A Review of Pakistan’s National Spatial Data Infrastructure Using Multiple Assessment Frameworks

Abstract

Efforts to establish Pakistan’s National Spatial Data Infrastructure (NSDI) have been underway for the past 15 years, and therefore it is necessary to gauge the current progress to channelize efforts into areas that need improvement. This article assessed Pakistan’s NSDI implementation efforts through well-established approaches, including the SDI readiness model, organizational aspects, and state of play. The data were collected from Spatial Data Infrastructure (SDI) and Geographic Information System (GIS) experts. The findings underscored challenges related to human resources, SDI education/culture, long-term vision, lack of awareness of geoinformation (GI), sustainable funding, metadata availability, online geospatial services, and geospatial standards hindering NSDI development in Pakistan. However, certain factors exhibit favorable standings, such as the legal framework for NSDI establishment, web connectivity, geospatial software availability, the unavailability of core spatial datasets, and institutional leadership. Thus, to enhance the development of NSDI in Pakistan, recommendations include bolstering financial and human resources, improving online geospatial presence, and fostering a long-term vision for NSDI.

1. Introduction

Spatial data are a vital input for national planning and development [1]. Consequently, there is great demand for numerous advanced tools to extract and utilize such data effectively. Spatial Data Infrastructure (SDI) supports data sharing and the organization of different sources into a system. That is why, in many countries, to manage spatial data better, NSDIs have been envisioned [2]. Moreover, the UN Sustainable Development Goals (SDGs) Agenda 2030 prompts countries to create and utilize spatial data to advance Sustainable Development (SD), which also requires access to standardized spatial data. This is one of the core functions of SDI. SDI permits the immediate sharing of spatial data, which is instrumental for development and resource management.

To face the challenges of world dynamism, the effort to promote the development of a National Spatial Data Infrastructure in Pakistan has been initiated. Numerous seminars, training, and meetings have been organized on spatial data sharing, spatial data integration, and spatial planning [3,4]. Pakistan’s government mandated a Survey of Pakistan to establish a National Spatial Data Infrastructure (NSDI) for the country in 2014 to support cooperation among different government agencies [5,6].

Implementing SDIs requires institutional frameworks, policies, and technologies to facilitate the accessibility and availability of spatial data and information [7]. The process can be viewed as a joint way of bringing spatial data closer to the public, resulting in broader distribution, and optimizing the use of funds for overall benefit [8]. Although some countries are using SDIs to formulate policies, share geospatial data resources, and tackle some issues related to data access and use, there have been varying degrees of success in these areas. In developed countries, there have been instances of success, whereas underdeveloped nations have encountered significant challenges.

When data created by governments and private companies in developing countries are unstructured, the use of these data for the improvement of land use and economic development is restricted due to interoperability and data standardization issues [9]. For example, Tanzania’s development efforts are hindered by the fact that there is poor management of spatial data in the country, making it difficult for people to obtain, share, and use valuable spatial data. The absence of synergy among organizations significantly affects data collection, as well as the sharing of information [10]. Similarly, Efendyan and Petrosyan [11] researched the legal documentation associated with spatial data legislation and revealed a plethora of incompatibilities and challenges in implementing an NSDI and formulating strong policies in Armenia. Izdebski and Zwirowicz [12] examined the open data of the Polish Spatial Data Infrastructure (PSDI) to create technical tools and engage more stakeholders to participate in the decision-making process. Vaitis et al. [13] presented a developmental outline of a Marine SDI to contribute to Marine Spatial Planning in Greece. Castro and Rifai [14] outlined an NSDI to guide decision-making for NBS projects involving the integration of social, ecological, environmental, and hydrological data, as well as health outcomes, into flood risk assessments.

Currently (2022–2024), a feasibility study is being conducted which is aimed at establishing an NSDI in Pakistan [15,16]. The main objective of this feasibility study is to define and distinguish financial, legal, technical, and human factors to support project implementation. Also, the feasibility study investigates governance, management, financial, and business models, and the establishment of the NSDI secretariat. The research on the purpose of the feasibility study is based on data collected from various sources, such as workshops, social media sites, and meetings, to obtain a high-level overview of the analysis. Furthermore, COMSATS University Islamabad hosted a workshop that included all aspects of Pakistan’s National Spatial Data Infrastructure, as endorsed by Ahmad et al. [15]. On the other hand, we foresee that the adoption of the NSDI will not only improve cadastral systems but will straightforwardly provide other benefits. This holds special importance specifically in agricultural policymaking, which was brought to light by [17,18].

In addition to ongoing initiatives, Pakistan continues to grapple with challenges in providing a supportive environment for users to access spatial datasets. There is an urgent need to systematically address this issue and evaluate the readiness of Pakistan’s NSDI to identify focal points for development and facilitate the NSDI’s progress in the nation. Giff and Jackson [19] contend that the SDI readiness model is particularly applicable in the nascent stages of NSDI development, such as the case of Pakistan’s NSDI. Within the framework of the multi-view assessment approach [20,21], the SDI readiness model proves to be an effective technique.

To date, no comprehensive study has been commissioned to assess the status of Pakistan’s NSDI systematically. Therefore, the research questions for this study are as follows:

• What is the current status of the key indicators of SDI readiness in Pakistan, and how do these indicators compare with those of other countries?
• What is the status and progress of the SDI in Pakistan when assessed using an organizational framework or approach?
• What are the key strengths and weaknesses of the SDI in Pakistan when evaluated using the state-of-play approach?

2. Literature Review

SDI support the connectivity of key spatial databases in regions, provinces, states, and countries, acting as a pipeline that serves to connect them [22]. As McLaughlin and Nichols [23] stated, being interconnected is the core idea of creating an NSDI, as it provides easy access to data sources and useful services to different private sectors, government sectors, and the general public.

Spatial Data Infrastructure is a multifaceted, complicated, and dynamic concept. The assessment of SDI using a linear approach may not produce quality results. Therefore, a multi-view framework that combines many approaches may be an appropriate method to assess NSDIs. The SDI readiness model was selected because it is best suited to situations where NSDI development is in its early stages [19], as NSDI development in Pakistan is in its initial stages. State of play and organizational approaches were selected to explore the in-depth status of the NSDI in Pakistan. The proceeding sections underscore a brief overview of each approach.

2.1. SDI Readiness Approach

The SDI readiness index developed by Delgado Fernández [24] permits an integrated evaluation of countries’ capacities and strengths in implementing SDIs. By employing the SDI readiness model, policymakers can delve into critical aspects of SDI assessments, aiding in the formulation of effective policies for national SDI development, implementation, maintenance, and enhancement. Delgado Fernández [24] argued that the SDI readiness model facilitates the identification of SDIs’ primary strengths and weaknesses, enabling a comparative analysis of SDI readiness indices across countries or initiatives.

The SDI readiness index encompasses 16 factors grouped into five indices: technological, organizational, informational, financial, and human resources (

Table 1. Factors and indicators of the SDI readiness model adapted from [25].

Factors	Indicators
Organizational Infrastructure	Politicians’ visions of SDI (Ov)
	Institutional leadership (Ol)
	Legal framework (Of)
Information Infrastructure	Availability of core spatial datasets (Ic)
	Availability of metadata (Im)
Human Resources	Human capital (Pc)
	Culture/education regarding SDI (Ps)
	Individual leadership (Pl)
Technology Infrastructure	Web connectivity (Aw)
	Telecommunication infrastructure (At)
	Indigenous development of geospatial software (Ad)
	Availability of commercial geospatial software (As)
	Culture regarding the use of open-source GI software (Ao)
Financial Resources	Government-level funding (Fg)
	Mechanism of cost recovery (Fr)
	Funding from private sector (Fp)

). The organizational index comprises three key factors: political dedication to the SDI vision, institutional leadership for the SDI, and the establishment of legal frameworks. Political commitment is pivotal for recognizing NSDI’s role in evidence-based policymaking and project oversight. Institutional leadership entails collaboration among national-level SDI-related bodies, while the legal framework factor concentrates on setting up pertinent legal instruments at the national level.

The informational index comprises metadata availability for geospatial data and core geospatial dataset availability. The human resources index includes human capital, SDI-related education, culture, and individual leadership. The education/culture aspect pertains to capacity building and awareness campaigns regarding geospatial data utilization. Individual leadership denotes the capability to implement SDI-related agendas.

The financial resources index encompasses public sector and private sector funding, as well as cost recovery models. Adequate funding is indispensable for SDI initiative development. Funds can be earmarked for capacity building, data collection, and metadata preparation, as well as management responsibilities. The technological index is made up of data access networks and technologies that deliver data-sharing and digital services. As part of these services, telecommunication infrastructure, internet connectivity, indigenous/commercial geospatial software, and open resources are established.

Further details regarding indicators and factors are provided in Table 1.

2.2. Organizational Approach

Kok and Van [26] presented an organizational framework for evaluating the status of NSDIs. This framework, as outlined by Grus [21], assesses an SDI’s status and progress using six organization-specific parameters: vision, leadership, communication, self-organization ability, awareness, and financial suitability. These parameters are further broken down into 12 sub-indicators, as depicted in

Table 2. Indicators and sub-indicators adopted from [21].

Indicators	Sub-Indicators
Leadership	Does the government of Pakistan establish leadership for Pakistan’s NSDI? Is Pakistan’s NSDI is formally supported by relevant laws, acts, or regulations?
Inclusiveness and Communication Channels	Are participants actively participating in the process of establishing SDI at the national or local level? Does a commitment platform exist to support and facilitate the journey of establishing Pakistan’s NSDI?
Long-Term Vision	Presence of a strategic plan to establish NSDI that is acceptable to all stakeholders? Are private sector organizations aligned with the development plan for Pakistan’s NSDI? Are most organizations aligned with the strategic plan for Pakistan’s NSDI?
Self-Organizing Ability	SDIs address problems in society that may require the availability of relevant geospatial data. Does Pakistan’s NSDI do the same? Do the capacity building and awareness campaigns of Pakistan’s NSDI influence societal dynamics?
GI Awareness	Has Pakistan’s NSDI initiative launched an awareness campaign to raise awareness among citizens of the importance of NSDI? Does Pakistan’s NSDI initiative have an awareness campaign dedicated to the private sector and academia?
Sustainable Funding	Does Pakistan’s NSDI initiative have sustainable funding?

, detailing both the main indicators and their corresponding sub-indicators within the organizational approach.

2.3. Modified State of Play

The state-of-play approach, initially tailored for monitoring and analyzing NSDI-related endeavors primarily within European nations [27], encompasses various parameters for assessing SDI. These parameters include organization, personnel, policy framework, data and metadata management, access services for data/metadata, adherence to relevant standards, and thematic environmental data integration. While initially conceived for European contexts, studies indicate its applicability beyond Europe [28,29,30].

Grus et al. [20] implemented the state-of-play approach by gathering data from country reports, websites, and expert interviews. A modified version, derived from the INSPIRE state-of-play approach within a multi-view assessment framework, includes 26 indicators, categorized according to the SDI components of personnel, policy, data management, technology, and standards, as delineated in

Table 3. Indicators and sub-indicators of the state-of-play approach adopted from [21].

Indicators	Sub-Indicators
People	SDI initiatives being executed in the country are truly national. One or more components of the SDI architecture have gained a certain level of maturity at the operational level. The national-level GI association is part of the process of coordination for the establishment of the NSDI initiative. Only public sector organizations are engaged in NSDI development. Enough qualified manpower is available to implement SDI initiatives in the country. Involvement of spatial data producers and users in the process of the establishment of the NSDI.
Policy	True public–private partnerships are available to support and facilitate the initialization, development, and commissioning of NSDI-related projects. There is a “Right of Access to Information Act” which covers legislation about the protection of Geo-Information. Privacy laws are actively put in place by stakeholders in the NSDI. There is a pricing policy that exists for GI trading. Existence of relevant frameworks, guidelines, acts, laws, rules, or policies for spatial data sharing.
Data	All applicable geodetic reference systems and projection systems are standardized, organized, documented, and interoperable. Spatial datasets are available for most of the domain areas. Metadata of reference data and core thematic data are produced at a significant level. Data quality control procedures and guidelines applicable to NSDI are available in organized and documented form.
Technology	Online access services for metadata are available for one or more organizations. Online service to download core spatial datasets is available at the national level. An online web mapping service is available for the core spatial set at the national level. One or more standardized metadata catalogues are available for one or more organizations.
Standards	All SDI initiatives pay special attention to issues regarding standards. The process of data collection is properly standardized for all data collection drives.

.

In the year 2005, the readiness index was introduced in Cuba to assess SDI readiness and identify deficiencies. The year 2005 was chosen because a geographic data portal at the national level was set up in the same year to identify the spatiotemporal data distribution of users [24]. The authors explained the different SDI readiness model dimensions, its reasons for existence, and its development process, among many other elements. They applied the SDI readiness model to 27 countries worldwide: Argentina, Barbados, Brazil, Canada, Chile, Colombia, Cuba, Denmark, Dominica, Dominican Republic, Ecuador, Grenada, Guyana, Jamaica, Malaysia, Mexico, the Netherlands, Nepal, Norway, Poland, Serbia, St. Lucia, St. Vincent, Spain, Trinidad and Tobago, Turkey, and Uruguay. They concluded that these countries encountered numerous developmental challenges with SDI, providing a deeper insight into the main stakeholders of SDI programs globally.

Fernández and Crompvoets [31] explored the development of SDI in the Caribbean from different angles, such as the SDI readiness model, state of play as envisioned by Vandenbroucke et al. [32], and the clearinghouse suitability index, as introduced by Crompvoets [33]. From the SDI readiness index findings, we note that the development of Spatial Data Infrastructure in the Caribbean is at a very early stage. Even though there is significant variation in SDI progress among the islands due to the reasons of low financial resources or the area, some of the islands have already undergone the process and benefited a lot. Just like the above-mentioned approach, Nushi et al. [27] applied the SDI readiness model, INSPIRE state of play, and a maturity matrix [26] to investigate the SDI situation in Kosovo. In Kosovo, the SDI readiness model was applied in two specific periods (2007 and 2010), and an independent panel composed of ten SDI experts was asked about different factors. This analysis led to an SDI readiness index score of 0.26 in 2007 and 0.36 in 2010, indicating a slight improvement. Furthermore, organizational aspects were emphasized to enhance the success of SDI implementation in Kosovo.

Ethiopia’s NSDI was assessed by Gemeda [29], using a multifaceted evaluation framework comprising the SDI readiness scale, the state-of-play approach, the clearinghouse suitability index, and organizational factors. The assessment revealed that the overall readiness of the Ethiopian NSDI was 39%, with only the information and organizational components scoring above average. Similarly, Pinsonnault [34] scrutinized the adequacy of the NSDI of Peru. The reviewed results showed that a readiness score of 51% was registered for Peru’s NSDI. The study also magnified the problems surrounding the functioning of Peru’s NSDI. For example, there were problems pertaining to legal agreements, the availability of metadata, SDI culture, willingness to share spatial datasets, financial support from the central government, and communication infrastructure. Furthermore, the assessment of geographic information delivery gained a medium score.

Okuku and Grus [28] subjected Kenya’s NSDI to a multi-view evaluation in a study that followed the SDI readiness model, analyzing modified state of play and organizational aspects. Public and private sectors, academia, NGOs, and international entities, as well as civil society organizations were involved in the research. The analysis of the results showed that Kenya’s NSDI had a preparedness score of 39%; spatial data were not available due to problems with information and communication infrastructure, web connectivity, and human resources shortages. An inadequate sharing of digital data, a lack of financial support over a long period, a lack of professionals with geospatial skills, problems with technology advancement, minimal public awareness, no availability of data metadata, and poor network access are the weaknesses noted for Kenya’s NSDI.

Mwange et al. [35] investigated the presence or absence of NSDI in 12 African countries through the SDI readiness index, considering 15 variables. Tanzania, Zimbabwe, Botswana, and Malawi received low scores, while Senegal, Rwanda, South Africa, and Ghana received high scores. A review of the NSDI development process in African countries revealed some of the areas that need development, such as the quality and quantity of human resources and financial resource constraints. Kalantari [36] investigated the current nationwide status of SDI development in Iran. They based their study on a review of the literature and local surveys, as well as an SDI readiness model comprising 16 variables. The results showed that Iran’s NSDI readiness level was 44%. Comparing the readiness index of Iranian SDI with that of other countries revealed that the Iranian SDI readiness indicators were below average, considering the country’s under-developed organizational, human resource, and information factors. According to the research findings, infrastructure development in relation to macro-policies, legislation, culture, HR, and institutions is needed to support Iran’s NSDI development.

Ogunbiyi [30] completed a status analysis and an ongoing development analysis of NSDIs in several selected countries, namely, “Botswana, South Africa, Malawi, Zimbabwe, and Tanzania”. The evaluation method utilized two multi-view frameworks, namely the organizational evaluation method and the enhanced state-of-play technique. The investigation of synergies showed that the exchange and integration of data among various stakeholders and departments are obstacles to carving out NSDI in the Republic of Africa. The analysis of spatial data infrastructure indicated that there were areas that were underdeveloped in the chosen countries, including technical infrastructure, regulatory frameworks, strategic policy impacts, national security considerations, and privacy concerns. Technical options for enabling interoperability and data transactions across digital channels in southern African nations have not yet matured and are at an initial stage, and human and policy-related activities are still in the early stages. The study showed that, often, governmental agencies’ prioritization of their mandates in developing countries may discourage collective efforts to share and distribute spatial infrastructures.

Rahman and Szabó [37] assessed Bangladesh’s NSDI using 14 key variables developed by Eelderink and Crompvoets [38], and reported challenges like limited funding, data-sharing reluctance, and a lack of human capital. The authors also noted that, despite these challenges, Bangladesh has made progress through investments in data availability, institutional leadership by the Survey of Bangladesh, and initiatives to raise awareness.

3. Materials and Methods

The methodology used in this article is based on multi-view assessment approaches (SDI readiness index, organizational aspects, and state-of-play), as envisaged by Delgado Fernández [25].

3.1. SDI Readiness Approach

Sixteen SDI readiness index factors are grouped into five indices: technological, organizational, informational, financial, and human resources. Out of the 16 indicators, 03 (human capital, telecommunication infrastructure, and web connectivity) are extracted from the UN E-Government Survey (2022).

The remaining 13 indicators were established through surveys with SDI and GIS experts. The expert surveys were conducted via a questionnaire with 13 questions. Each question provided seven response options: “extremely high, very high, high, medium, low, very low, and extremely low”. To assess each indicator, a weight was assigned to each option.

Table 4. Weights for the indicators.

Options	Weights
Extremely high	0.99
Very high	0.80
High	0.65
Medium	0.50
Low	0.35
Very low	0.20
Extremely low	0.01

shows the weights assigned to each option.

The fuzzy-based model introduces the notion that weights can range from 0.01 to 0.99, as indicated in Table 4. Typically, the initial and the last choices (extremely high and extremely low) are given rather big weights [36].

Survey data were collected in 2023 from 20 experts. Following the survey, we utilized a formula recommended by Delgado Fernández for data analysis [25]. This involved assigning weights to respondents’ answers according to the measures outlined in Table 2. Subsequently, calculations were conducted for various SDI readiness factors and indices to gain insights into Pakistan’s SDI preparedness. The data calculation process involved several steps:

• Each survey/interview response was assigned a weight based on the measures specified in Table 4.
• Values for different SDI readiness factors—such as information infrastructure, technology infrastructure, financial resources, organizational infrastructure, and human resources—were estimated using formulas from the SDI readiness model. The calculated values for these factors represent the geometric mean of scores derived from each factor’s specific formula. For instance, the information factor’s value was estimated using the formula (I_c ∗ I I_m)^(1/2), where I_c and I_m denote criteria scores relating to core spatial dataset availability and metadata availability, respectively.
• For each answer, the overall SDI readiness index was calculated by computing the geometric mean of the factors.
• Finally, the overall score of Pakistan’s NSDI was the geometrical mean of the indices obtained from the responses to each question. To make the calculation easy, fast, and accurate, all the steps involved were executed using the built-in functions of Microsoft Excel.

In the readiness model, the overall score is calculated based on the formula presented by the authors in [24].

SDI readiness = (O_v ^ O_l ^ O_a) ^ (I_c ^ I_m) ^ (P_c ^ P_c ^ P_l) ^ (F_g v F_p v F_r) ^ (A_t ^ A_w ^ (A_s v A_d v A_o))^0.5

(1)

where compensatory logic is applied, the conjunction is solved by

c(x₁, x₂, …, x_n) = (x₂, …, x_n)^(1/n)

(2)

and the disjunction by

d(x₁, x₂, …, x_n) = 1 − ((1 − x₂) ∗ (1 − x₂) … (1 − x_n))^(1/n)

(3)

Finally, the following expression calculates the SDI readiness score:

SDI readiness = (O_v ∗ O_l ∗ O_a)^(1/3) ∗ (I_c ∗ I_m)^(1/2) ∗ (P_c ∗ P_s ∗ P_l)^(1/3) ∗ (1 − ((1 − F_g) ∗ (1 − F_p) ∗ (1 − F_r)^(1/3)
∗ ((A_t ∗ A_w ∗ (1 − ((1 − A_s) ∗ (1 − A_d) ∗ (1 − A_o)) ^(1/3)))^(1/3))^(1/2)

(4)

3.2. Organizational Approach

This approach involves the assessment of 12 sub-indicators grouped into 06 main indicators. The same experts who were involved in the assessment of the readiness index were employed to assess the sub-indicators and indicators involved in the organization approach. Each sub-indicator was evaluated on a binary scale of yes or no. The main indicators were evaluated based on the ratings of the sub-indicators.

3.3. Modified State of Play

The state-of-play approach parameters include organization, personnel, policy framework, data and metadata management, access services for data/metadata, adherence to relevant standards, and thematic environmental data integration. The 26 sub-indicators are grouped into 05 main indicators. The same experts were also asked to answer 26 questions, each corresponding to a sub-indicator. Each question was assessed using four options (fully agree, partially agree, do not agree, and no information available). The main indicators are evaluated based on the ratings of the sub-indicators.

3.4. Sampling Strategy and Respondent Details

The sampling strategy was designed to capture a diverse range of perspectives. Participants who had direct experience and expertise in GIS and SDI were considered. This included individuals from various sectors such as the government, non-governmental organizations, private sector entities, and academia. Qualifications for expert selection included operational and managerial-level experience and expertise in SDI- and GIS-related fields, along with a willingness to engage in the survey. Twenty experts were selected to conduct the questionnaire-based survey. These experts were intentionally selected from diverse backgrounds, including public and private sectors, as well as academia. The expert selection proved challenging because NSDI in Pakistan is still in its infancy, and a limited number of professionals have knowledge of SDI-related concepts. As we selected respondents from various sectors, such as the government, non-governmental organizations, private sector entities, and academia, the chances of bias in the data collection were minimized.

4. Results

The subsequent sections describe the outcomes of the analysis based on different approaches for the assessment of Pakistan’s NSDI.

4.1. SDI Readiness Approach

The SDI readiness approach employs a readiness model utilizing five indices. The results for each index, as well as the overall index, are presented below.

4.1.1. Organization Index

The organization matrix consists of indicators like politicians’ knowledge about SDI, institutional guidance, and legal systems. In this research, the total value of the organizational factor index for Pakistan’s SDI was measured as 0.37. Politicians’ visions of SDI, leadership in institutions, and legal aspects were scored at 0.21, 0.58, and 0.42, respectively. These data suggest that vision from institutional leadership has the highest impact, while vision from politicians reported the lowest score.

4.1.2. Information Index

The information base (the information index) includes indicators such as metadata availability; in addition, spatial datasets with regard to administrative boundaries, elevation, local names, cadastral parcels, transportation, aerial photography, and satellite images are also part of this. These principles were the pre-conditions of the information factor index for the SDI of Pakistan, which received a score of 0.36. The spatial data and metadata indicators were rated at 0.56 and 0.23, respectively. These results indicate a low overall score for the information index, as both components have values below 0.5.

4.1.3. Human Resources Index

The human resources index is anchored by the human capital index, education relating to SDI, and leadership at an individual level. The factor index score for the human resources factor for the case study of SDI in Pakistan is 0.25. The chosen indicators of human capital index, SDI education, and the best practices of individual leadership scored 0.39, 0.32, and 0.13, respectively. These results reflect a low score of less than 0.5 across all indicators.

4.1.4. Technology Index

Technology infrastructure is one of the most significant aspects in making geospatial data and services in SDI architecture reachable and available. The technology infrastructure index comprises five indicators: telecommunication infrastructure, the technology of the web, the availability of commercial geospatial software, the technology created by indigenous informational development, and the culture of open-source technologies in SDI. In this study, we estimated the technological infrastructure index of the SDI in Pakistan at 0.66. The result obtained showed that the leading index was web connectivity, and the trailing one was the availability of geospatial software.

4.1.5. Financial Index

The indicator of financial resources being strong is very important for SDI progress in every country. The financial resources index includes elements like shared funding schemes, grant-making from the private sector, and cost-recovery measures. These indicators form the basis for calculating the financial resources factor index for Pakistan’s SDI, which is scored at 0.16. The scores for public sector funding, pricing acts, and private sector funding were 0.20, 0.15, and 0.11, respectively.

4.1.6. Overall Index

The SDI readiness model developed by Delgado Fernández [25] suggests that a country is nationally ready to adopt SDI when it scores well in various parameters, including but not limited to levels of organization, information, human resources, financial resources, and technology. The aggregate index of all indices to reveal Pakistan’s SDI readiness was computed to be 0.32, which shows that Pakistan has a lot to undertake to succeed in the process of establishing an NSDI. Figure 1 depicts the overall Pakistan SDI readiness score, rated along with the scores of separate indices.

As depicted in Figure 1, the scores for the information and organization factors were similar to the overall readiness index score. Among the factors, technology had the highest score, while financial resources had the lowest. Figure 2, Figure 3, Figure 4, Figure 5 and Figure 6 provide a detailed breakdown of the scores for the five indices.

Based on the 16 indicators in Figure 2, Figure 3, Figure 4, Figure 5 and Figure 6, the results show that the private sector funding and web connectivity scores were the lowest and the highest, respectively. Additionally, it is evident from the indicator rankings that 12 out of 16 indicators scored less than 50%, compared to the 100% benchmark for full readiness.

4.2. Organizational Approach

The organizational approach involved 6 indicators and 12 sub-indicators to assess various aspects. For the leadership indicator, both sub-indicators received agreement from the majority of respondents (90%). For inclusiveness and communication channels, the majority of respondents disagreed (75%), with one sub-indicator showing more agreement than the other regarding the existence of a commitment platform for Pakistan’s NSDI. The long-term vision indicator showed the highest disagreement (92% of respondents) across all three sub-indicators. In terms of self-organizing ability, while 60% of respondents agreed overall, one sub-indicator had 20% more agreement than the other. Regarding GI awareness, 70% of respondents expressed disagreement, with one sub-indicator showing 20% more disagreement than the other. The sustainable funding indicator had only one sub-indicator, with the majority (90%) of respondents showing disagreement. Figure 7 presents the cumulative results of the indicators for the organizational approach.

4.3. State-of-Play Approach

The state-of-play approach employed 5 indicators with 26 sub-indicators for assessment. The people indicator included six sub-indicators. While 19% fully agreed and 28% partially agreed with the statements, 33% were unaware of information availability. For the policy indicator, more than 50% stated information unavailability. Particularly, 90% were unaware of the existence of a data-sharing policy framework or strategy. No one fully agreed to four sub-indicators, while 15% fully agreed to one; 30% disagreed and 13% partially agreed with the statements for this indicator. The data indicator comprised four sub-indicators; 36% disagreed, 24% partially agreed, and 11% fully agreed with the statements. One sub-indicator showed 30% more disagreement than the others.

For the technology indicator, the majority (91%) disagreed with the statements, with two sub-indicators showing 100% disagreement. No respondents fully or partially agreed. The standards indicator consisted of two sub-indicators, with 70% expressing disagreement with the statements. Figure 8 presents the results of the indicators and sub-indicators.

5. Discussion

This research presents the first-ever systematic assessment of Pakistan’s NSDI development status using multi-view assessment approaches, including the SDI readiness model, organization aspects, and state-of-play.

5.1. SDI Readiness Approach

SDI readiness encompasses five factors: organizational infrastructure, information infrastructure, technology infrastructure, human resources, and financial resources.

Organizational infrastructure received a low score (0.37) primarily due to subpar performance in its key indicators, including politicians’ visions of SDI. To elevate this factor’s score, it is imperative to enhance politicians’ understanding of and commitment to NSDI, making it a top priority for development. Additionally, improving the legal framework is crucial, alongside robust SDI awareness campaigns targeting higher-level politicians and governmental bodies. In short, the low scores of these organizational indicators can pose a significant obstacle to the effective implementation of NSDI in Pakistan.

The information infrastructure factor scored poorly primarily due to the limited availability of metadata indicators. However, the availability of core spatial dataset indicators performed better, scoring 0.58. This higher score reflects the availability of numerous geospatial datasets that can be shared with users via web connectivity. Nonetheless, data sharing may be constrained by low scores in various indicators, including metadata availability, the absence of a geoportal for online services, the lack of data-sharing policies, and insufficient indigenous geospatial software development. The low score for metadata availability indicates an inadequate preparation of metadata requirements within Pakistan’s SDI development context. To enhance information factors, Pakistan should increase awareness about the importance of spatial data and metadata for national-level planning and development. By standardizing metadata practices, building local capacity, developing user-friendly tools, and incentivizing metadata creation, spatial data management capabilities can be enhanced. A robust SDI with high-quality metadata can drive sustainable development, inform decision-making and efficient resource management, and ultimately contribute to economic growth and improved quality of life. Additionally, fostering collaboration between public and private sector organizations and enhancing policy, legal, and organizational frameworks are crucial steps that can be taken for the successful implementation of NSDI in Pakistan.

The human resources factor also exhibited lower scores, primarily due to the inadequate performance of indicators such as culture/education regarding SDI and individual leadership. The human capital indicator scored relatively higher, likely influenced by investments to increase adult literacy rates and gross enrollment ratios; it remains notably higher than the other two indicators. The low score for culture and education regarding SDI underscores the insufficient investment in societal capacity building concerning spatial data’s significance and its societal impact. Moreover, the low score for individual leadership highlights leaders’ weak capacity to collaborate across organizational boundaries. To address these challenges, stimulating activities should be employed to foster a collaborative culture and motivate individuals toward common goals. Hence, investing in enhancing this factor is imperative to bolster NSDI development in Pakistan.

The financial resources factor attained the lowest score among all five factors. This is primarily attributed to the low values of all three indicators: governmental funding, private sector funding, and cost recovery. Particularly, the private sector funding indicator scored lower than the other two indicators in this factor. This can be attributed to the inadequate investment opportunities available for the private sector. In short, the limited financial resources allocated to Pakistan’s SDI development hinder the progress of SDI development in the country.

The technology infrastructure factor exhibited a relatively high score compared to the other factors within the SDI readiness model. This heightened score can be primarily attributed to the strong performance of two indicators: web connectivity and the availability of geospatial software. However, other indicators such as telecommunication infrastructure, native development of geospatial software, and the utilization of open-sourced resources obtained relatively low scores. The robust score of the web connectivity indicator indicates the extensive use of information and communication technologies (ICTs), as well as a prevalent culture of mobile and web applications for service delivery. Similarly, the high score for the availability of geospatial software suggests advancements in developing and implementing effective policies and guidelines to leverage GIS technologies effectively in the country. This also signifies a growing trend in the utilization of location-based services by various stakeholders, including public and private sector organizations as well as academia. Conversely, limited awareness campaigns promoting the use of open data resources, a lack of easy access to proprietary software solutions at minimal costs, and an inadequate awareness of relevant copyright laws contributed to the low score in the indicator related to the culture of using open-source resources.

Four out of five factors within the SDI readiness model, namely organizational infrastructure, financial resources, human resources, and information infrastructure, fall short of the required standards for NSDI development in the country. Hence, it is imperative to undertake appropriate actions to enhance the status of these factors, as improvement in these areas is crucial for the successful implementation of NSDI in Pakistan. This observation is supported by findings from studies conducted by [36,39,40,41].

5.2. Organizational Approach

The organizational approach encompassed six indicators: leadership, inclusiveness and communication channels, long-term vision, self-organizing ability, GI awareness, and sustainable funding. In terms of leadership establishment for NSDI, 90% of respondents agreed, likely influenced by the legal mandate outlined in the Surveying and Mapping Act of 2014 by the government of Pakistan [42]. However, concerning the existence of a long-term vision for NSDI, 92% disagreed. This discrepancy stems from the lack of progress despite the enactment of relevant legislation in 2014; NSDI has not been prioritized by the government of Pakistan. Overall, the organizational aspects analyzed indicate relatively high levels of leadership and self-organizing ability, but a lack of long-term vision and sustainable funding.

5.3. State-of-Play Approach

The modified state-of-play approach assessed five indicators: people, policy, data, technology, and standards. In terms of standards and technology indicators, most respondents expressed disagreements. This is primarily attributed to the absence of a geoportal in the country, which hampers online data downloads and access to services. Additionally, there is a lack of comprehensive guidelines regarding standard implementation. More than 50% of respondents were unaware of any policy documents, indicating that no coordinating body exists in the country. Overall, the state-of-play approach indicated relatively high scores for people and data, while technology and standards exhibited lower scores.

5.4. Comparative Analysis of Recent SDI Practices

This section provides an analytical study of the emerging SDI implementations in EU countries and compares these practices with the situation in Pakistan.

5.4.1. Analysis of SDI Practices in EU Countries

In EU countries that have implemented SDIs, changes have been experienced as a result of the development of technologies, policies, and cooperation between state members. Key aspects of these practices include the following:

• EU countries have established various policy measures for SDI support, including the INSPIRE Directive, through which member states are directed on the harmonization of spatial data in Europe. Close cooperation among stakeholders is possible due to proper governance in terms of government, private businesses, and academic institutions [43].
• The EU has spent a lot of money to foster the establishment of sophisticated geospatial technologies and networks. This includes the integration of systems and data formats that can be exchanged between various systems. It has also increased the availability of spatial data due to the focus on open data policies and other similar concepts [44].
• Another important component of SDI practices in the EU is the focus on cooperation, both internally and inter-state [45]. Generally, collaborations at a regional level have enhanced the exchange of data and information, with a positive effect on SDIs.

5.4.2. Conditions in Pakistan

In contrast to the EU, Pakistan faces several challenges and constraints in developing and implementing effective SDI practices:

• At present, the overall policies and regulations on SDI in Pakistan are in their infancy. Though attempts are being made towards formulating policies regarding geospatial data [46], an umbrella framework that provides coherence is still not well developed, and thus the country cannot adequately support the development of a comprehensive system for the integration and management of spatial data across sectors.
• Unfortunately, Pakistan is not very up-to-date in the implementation of highly technical geospatial science and technology. Deficiencies in today’s infrastructures, restrictions in access to advanced equipment, and low capital investments in the technology creation sector remain critical challenges to establishing a strong SDI.
• There are limitations on finances and human resources that present a great issue in Pakistan. A lack of funds and a shortage of qualified manpower for developing and maintaining effective SDIs makes it difficult for funds and initiatives to obtain support for SDI development.
• In contrast to the approaches characteristic of EU SDI development, which emphasize cooperation, Pakistan experiences difficulties in establishing effective partnerships and promoting data sharing between various organizations. Such problems are compounded by institutional siloes and a lack of trust between government departments and other stakeholders [47].

5.4.3. Assessment of Differences

In this respect, the current state of SDI practices in EU countries can be considered to differ from the conditions in Pakistan in several ways. The key differences include the following:

• There is strength in the policies already adopted across several liberalized EU countries. This facilitates SDI implementation, as opposed to Pakistan, which is in the process of coming up with relevant policies and formulations.
• The EU has extraordinary technologies and infrastructure, which are mandatory for developing effective SDIs. However, Pakistan has the problem of technological insecurity, which hinders the country from developing a good SDI.
• The access to resources—financial and human—is considerably higher in the EU, allowing for more complex and broad-scale SDI efforts. Pakistan, by contrast, has scarce human and financial capital, defining the scale and effectiveness of its SDI endeavours.
• The EU culture of collaboration, i.e., sharing data and building up partnerships based on institutional assets, is found to play an influential role in bringing success in SDI practices. The fact that Pakistan does not have such a culture, along with other institutional constraints, has adverse effects on the construction of integrated and coordinated SDI systems.
• Based on the above facts, the strengths and weaknesses of the SDI of Pakistan are presented in

  Table 5. Key strengths and weaknesses of SDI of Pakistan.

  Key Strengths	Key Weaknesses
  Pakistan is in the process of formulating relevant SDI policies, which shows a commitment to future development.	Unlike liberalized EU countries, Pakistan’s policies are still in development, leading to delays in effective SDI implementation.
  Initiatives towards adopting SDI in Pakistan indicate a growing recognition of its importance.	Pakistan faces significant technological challenges, including outdated infrastructure and limited access to cutting-edge SDI technologies.
  There is room for growth and development in both the financial and technological sectors to boost SDI.	Pakistan lacks sufficient financial and skilled human resources, which restricts the scale and complexity of SDI efforts.
  Ongoing policy formulation provides opportunities to create frameworks suited to the country’s unique challenges.	Unlike the EU’s strong institutional culture of data sharing and partnership, Pakistan lacks this, hindering coordinated and integrated SDI systems.
  Awareness of SDI’s potential benefits for sectors like agriculture and urban planning is increasing.	Various institutional limitations, such as weak partnerships and poor collaboration, reduce the effectiveness of Pakistan’s SDI development efforts.

  .

5.4.4. Implications for Pakistan

The analysis of EU practices offers several lessons for Pakistan:

• It is high time the government of Pakistan develop a national geospatial policy that aligns with best practices from around the globe, including the EU.
• There is a need to upscale Pakistan’s geospatial technology and frameworks. Pakistan can learn from the EU’s experiences in terms of the need to actualize on the development of interoperable systems and open data.
• Given the resource constraints identified, Pakistan needs to step up its efforts for capacity development, especially regarding training human capital and nurturing specialism in the sphere of geospatial science.
• It can also be seen that a culture of collaboration and data sharing is required within Pakistan. This may include the establishment of structures for bilateral cooperation between federal and provincial organs, similar to the structures within the EU.

6. Conclusions

The assessment of NSDI development in Pakistan using multi-view approaches such as the SDI readiness model, an organizational approach, and state of play revealed a lack of basic requirements necessary for its true development. This is evident by the low score (less than 0.5) of 12 out of 16 indicators across various domains, including public and private sector funding, ICT infrastructure, individual leadership, legal framework, politicians’ visions regarding SDI, the availability of relevant metadata, SDI-related education, cost-recovery mechanisms, indigenous geoinformation development, culture of open-source resource utilization, and human capital. While the SDI readiness model offers valuable insights into the NSDI status of a given country [21], it does not inherently provide solutions for addressing the low scores observed in some factors. These insights serve to highlight the associated challenges and weaknesses in NSDI development. Additionally, within the organizational approach, respondents exhibited disagreement regarding long-term vision, sustainable funding, inclusiveness and communication channels, and GI awareness. Similarly, the state-of-play assessment also witnessed different opinions from the respondents on the two matters of technology and standards. The insights show that improving the status of NSDI in Pakistan is a multilevel problem.

In light of these findings, the Survey of Pakistan could be designated as the main holding, coordinator, and facilitator of NSDI in the nation, as specified in Clause 15 of the Surveying and Mapping Act 2014 [42]. The Survey of Pakistan could play a pivotal role in addressing the challenges identified in Pakistan’s NSDI development, as highlighted in the results, through the following approaches:

• A strong coordination and administrative body should be formed for SDI management in conjunction with key players in the private and public sectors, as stated in Article 15 of the Surveying and Mapping Act 2014 [42]. This body shall create links with concerned public and private sector bodies and seek changes to regulatory procedures with crucial considerations for national spatial development.
• Awareness programs about the benefits of NSDI for politicians, the government, and the private sector should be promoted to create supporters and ensure suitable comprehension of the NSDI.
• Common guidelines, standards, and techniques should be established to make the deployment of NSDI effective; thus, systems and devices across different platforms will be consistent and interoperable.
• Private sector involvement, such as public-private partnerships (PPP) [48] or other suitable instruments, should be promoted to employ private sector problem-solving abilities and resources to speed up progress.
• Stable financial resources for NSDI should be set up to provide the geospatial data necessary for the continuity of important projects, including NSDI initiatives. Projects like the formation of new geodetic data by the country, as well as China–Pakistan Economic Corridor (CPEC) projects, can be incorporated to supplement the progress of NSDI development in Pakistan.

NSDI development in Pakistan needs continuous upgrades on all fronts to be able to overcome the restrictive aspects that have been mentioned above. The absence of an established NSDI has created problems with the identification of specialists in the area of SDI. Several experts in both the public and private sectors lacked sufficient experience and a proper understanding of SDI principles such as metadata and geoportals, which made it hard to determine unbiased stances on NSDI readiness.

This study only applied three assessment approaches; therefore, this study needs to be extended by the addition of other assessment modes, such as cadastral [17] and the clearinghouse maturity matrix [49], to obtain a wider understanding of Pakistan’s NSDI.