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The EarthCube Technology and Architecture Committee working groups needed current information on the development of existing EarthCube-funded projects (e.g. building blocks, conceptual designs, and research coordination networks) to fulfill the goals of the working groups (e.g. gap analysis, use cases, standards bodies and testbed). The aims of this study include a compilation of planned outcomes, an assessment of current work and an investigation of interests in research collaboration among select EarthCube-funded projects.

Twenty-four principal investigators of 24 different EarthCube projects completed the Funded Projects Questionnaire composed of 35 questions in March and April 2015.

The survey response rate was 100 per cent and included a diversity of results ranging from planning stages to early development to final development. The funded projects in this study received awards in 2013 and 2014.

The results are EarthCube-specific and are not generalizable. Suggestions for future research include integration of crosscutting disciplines and perspectives, best practices, guidelines and standards for broader impact.

This study identified potential collaboration opportunities, use cases and gaps (e.g. unmet architectural, functional, operational, organizational and/or technical needs).

The impact on society include an improved understanding of the various EarthCube-funded projects and potential for collaboration within and across multiple disciplines.

This study contributed to the development of select outputs for EarthCube-funded projects’ presentations, Tech Hands Meeting, 2015 All Hands Meeting, select working groups’ outcomes and EarthCube Strategic Technology Plan and is of value to stakeholders, scientists and users.

The purpose of this paper is to identify the gaps and potential future research avenues in the big data research specifically in the construction industry.

The paper adopts systematic literature review (SLR) approach to observe and understand trends and extant patterns/themes in the big data analytics (BDA) research area particularly in construction-specific literature.

A significant rise in construction big data research is identified with an increasing trend in number of yearly articles. The main themes discussed were big data as a concept, big data analytical methods/techniques, big data opportunities – challenges and big data application. The paper emphasises “the implication of big data in to overall sustainability” as a gap that needs to be addressed. These implications are categorised as social, economic and environmental aspects.

The SLR is carried out for construction technology and management research for the time period of 2007–2017 in Scopus and emerald databases only.

The paper enables practitioners to explore the key themes discussed around big data research as well as the practical applicability of big data techniques. The advances in existing big data research inform practitioners the current social, economic and environmental implications of big data which would ultimately help them to incorporate into their strategies to pursue competitive advantage. Identification of knowledge gaps helps keep the academic research move forward for a continuously evolving body of knowledge. The suggested new research avenues will inform future researchers for potential trending and untouched areas for research.

Identification of knowledge gaps helps keep the academic research move forward for continuous improvement while learning. The continuously evolving body of knowledge is an asset to the society in terms of revealing the truth about emerging technologies.

There is currently no comprehensive review that addresses social, economic and environmental implications of big data in construction literature. Through this paper, these gaps are identified and filled in an understandable way. This paper establishes these gaps as key issues to consider for the continuous future improvement of big data research in the context of the construction industry.

This paper aims to convert surface data directly to a three-dimensional (3D) stereolithography (STL) part. The Geographic Information Systems (GIS) data available for a terrain are the data of its surface. It doesn’t have information for a solid model. The data need to be converted into a three-dimensional (3D) solid model for making physical models by additive manufacturing (AM).

A methodology has been developed to make the wall and base of the part and tessellates the part with triangles. A program has been written which gives output of the part in STL file format. The elevation data are interpolated and any singularity present is removed. Extensive search techniques are used.

AM technologies are increasingly being used for terrain modeling. However, there is not enough work done to convert the surface data into 3D solid model. The present work aids in this area.

The methodology removes data loss associated with intermediate file formats. Terrain models can be created in less time and less cost. Intricate geometries of terrain can be created with ease and great accuracy.

The terrain models can be used for GIS education, educating the community for catchment management, conservation management, etc.

The work allows direct and automated conversion of GIS surface data into a 3D STL part. It removes intermediate steps and any data loss associated with intermediate file formats.

In the past 25 years, and as recent as 2011, all external evaluations of the Quality Improvement Organization (QIO) Program have found its impact to be small or difficult to discern. The QIO program costs about $200 million on average to administer each year to improve quality of healthcare for people of 65 years or older. The program was created to address questionable quality of care. QIOs review how care is provided based on performance measures. The paper aims to discuss these issues.

In 2012, the author supported the production of quarterly reports and reviewed internal monitoring and evaluation protocols of the program. The task also required reviewing all previous program evaluations. The task involved many conversations about the complexities of the program, why impact is difficult to discern and possible ways for eventual improvement. Process flow charts were created to simulate the data life cycle and discrete event models were created based on the sequence of data collection and reporting to identify gaps in data flow.

The internal evaluation uncovered data gaps within the program. The need for a system of specification rules for data conceptualization, collection, distribution, discovery, analysis and repurposing is clear. There were data inconsistencies and difficulty of integrating data from one instance of measurement to the next. The lack of good and reliable data makes it difficult to discern true impact.

The prescription is for a formal data policy or data governance structure to integrate and document all aspects of the data life cycle. The specification rules for governance are exemplified by the Data Documentation Initiative and the requirements published by the Data Governance Institute. The elements are all in place for a solid foundation of the data governance structure. These recommendations will increase the value of program data.

The model specifies which agency units must be included in the governance authority and the data team. The model prescribes in detail a data governance model to address gaps in the life cycle. These prescriptive measures will allow the program to integrate all of its data. Without this formal data governance structure, the QIO program will be undetermined by the persistent lack of good data for monitoring and evaluation.

The chapter assesses the state of research and gender-specific data in maritime shipping and ports. This is crucial for implementing and promoting Sustainable Development Goal 5 ‘Achieve gender equality and empower all women and girls’ in the sector under study. Moreover, the present chapter examines whether progress has been made regarding the availability of gender-related data and research in the port sector.

An extensive review of the literature covering gender-related research in the shipping and port sectors going back to the pre-1990 period has been carried out. Next, data from the Port Performance Scorecard established under the United Nations Conference for Trade and Development (UNCTAD) TrainForTrade (TfT) Port Management Programme (PMP) is analysed, covering the 2015–2020 period. Last, this research is complemented by the results of a survey conducted in 2021 across UNCTAD’s TfT port network.

The literature review identified the main gender dimensions affecting maritime shipping and ports, namely health, empowerment, economic, and education. These results were completed by insights generated by the analysis of gender-related data obtained through selected member ports of the UNCTAD TfT PMP. Overall, the data provided information about the state of play and the existing data gaps and limitations relating to mainstreaming the gender dimension in maritime shipping and ports. It confirmed that traditional stereotypes about the type of job functions that can be fulfilled by women remain prevalent in these two sectors. In this context, the chapter concludes that improving data availability and accessibility in maritime shipping and ports is imperative to advance research and evidence-based policymaking that promote gender equality in maritime transport. Closing the data gap and refining data on gender across the maritime supply chain sector is therefore key. As available data are insufficiently accessible and highly aggregated and which in turn limits the analytical scope, the present chapter recommends that a framework for a Maritime Shipping and Port Gender Equality and Diversity Index be established while leveraging existing data and efforts, including by UNCTAD.

The purpose of this paper is to assess whether current routinely available population level data are adequate for assessing the health needs of vulnerable children.

The paper presents a review of routinely available population level data relating to 23 vulnerable child groups.

Data were available to measure how many children may be affected locally for seven groups (30 per cent) (looked after children, care leavers, absent or excluded pupils, children in poverty, young offenders, children in need and children assessed to be at risk of social services). Partial data were available for 11 (48 per cent) groups and no data were identified for five (22 per cent) groups. At least one measure of health and well being status was identified for three groups (13 per cent) (care leavers, children assessed to be in need of social services and children assessed to be at risk by social services). For seven groups (30 per cent), a measure of health status was identified for some children in the group. No measure of health status was identified for 13 groups (57 per cent).

The review only considered routinely published data that can be reported for all counties or unitary authorities in England. Although every effort was taken to ensure complete identification, it is still possible that some data sources may have been missed.

The gaps in available data to monitor vulnerable children's health will make the task of ensuring their needs are appropriately represented in local needs assessment and health strategies more difficult. The current service reforms offer an opportunity to address the data gaps.

Data relating to some vulnerable child groups was reviewed in 2006 when a number of recommendations were made. This paper updates and broadens that review and reports on progress made against the 2006 recommendations. The findings of the paper have implications for policy makers and commissioners of children's services.

The purpose of this paper is to assess the relevance of the glass ceiling effect, according to which the gender log wage gap accelerates in the upper tail of the wage distribution, at the firm level.

The empirical analysis is based on a sample of 4,654 employees, working in a French private company from the Defence and Aerospace sector. Quantile wage regressions were used to study whether a glass ceiling effect exits at the firm level. The difference between the male and female wage distributions is also decomposed into two components, one due to differences in labour market characteristics between men and women and one due to differences in rewards to these individual characteristics.

It was found that the gender wage gap measured through OLS is quite low, less than 8 per cent when controlling for age, experience, qualification and location. It remains rather flat along the wage distribution, a result which casts doubt on the glass ceiling theory. The gender gap is mainly due to differences in labour market characteristics rather than to differences in the rewards of these characteristics, especially among executives. Finally, women face a lower probability of reaching higher hierarchical positions within the firm.

Taking into account firm effects matters when measuring the magnitude of the gender wage throughout the wage gap distribution.

This paper presents original estimates of the gender wage gap with an unusual, firm‐based sample of workers.

Climate change data and predictions for the Himalayas are very sparse and uncertain, characterized by a “Himalayan data gap” and difficulties in predicting changes due to topographic complexity. A few reliable studies and climate change models for Nepal predict considerable changes: shorter monsoon seasons, more intensive rainfall patterns, higher temperatures, and drought. These predictions are confirmed by farmers who claim that temperatures have been increasing for the past decade and wonder why the rains have “gone mad.” The number of hazard events, notably droughts, floods, and landslides are increasing and now account for approximately 100 deaths in Nepal annually. Other effects are drinking water shortages and shifting agricultural patterns, with many communities struggling to meet basic food security before climatic conditions started changing.

The aim of this paper is to examine existing gaps between current climate models and the realities of local development planning through a case study on flood risk and drinking water management for the Municipality of Dharan in Eastern Nepal. This example highlights current challenges facing local-level governments, namely, flood and landslide mitigation, providing basic amenities – especially an urgent lack of drinking water during the dry season – poor local planning capacities, and limited resources. In this context, the challenge for Nepal will be to simultaneously address increasing risks caused by hazard events alongside the omnipresent food security and drinking water issues in both urban and rural areas. Local planning is needed that integrates rural development and disaster risk reduction (DRR) with knowledge about climate change considerations. The paper concludes with a critical analysis of climate change modeling and the gap between scientific data and low-tech and low capacities of local planners to access or implement adequate adaptation measures. Recommendations include the need to bridge gaps between scientific models, the local political reality and local information needs.

The study aimed to focus on how well information technology (IT) was supporting business processes in small‐ and medium‐sized enterprises (SMEs).

The study collected data using a questionnaire that incorporated the 12 processes of the American Productivity and Quality Center's (APQC) process classification framework. Structured interviews were conducted with managers in 66 SMEs.

The data indicated the importance of each process and how well IT supported each process. The following two core business processes were identified as strategically most important: deliver products and services, and manage customer service. Although the evidence indicated that the most important business processes were supported at an acceptable level, IT support was found to be low for many business processes. IT support also varied considerably across the sample, indicating that some firms have much higher IT support for business processes than others.

A limitation of the study is that it used a new instrument. Also, all the firms were SMEs in one part of one country. The study created an instrument that can be used by managers as a diagnostic tool to help SMEs identify areas for business improvement.

The study indicates that the business process view provides a useful lens for studying IT support. There seems to be much potential for SMEs to improve their IT support for some business processes.

The focus on IT support for business processes is original, especially by examining support for the broad range of processes of the APQC's model.