 3‐in‐1, and the Mivardi Carp Scout bait boat—to assess sediment levels in Žebětínský Pond in Brno, Czech Republic. The research reveals that each method offers distinct advantages and limitations. Through measurement and triangulated networks, the study creates a digital terrain model that facilitates the determination of reservoir volume and sediment levels. The comparison shows that the cost‐effective alternatives, Echolot HDS LIVE 7 and Mivardi Carp Scout, provide sufficiently accurate results. The evaluation shows that while the GNSS RTK Trimble R8s has the highest level of accuracy and is unique in its ability to measure both along the shoreline of the reservoir and the hard bottom, it comes with increased costs and logistical challenges. The Echolot HDS LIVE 7 and Mivardi Carp Scout offer efficient, cost‐effective solutions that are suitable for a quick estimate of sediment thickness. This research contributes to the use of reliable mathematical models and water management strategies, advocating for a pragmatic approach to the selection of methods based on the project characteristics. The study provides valuable insights into sediment measurement techniques, guiding future endeavors in reservoir management and environmental conservation. It is also used to easily indicate the loss of arable land in the catchment upstream of the reservoir.

Empirical Study on Delays in Highway Projects: A Comparative Analysis of Small and Large Projects

Delays in National Highway projects, regardless of their geographical location, have exerted a substantial impact on project performance and yielded unfavourable economic consequences. The majority of these projects in India are implemented by Public-Private Partnerships (PPPs), which use a wide range of contract types, including traditional ones such as item rate contracts and bills of quantity, in addition to more modern alternatives such as build operate transfer, engineering procurement and transfer, and recently developed hybrid models. This study examines and compares the reasons of critical delays in national highway projects in Himachal Pradesh with project characteristics. This mixed-methods study gathered comprehensive data from project participants using qualitative analysis and a survey questionnaire. Interviews and document analysis identified delay factors, which were then assessed through a structured questionnaire distributed to a representative sample of project participants. The findings highlight critical delay factors in National Highway projects in Himachal Pradesh and offer insights into the unique challenges faced by large PPP projects and small traditional projects. Despite the small sample size of 134 survey responses, the findings are significant but may have limited applicability to other infrastructure projects due to socio-economic and geographic variations. This suggests a research gap indicating that further analysis is needed to understand the challenges in EPC and PPPs for large hilly road projects, along with a focused study on organizational culture to assess highway project performance. This study contributes empirical data to the literature about the steep National Highway projects in Himachal Pradesh. Policymakers, project specialists, and stakeholders may ascertain the reasons of delays and formulate targeted actions to enhance project efficiency.

Research on sedimentation characteristics of the end bend water extraction project of cascade reservoir backwater

Abstract The operation mode of upstream and downstream cascade power stations significantly impacts the river bed in the water intake section, leading to complex sediment deposition characteristics in the curved river section at the reservoir’s end. In this research, a standard physical model for bed load and suspended load at a scale of λl=λh=100 was conducted, combined with the operation mode of upstream and downstream power stations, to investigate the sediment deposition patterns in the intake section and to study the sediment deposition characteristics in the intake area. The experimental results reveal that bed load sediment predominantly accumulates on the right bank (convex bank) of the river, with no bed load sediment accumulation at the mushroom head layout of the water intake project on the left bank (concave bank). When the operation of upstream and downstream power stations is uncoordinated, suspended sediment settles in the water intake section, with no sediment accumulation in the local area of the mushroom head of the intake due to the disturbance effect. Safety sensitivity analysis indicates that the safety of the water intake project can be ensured.

공공디자인 대상으로서 공공공간의 해석과 적용실태 분석

This study was conducted to diagnose the phenomenon in which the Public Design Act only applies to facilities, supplies, and visual images, while the ordinance includes public spaces, thereby conflicting with the higher law, and to examine the legitimacy of including public spaces as subjects of public design. Accordingly, the history and structure of laws related to public design were confirmed through the website of the National Law Information Center, and the current status of application of public spaces was analyzed from four perspectives: related laws, subjects of application of ordinances, public design projects, and related fields through prior studies and research materials. As a result of the study, the current status of application was diagnosed from the perspectives of ambiguity in legal interpretation, limitations in application of ordinances, characteristics of public design projects, and scope of recognition in related fields, and the conclusion was reached that efforts to revise the law are necessary to include public spaces as subjects of public design.

Production of cultural and educational programs and cultural industries: on the issue of approaches to television analysis

INTRODUCTION. Television activity is devalued due to the loss of its exclusivity in the creation of video content and dissemination of video information. However, television has creative and technical resources, professionals, a school for producing programs aimed not only at supporting the consumer society and political manipulations, but also at developing fundamental meanings and strengthening values – culture, memory, national heritage. The gap that has occurred between the perception of television and its advantages and experience in creating content is a problem affecting the development of the media industry and television journalism. At the same time, the production of television special projects based on cultural events is related to the direction of cultural industries that is relevant for Russia, which allows us to rethink the meaning of television. The purpose of the study is to compare the creative characteristics of special TV projects with the properties of cultural industries and record the identified correspondences.MATERIALS AND METHODS. The empirical basis of the study is special projects of the regional TV channel “Saint Petersburg”, which are representations of cultural events based on live broadcast technology and using expressive means of television. The study used the case study method, as well as a comparative analysis of approaches to creating television projects and criteria of cultural industries.RESULTS AND DISCUSSION. A comparison of modern special television projects with the theory of creative industries revealed similarities in such positions as: a) high risks; b) the opposition of creativity and commerce; c) high production costs and low distribution costs; d) attitude to semipublic goods, etc.CONCLUSION. The models of such television projects correspond to the characteristics of cultural industries, which develops a theoretical view of television and actualizes its possibilities in the context of media transformation.

Main contents and revision direction of the Urban Complex Development Act

The Act on Support for Urban Complex Development was enacted and promulgated on February 6, 2024. It is scheduled to take effect on February 7, 2025. This new law encourages private project implementers to actively participate in urban complex development, unlike the urban public housing complex project (under the public housing special law) that was introduced in accordance with the government’s plan to drastically expand the supply of 3080+ publicly led metropolitan housing announced on February 4, 2021. The urban public housing complex project is a system designed to establish a new business model for station areas, semi-industrial areas, and low-rise residential areas that are underutilized and aging because of difficulties with redevelopment and reconstruction projects. Public institutions have become project implementers instead of existing cooperative-centered redevelopment and reconstruction projects. The urban public housing complex project is a development project that utilizes comprehensive acquisition (including land expropriation) to quickly promote the project and supply new buildings in the form of compensation in kind if the landowner so desires. However, the complex development project introduced in the Act on Support for Urban Complex Development differs significantly from the plan described above in that the private sector, including landowners, trustees, and real estate investment trusts (REITs), become the main project implementers, promoting the project by utilizing management, disposal plans, and sales claims. In this article, I examine the concept and characteristics of complex development projects, procedures, and special provisions for these projects and identify problems and revision directions for relevant laws. Since complex development projects utilize management, disposal plans, and sales claims as business methodsand the project target is an urban area with a high concentration of old and substandardbuildings, I describe such projects by comparing them with the provisions of the Urban and Housing Environment Improvement Act, which regulates redevelopment and reconstruction projects. Finally, I suggest that necessary actions to smoothly implement complex development projects include securing differentiation from other development projects, supplementing specific provisions on REITs as the newly introduced project implementers, and improving the sales claim system and consent rate centered on land area.

Design and application of omnidirectional mirror for catadioptric optical system dedicated to high-speed video registration of lightning

Omnidirectional optical mirrors are widely used in many scientific, industrial and military applications but there is still a lot to do to improve their projection characteristics. The paper presents design method for a novel class of omnidirectional mirrors characterized by their settable reflection angle and 3D/2D image projection. Such approach can effectively improve the mirrored image distribution on matrix of optical sensor. A complex mirror curvature was manufactured with application of computerized numerical control milling machines and Physical Vapor Deposition technique. Three prototypes with 15°, 30° and 45° vertical top view angles were tested. Mirrors were applied to get a set of wide range cloud-to-ground lightning video registrations. Analysis of the high-speed video confirmed design assumptions, and using lightning location system data, enabled dimensioning and measurement of the lightning channel geometry in 3D. Proposed method can be easily implemented in other applications involving omnidirectional observation and photogrammetry.

A dual opposition learning-based multi-objective Aquila Optimizer for trading-off time-cost-quality-CO2 emissions of generalized construction projects

PurposeMost of the existing time-cost-quality-environmental impact trade-off (TCQET) analysis models have focused on solving a simple project representation without taking typical activity and project characteristics into account. This study aims to present a novel approach called the “hybrid opposition learning-based Aquila Optimizer” (HOLAO) for optimizing TCQET decisions in generalized construction projects.Design/methodology/approachIn this paper, a HOLAO algorithm is designed, incorporating the quasi-opposition-based learning (QOBL) and quasi-reflection-based learning (QRBL) strategies in the initial population and generation jumping phases, respectively. The crowded distance rank (CDR) mechanism is utilized to rank the optimal Pareto-front solutions to assist decision-makers (DMs) in achieving a single compromise solution.FindingsThe efficacy of the proposed methodology is evaluated by examining TCQET problems, involving 69 and 290 activities, respectively. Results indicate that the HOLAO provides competitive solutions for TCQET problems in construction projects. It is observed that the algorithm surpasses multiple objective social group optimization (MOSGO), plain Aquila Optimization (AO), QRBL and QOBL algorithms in terms of both number of function evaluations (NFE) and hypervolume (HV) indicator.Originality/valueThis paper introduces a novel concept called hybrid opposition-based learning (HOL), which incorporates two opposition strategies: QOBL as an explorative opposition and QRBL as an exploitative opposition. Achieving an effective balance between exploration and exploitation is crucial for the success of any algorithm. To this end, QOBL and QRBL are developed to ensure a proper equilibrium between the exploration and exploitation phases of the basic AO algorithm. The third contribution is to provide TCQET resource utilizations (construction plans) to evaluate the impact of these resources on the construction project performance.

The performance of priority rules for the decentralized resource-constrained multi-project scheduling

Decentralized resource-constrained multi-project scheduling (DRCMPSP) is becoming increasingly common in construction, supply chains, and many other industrial disciplines. DRCMPSP faces difficult decisions in resolving resource conflicts to generate a baseline schedule to optimize global objectives. We propose an agent-based approach to address the DRCMPSP based on two global objectives: average project delay and total project delay. A heuristic based on the priority rule (PR) is developed to coordinate the global resource allocation. A comprehensive analysis of 30 PRs was conducted on 16,000 portfolios containing 48,000 projects . We confirmed that using the same PR to allocate global resources on all occasions often results in unnecessarily poor performance. The best PR depends on project and portfolio characteristics such as serial/parallel indicators, global resource distribution, and tightness. Moreover, the best PR differs from various perspectives (e.g., projects and portfolios). We summarized our results in three decision tables and further distilled these results for practical use, which only provide a rough estimate of the project and portfolio characteristics.

Analysis of the Spatial Characteristics and Influencing Factors of Large-Scale Land Acquisition Projects in Southeast Asia

Southeast Asia is an essential region for companies carrying out large-scale land acquisitions (LSLAs). Exploring the distribution patterns and influencing factors of LSLA projects in this region is of great practical significance for summarizing the characteristics of LSLA projects in Southeast Asia, for gaining a thorough understanding of LSLA project development rules, and for formulating reasonable policies to guide local LSLA projects. This study explores the spatial distribution and influencing factors of LSLA projects in Southeast Asia using the mean center method, the kernel density estimation method, and the grey correlation method. The findings indicate the following: Firstly, the majority of LSLA projects in Southeast Asia are located in the Indo-China Peninsula, Cambodia, Myanmar, Laos, and other countries, which represent significant regions of interest for LSLA projects in this region. Secondly, the spatial distribution of LSLA intention projects and LSLA contract projects in Southeast Asia is similar, whereas LSLA production projects differ from the former two. Thirdly, the scale of LSLA projects in Southeast Asia is closely related to the host country’s natural resources, socio-economic conditions, governance, and market environment. The total GDP, per capita arable land area, net foreign direct investment inflow, and political stability have been identified as exerting a significant influence on investment corporations’ selection of LSLA host countries.

Predicting Extension of Time and Increasing Contract Price in Road Infrastructure Projects Using a Sugeno Fuzzy Logic Model

Road infrastructure plays a crucial role in the development of countries, significantly influencing economic growth, social progress, and environmental sustainability. Major infrastructure projects are frequently challenged by substantial risks and uncertainties, leading to delays, budget overruns, and compromised quality. These issues can undermine the economic viability and efficiency of projects, making effective risk management essential for minimizing negative impacts and ensuring project success. For these reasons, a study was conducted using a Sugeno fuzzy logic system applied to completed projects. The resulting model is based on 10 project characteristics and provides highly accurate predictions for Extension of Time (EoT) and Increasing Contract Price (ICP). By utilizing this model, project management can be significantly improved through more accurate forecasting of potential delays and cost overruns. The high precision of the Sugeno fuzzy logic system enables better risk assessment and proactive decision-making, allowing project managers to implement targeted strategies to mitigate risks and optimize project outcomes.

Remixing between imitation and originality: Exploring creative behaviors in scratch projects

Remixing is a balance between imitation and originality, which gets a lot of attention as an important source of creative behaviors. Exploring the relationship between the Scratch project and its remix would provide a new perspective for understanding users’ creative behaviors. To this end, this study used 20 projects and their 957 remixes as samples to analyze creative behavior in Scratch through quantitative statistics and correlation analysis. Three research questions are addressed: (1) What creative levels are there among the remixes? (2) What relationships are there between the project and its remixes? and (3) What creative trends are there indicated in the remixes? The main results are concluded as follows. First, four creative levels of remixes based on the SOLO taxonomy are found, including feature change, appearance change, element creation, and structure creation. Feature change has the highest sum of remixes, which indicates that most remixes are at a low creative level. Second, the internal characteristics of projects are related to the lower creative level of remix, while the external characteristics are attached to the higher creative level of remix. Finally, the two-level, three-level, and four-level iteration chain of remixes are found, in which remixes with high creativity is more likely to inspire remixes with lower or equal creativity. Based on these results, suggestions for further research and improvement are discussed. This study has important implications for understanding the creative level of remix among users in programming community and guiding users to make valuable remixes.

Forecasting the outcomes of construction contract disputes using machine learning techniques

PurposeThis study aims to develop a predictive model using machine learning techniques to forecast construction dispute outcomes, thereby minimizing economic and social losses and promoting amicable settlements between parties.Design/methodology/approachThis study develops a novel conceptual model incorporating project characteristics, root causes, and underlying causes to predict construction dispute outcomes. Utilizing a dataset of arbitration cases in Türkiye, the model was tested using five machine learning algorithms namely Logistic Regression, Support Vector Machines, Decision Trees, K-Nearest Neighbors, and Random Forest in a Python environment. The performance of each algorithm was evaluated to identify the most accurate predictive model.FindingsThe analysis revealed that the Support Vector Machine algorithm achieved the highest prediction accuracy at 71.65%. Twelve significant variables were identified for the best model namely, work type, root causes, delays from a contractor, extension of time, different site conditions, poorly written contracts, unit price determination, penalties, price adjustment, acceptances, delay of schedule, and extra payment claims. The study’s results surpass some existing models in the literature, highlighting the model’s robustness and practical applicability in forecasting construction dispute outcomes.Originality/valueThis study is unique in its consideration of various contract, dispute, and project attributes to predict construction dispute outcomes using machine learning techniques. It uses a fact-based dataset of arbitration cases from Türkiye, providing a robust and practical predictive model applicable across different regions and project types. It advances the literature by comparing multiple machine learning algorithms to achieve the highest prediction accuracy and offering a comprehensive tool for proactive dispute management.

Comparing Developer Attraction and Turnover in OSS vs. OSS4SG Projects: An MSR Study

Open source for social good (OSS4SG) projects are projects whose overarching goal focuses on solving a societal issue and driving positive change. Despite the societal importance of such projects and their alignment with the open-source ideology at its very core, there is a clear lack of understanding of the unique characteristics and operational dynamics of OSS4SG projects. In this work, we use Mining Software Repository (MSR) techniques to empirically investigate the community dynamics and project characteristics of OSS4SG projects compared to OSS projects. We leveraged the GitHub API and GraphQL to mine a dataset of 290 projects (199 OSS4SG, 91 OSS) and answer our main research questions: RQ1: How stable are OSS4SG compared to OSS in terms of newcomers and leavers? RQ2: To what extent do turnover and retention of contributors change over time for OSS vs OSS4SG? Namely, we studied and compared the rates at which contributors joined and left OSS and OSS4SG projects at different stages of life (early, mid, late). We classified projects as attractive (high join rate and low leave rate), unattractive (low join rate and high leave rate), stable (low join rate and low leave rate), and unstable (high join rate and high leave rate). Our results show that the majority of OSS4SG projects (60%) are stable, while the majority of OSS projects (74%) are unstable. Our results also show that OSS4SG retains more of their contributors and has less turnover. Looking at the join and leave rates for projects across different life stages, we found that the difference is significant when all stages of life and considered together. However, the difference is far less significant in the late stage of the project's lifespan, indicating that, as they mature, OSS becomes more similar to OSS4SG in terms of community dynamics.

Analyzing the Spatial Factors and Characteristics of Urban Regeneration Projects of Haebangchon Sinheung Market: From the Perspective of Henri Lefebvre’s Spatial Triad

Analyzing the Spatial Factors and Characteristics of Urban Regeneration Projects of Haebangchon Sinheung Market: From the Perspective of Henri Lefebvre’s Spatial Triad

Regulatory mechanisms orchestrating cellular diversity of Cd36+ olfactory sensory neurons revealed by scRNA-seq and scATAC-seq analysis

Recent discoveries have revealed remarkable complexity within olfactory sensory neurons (OSNs), including the existence of two OSN populations based on the expression of Cd36. However, the regulatory mechanisms governing this cellular diversity in the same cell type remain elusive. Here, we show the preferential expression of 79 olfactory receptors in Cd36+ OSNs and the anterior projection characteristics of Cd36+ OSNs, indicating the non-randomness of Cd36 expression. The integrated analysis of single-cell RNA sequencing (scRNA-seq) and scATAC-seq reveals that the differences in Cd36+/- OSNs occur at the immature OSN stage, with Mef2a and Hdac9 being important regulators of developmental divergence. We hypothesize that the absence of Hdac9 may affect the activation of Mef2a, leading to the up-regulation of Mef2a target genes, including teashirt zinc finger family member 1 (Tshz1), in the Cd36+ OSN lineage. We validate that Tshz1 directly promotes Cd36 expression through enhancer bindings. Our study unravels the intricate regulatory landscape and principles governing cellular diversity in the olfactory system.

An integrated multi-criteria decision making approach for selecting the starting location of railroad projects

PurposeThe successful completion of linear infrastructure construction projects such as railroads, roads, tunnels, and pipelines relies heavily on decision-making processes during planning phase. Professionals in the construction industry emphasize that determining the starting point of a linear infrastructure construction project is one of the most important decisions to be made in the planning phase. However, the existing literature does not specifically focus on selection of the starting point of the segments to be constructed. Therefore, it is of utmost importance to develop a multi-criteria decision-making (MCDM) model to support selection of the starting point of the segments to be constructed in linear infrastructure construction projects.Design/methodology/approachBased on the characteristics of the railroad projects and insights gathered from expert interviews, the appropriate criteria for the model were determined. Once the criteria were determined, a decision hierarchy was developed and the weights of the criteria (w_i) were calculated using DEcision MAking Trial and Evaluation Laboratory (DEMATEL) method. Then, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), COmplex PRoportional Assessment (COPRAS), and evaluation based on distance from average solution (EDAS) methods were used. The alternatives were ranked in terms of their priority with TOPSIS method based on relative closeness (Ci) of each alternative to the ideal solution, COPRAS method based on quantitative utility (Ui) for each alternative and EDAS method based on evaluation score (ASi) for all alternatives. The results were compared with each other.FindingsThe study reveals the effects of all criteria on the proposed model. The results of DEMATEL method indicated that quantity of aggregate (w_i = 0.075), ballast (w_i = 0.071), and sub-ballast (w_i = 0.069) are the most important criteria in starting location selection for railroads, where earthquake (w_i = 0.046), excavation cost (w_i = 0.054), and longest distance from borrow pit (w_i = 0.055) were found to be less important criteria. The starting location alternatives were ranked based on TOPSIS, COPRAS and EDAS methods. The A-1 alternative was selected as the most appropriate alternative (Ci = 0.64; Ui = 100%; ASi = 0.81), followed by A-6 alternative (Ci = 0.61; Ui = 97%; ASi = 0.73) and A-7 alternative (Ci = 0.59; Ui = 94%; ASi = 0.60). Even tough different methods were used, they provided compatible results where the same ranking was achieved except three alternatives.Originality/valueThis study identifies novel criteria for the starting location selection of railroad construction based on the data of a railroad project. This study uses different methods for selecting the starting location. Considering the project type and its scope, the model can be used by decision-makers in linear infrastructure projects for which efficient planning and effective location selection are critical for successful operations.

Incorporating citizen science into IUCN Red List assessments.

Many citizen scientists are highly motivated to help address the current extinction crisis. Their work is making valuable contributions to protecting species by raising awareness, identifying species occurrences, assessing population trends, and informing direct management actions, such as captive breeding. However, clear guidance is lacking about how to use existing citizen science data sets and how to design effective citizen science programs that directly inform extinction risk assessments and resulting conservation actions based on the International Union for Conservation of Nature (IUCN) Red List criteria. This may be because of a mismatch between what citizen science can deliver to address extinction risk and the reality of what is needed to inform threatened species listing based on IUCN criteria. To overcome this problem, we examined each IUCN Red List criterion (A-E) relative to the five major types of citizen science outputs relevant to IUCN assessments (occurrence data, presence-absence observations, structured surveys, physical samples, and narratives) to recommend which outputs are most suited to use when applying the IUCN extinction risk assessment process. We explored real-world examples of citizen science projects on amphibians and fungi that have delivered valuable data and knowledge for IUCN assessments. We found that although occurrence data are routinely used in the assessment process, simply adding more observations of occurrence from citizen science information may not be as valuable as inclusion of more nuanced data types, such as presence-absence data or information on threats from structured surveys. We then explored the characteristics of citizen science projects that have already delivered valuable data to support assessments. These projects were led by recognized experts who champion and validate citizen science data, thereby giving greater confidence in its accuracy. We urge increased recognition of the value of citizen science data within the assessment process.