Evaluating a public sector organisation for SDI Readiness – The case of a South African government department

Spatial data infrastructure (SDI) facilitates the collection and sharing of geographic information developed by different organisations. As a result, SDI initiatives are occurring in different countries. Various government departments are implementing SDI in order to contribute to the achievements of its objectives. SDI assessments to evaluate the implementation thereof is also occurring from local levels to international levels. This paper establishes the availability of geographic information within the Department of Environmental Affairs (DEA) by describing DEA’s contribution to the South African SDI objectives and by assessing DEA’s SDI readiness.The qualitative method was used to collect data. The techniques used in this research were literature review, interviews, mainly in-depth interview, document and internet analysis.The results indicate that geographic information is available and the department continues to make more means to make it available. They also reveal that there are some challenges with respect to accessibility. Currently there is a process to make it even more easily accessible. The results show DEA’s willingness and capacity to contribute to the South African SDI. The voluntary participation in SDI activities and the ability to obtain additional funding for geographic information is a clear indicator of DEA’s willingness to contribute to SASDI’s objectives. The results contribute to the body of knowledge that if an SDI is still in the early stages of development, it is challenging to make conclusions on some of the key SDI assessment indices. Future research is required once South African SDI has reached mature stages

Challenges and Opportunities for Spatial Data Infrastructure Development in Mozambique

Atumane, A. A. P., & Cabral, P. (2019). Challenges and Opportunities for Spatial Data Infrastructure Development in Mozambique. Journal of Map and Geography Libraries, 15(1), 7-27. https://doi.org/10.1080/15420353.2019.1661932The importance of access to spatial data for development and resource management is widely acknowledged worldwide. Unrestricted, reliable and efficient access to accurate, timely, and up-to-date spatial data may be achieved through a spatial data infrastructure. Thus, most developed countries implemented and continue to develop their spatial data infrastructure. In Africa, there is a growing number of governments committed to spatial data infrastructure development. This paper aims to contribute to initialize an spatial data infrastructure in Mozambique. We identified and characterized through a survey the government institutions producing, sharing, and using spatial data in the country to estimate their potential contribution to the development of the Mozambican spatial data infrastructure. We found 12 institutions producing 15 thematic datasets which can constitute the core of the spatial data infrastructure for Mozambique. Two government agencies have the technical skills and policies to make spatial data available to the public. Based on the possible contribution of these institutions, this paper proposes an spatial data infrastructure for Mozambique based on four pillars: i) organizational framework; ii) legal framework; iii) technical framework; and iv) accessibility.authorsversionpublishe

Improving the Availability of Space Research Spatial Data*

The rapid development of space technology and the increased interest in space exploration have resulted in the intensive observation of celestial bodies, mostly in the solar system, over the past decade with the prospect of an upward trend in the future. Large amounts of collected data on space bodies impose the need to develop the Spatial Data Infrastructure of Celestial Bodies at the general level to enable standardized organization and storage of these data, and their efficient use and exchange. To approach the development of such an infrastructure, it is necessary to investigate what data, as well as how and to what extent, are collected through space observation. It is also necessary to investigate how this data can be obtained. This paper provides an overview of planetary spatial data archives, data storage and retrieval methods, and their shortcomings in the context of easy search, download and interpretation of data, all with the aim of establishing Spatial Data Infrastructure of Celestial Bodies that would make space data more accessible to the public and non-planetary scientists

National spatial data infrastructure (NSDI) of Ukraine: what are its actual, feasible and simultaneously “correct” models?

Resume. The actual, feasible and simultaneously "correct" models of digital NSDI of Ukraine are considered in the work. A model of the existed digital NSDI system of Ukraine is named “actual”. This model already differs from the model defined by the [1]. As the latter is unlikely to be implemented in the near future, the issue of the digital feasible NSDI model of Ukraine in the next five years, which would take into account the actual model, is especially acute. In addition to feasibility, such a model must also be "correct", what is proposed in the article. The correct is called a model, the truth of which can be established by inductive or deductive reasoning. To do this, the correct model must be formalized enough so that everyone can verify the authors’ reasoning independently. Understanding both actual and correct models of NSDI of Ukraine will help to properly organize and develop actual Spatial Infrastructure Activities (SpIA) in Ukraine, including the real[1] implementation of the [1]. Although the results of the article call into question its feasibility and substantiate an alternative viewpoint on the automation problem of NGDI/NSDI/SpIA. However, we are convinced that it is still possible to change the alternative viewpoint to a cooperative one, if by means of by-laws the models of NGDI (Law), NSDI (article) and, finally, SpIA are agreed upon To prove the "correctness" of the feasible NSDI model, the theory of Relational cartography and its two main methods are used: Conceptual Frameworks and Solution Frameworks. In addition, the correspondence between Relational cartography and Model-Based Engineering is used. Key words: NSDI; product model; process model; actual, feasible and «correct» model. [1] Real. 1. Which exists in reality, true. Is used with: reality, life, existence, conditions, circumstances, fact, danger, force, wages, income. 2. One that can be implemented, executed: a real plan, a real program, a real task, a real deadline. 3. Which is based on taking into account and assessing the real conditions of reality: a real approach, a real view, a real policy.- accessed 2021-feb-14, http://slovopedia.org.ua/32/53408/32016.html (Ukrainian)

The stock-flow model of spatial data infrastructure development refined by fuzzy logic

The system dynamics technique has been demonstrated to be a proper method by which to model and simulate the development of spatial data infrastructures (SDI). An SDI is a collaborative effort to manage and share spatial data at different political and administrative levels. It is comprised of various dynamically interacting quantitative and qualitative (linguistic) variables. To incorporate linguistic variables and their joint effects in an SDI-development model more effectively, we suggest employing fuzzy logic. Not all fuzzy models are able to model the dynamic behavior of SDIs properly. Therefore, this paper aims to investigate different fuzzy models and their suitability for modeling SDIs. To that end, two inference and two defuzzification methods were used for the fuzzification of the joint effect of two variables in an existing SDI model. The results show that the Average–Average inference and Center of Area defuzzification can better model the dynamics of SDI development

The Evolution of National Spatial Data Infrastructure in Pakistan - Implementation Challenges and the Way Forward

Geospatial data are produced by several organizations located at various places, and that is clearly a distributed environment. Many technical and institutional issues need to be resolved to share data in such an environment and to eventually enable regional development. For this matter, many countries implement Spatial Data Infrastructures (SDIs) for the last 40 years. Since 2010, also Pakistan is striving to implement an SDI at the national level (NSDI). However, so far, the promised benefits have not yet been achieved. This study explores the evolution of the NSDI in Pakistan from 2010 till 2020 to reveal what kind of challenges the country is facing. Given the importance of stakeholders' support for the implementation of SDIs, we conducted a stakeholder analysis and a dedicated survey. We adopted the power-interest grid method to classify stakeholders' interests based on their authority to influence the NSDI development. Among other, the results show that stakeholders’ low participation due to insufficient technological, financial, and human resources impedes NSDI implementation efforts in the country

Evaluating a public sector organisation for SDI readiness – the case of a South African government department

Spatial data infrastructure (SDI) facilitates the collection and sharing of geographic information developed by different organisations. As a result, SDI initiatives are occurring in different countries. Various government departments are implementing SDI in order to contribute to the achievements of its objectives. SDI assessments to evaluate the implementation thereof is also occurring from local levels to international levels. This paper establishes the availability of geographic information within the Department of Environmental Affairs (DEA) by describing DEA’s contribution to the South African SDI objectives and by assessing DEA’s SDI readiness.The qualitative method was used to collect data. The techniques used in this research were literature review, interviews, mainly in-depth interview, document and internet analysis. The results indicate that geographic information is available and the department continues to make more means to make it available. They also reveal that there are some challenges with respect to accessibility. Currently there is a process to make it even more easily accessible. The results show DEA’s willingness and capacity to contribute to the South African SDI. The voluntary participation in SDI activities and the ability to obtain additional funding for geographic information is a clear indicator of DEA’s willingness to contribute to SASDI’s objectives. The results contribute to the body of knowledge that if an SDI is still in the early stages of development, it is challenging to make conclusions on some of the key SDI assessment indices. Future research is required once South African SDI has reached mature stages.http://www.sajg.org.za/index.php/sajgam2017Geography, Geoinformatics and Meteorolog

Evaluating the performance of large scale SDIs: two contrasting approaches

In the last couple of years there have been two very different attempts to evaluate the performance of large scale spatial data infrastructures (SDIs). The first of these was in the United States of America where the Coalition of Geospatial Organizations (COGO), a consortium of professional organisations, set up an expert panel to produce a report card of the performance of the US NSDI. The second evaluation was in the European Union where the European Commission carried out its own evaluation of its Infrastructure for Spatial Information in Europe (INSPIRE) Directive to meet the requirements of the European Commission.   The main features of these two contrasting approaches to evaluation are described in the opening sections of this paper while the final section considers the similarities and differences between the two outcomes of the two exercises. The outcomes of this investigation provide some interesting insights into the issues involved in the implementation of large scale SDIs.