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Data Collection & Analysis

This assessment employed two core methods—an online survey and manual research—to seek information regarding the human and technological capacities for deep-sea exploration and research.

Published onSep 12, 2022
Data Collection & Analysis
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This assessment employed two core methods—an online survey and manual research—to seek information regarding the human and technological capacities for deep-sea exploration and research. The results are presented and discussed in this 2022 Global Deep-Sea Capacity Assessment report.

The Ocean Discovery League (ODL) team first distributed a survey to the global marine community on various social media platforms and through direct email campaigns. An international team of researchers conducted manual research using standard search engines to augment data collected by the survey. Both methods were used to seek the same information from different yet complementary sources, and the manual research filled several gaps in the survey responses.

We used both methodologies to gather information by country or territory with coastal areas and deep waters in their Exclusive Economic Zones (EEZ). We refer to those geographic areas as Geographical Areas, or “GeoAreas,” throughout the report. Applying both survey and manual research methods allowed us to present and discuss a baseline assessment of current deep-sea exploration and research capacities worldwide, amplified by direct contributions from those living and working in each GeoArea.

1 Data Collection

1.1 Survey

1.1.1 Content

The foundation of this report is data collected from a 42-question online survey that remained open from February to December 2021. The survey includes questions to collect quantitative information (e.g., “What kinds of deep submergence vehicles do you have access to?”), as well as qualitative information (e.g., “How important are deep submergence vehicles for your work?”). Respondents were invited to take the survey for one GeoArea at a time and as many GeoAreas as they felt qualified to represent. We intended to collect information about local capacity directly from those living and working in each GeoArea.

The first set of questions was about the respondent and their GeoArea (Q1, Q2), the state of deep-sea exploration within that GeoArea (Q3, Q4), and their community and relationship to deep-sea exploration (Q5, Q6). We then asked about in-country human capacities by asking respondents to provide the names of institutions involved in deep-sea exploration, such as universities and research laboratories (Q7), ministries and governmental agencies (Q8), and other organizations (Q9). We then asked respondents which marine industries are present in their GeoArea, for example, fisheries & aquaculture, deep-sea mining, tourism, or conservation & protection (Q10).  

Deep-sea exploration and research require specialized technical capacities such as vessels (Q11-Q16), deep submergence vehicles (Q17-Q22), sensor systems (Q23-Q27), and data analysis tools (Q28-Q32). For each type of technology, we asked how important it was for the respondent’s work (Q11, Q17, Q23, Q28) and whether or not they have access to different types of those technologies (e.g., ROVs, AUVs, HOVs, etc.) (Q13, Q18, Q24, Q29), how satisfied they are with them (Q14, Q20, Q25, Q30), and how increased access to such technologies might impact their work (Q15, Q21, Q26, Q31). We also included an open-ended question to allow respondents to add any additional comments about each category of technology (Q16, Q22, Q27, Q32). 

Finally, we asked respondents about what they consider to be the most significant opportunities and challenges related to deep-sea exploration and research (Q33, Q34). 

We also allowed participants to provide their contact information if they wanted to be emailed updates on the assessment and final report (Q35-Q38, optional). We asked for optional demographic information (e.g., gender, age, work sector, education level) (Q39-Q43).

1.1.2 Distribution

The survey was launched in February 2021 and concluded on December 31, 2021, as an activity associated with the UN Decade of Ocean Science for Sustainable Development. It was available in four languages: English, French, Portuguese, and Spanish. We used collaborative networks, social media, and other online platforms to share the survey as widely as possible. To incorporate perspectives from as many nations and communities as possible, we also searched for contact information of professionals from GeoAreas, for which we didn't have any or enough survey entries by using available online directories. For example, we used OceanExpert.org, a global directory of Marine and Freshwater professionals maintained by the International Oceanographic Data and Information Exchange (IODE) program of the Intergovernmental Oceanographic Commission (IOC) of UNESCO. Personalized invitations were sent to those professionals with a description of the assessment survey, its aims, and an assurance that the survey results would be publicly available. 

1.1.3 Translation

Open-ended questions from surveys received in French, Portuguese, and Spanish were translated to English by native speakers from the team and online translators.

1.2 Research

We conducted online research to supplement the data collected by the survey. We used the quantitative questions of the survey (Q7-10, Q12, Q18, Q24, and Q29) to identify areas for follow-up research. We recorded in-country human capacities by listing up to five organizations of different types working on deep-sea and marine-related topics: universities and research laboratories (Q7R), ministries and governmental agencies (Q8R), and other organizations (Q9R). We also recorded the presence of marine industries (Q10R). For the technical capacities, we recorded the presence of different types of vessels (Q12R), deep submergence vehicles (Q18R), sensors (Q24R), and data tools (Q29R), using the same options as the survey (Manual Research Protocol: Technical Capacity).

1.2.1 Research Process

Research for each GeoArea was conducted by a researcher from the GeoArea’s region itself. A team of eight researchers conducted this work: two worked on Africa, two on the Americas, one on Asia, one on Europe, and two on Oceania. In this way, the researcher’s personal and contextual knowledge supported the research and allowed them to consult with professionals in their networks. All information gathered through the research process was verified by web-based sources and/or official national or regional reports. We identified current in-country capacity, as well as capacity in prospect, in development, or dependent on foreign partners and capabilities (Manual Research Protocol: Codes). 

We researched inhabited coastal areas with >1% deep sea in their EEZ within the five regions of the world: Africa, Asia, the Americas, Oceania, and Europe. Each researcher spent four hours investigating each GeoArea using the same protocol (Manual Research Protocol). We searched for information online mainly in English, French, and Spanish and also used translations from Arabic, Bengali, Georgian, Indonesian, Persian, and Vietnamese sources when needed.

1.2.2 Data Collected

We collected information on the deep-sea exploration and research capacity of 186 GeoAreas worldwide. We collected 360 survey responses for 124 GeoAreas and conducted online research for 181 GeoAreas. We received 279 survey responses in English (77%), 43 in French (12%), 32 in Spanish (9%), and 6 in Portuguese (2%). For 119 GeoAreas, we have both survey and research data (64% of GeoAreas); for 62 GeoAreas, we have only research data (33%). For 5 GeoAreas, we have only survey data (3%) (Table 1; 2022 Data Tables: Global). 

Table 1

Number of data sources for each region of the world included in the 2022 Global Deep-Sea Capacity Assessment.

Region

No. of Surveys

No. of GeoAreas Surveyed

No. of GeoAreas Researched

No. of GeoAreas in GDSCA2022

Africa

101

33

44

44

Asia

75

27

30

33

Europe

33

18

24

26

Latin America & the Caribbean

90

33

50

50

Northern America

38

3

5

5

Oceania

23

10

28

28

TOTAL

360

124

181

186

1.3 Additional Data Sources

Additional reference resources include: 

2 Data Analysis

2.1 GeoArea Classifications

2.1.1 Geographical Classifications

We analyzed survey responses and research results at three levels: regions, subregions, and GeoAreas, depending on the type and completeness of data available. 

GeoAreas | GeoAreas are countries or territories (e.g., Mexico, Montserrat, Oman, etc.) [1]. GeoAreas were assigned to subregions and regions based on geographic location, not the administrative center. For example, French Polynesia, a territory of France, was assigned to Oceania, not Europe.

Subregions | Subregions are groups of 5-31 GeoAreas within a Region (Western Europe, Southeastern Asia, Caribbean, etc.) [1]. If a GeoArea was not included in the UNSD data, it was assigned to the subregion of closest proximity; for example, Clipperton Island was assigned to Central America and Saba to the Caribbean.

Regions | Regions are groups of 1-5 subregions with 5-68 GeoAreas [1]. If a GeoArea was not included in the REF data, it was assigned to the region of closest proximity; for example, Tristan da Cunha was assigned to Africa and Jan Mayen to Europe. For regional results, GeoAreas were assigned to one of five areas: Africa, Americas, Asia, Europe, and Oceania. For global results, the Americas was split into the UNSD’s intermediate region classification Northern America and Latin America & the Caribbean because of the high number of survey responses for the United States.

Global | All GeoAreas, subregions, and regions.

2.1.2 Other Classifications

Political Status & SIDS | GeoAreas were classified as either sovereign countries or dependent territories. GeoAreas were also classified as Small Island Developing States (SIDS), based on the UN Statistics Division M49 Standards [1]

Economic Groups | GeoAreas were classified as High Income, Upper Middle Income, Lower Middle Income, Low Income, or Not Classified, based on the World Bank Country and Lending Groups [2].

EEZ Status & Calculations | GeoAreas were classified as EEZ with Deep Ocean, EEZ No Deep Ocean, or No EEZ. GeoAreas with less than 1% deep-sea area within their EEZ were considered “EEZ No Deep Ocean.” These classifications were based on Esri, GEBCO, and Flanders data [3][4][5]. The area of each GeoArea’s EEZ was provided by ESRI and based on Flanders EEZ data. We used sovereign countries and permanently inhabited territories as GeoAreas. The areas of joint regimes were divided in half and added to each of the two GeoAreas that jointly claimed them, such as the joint regime claimed by both the United States and Russia. Overlapping claims were not included unless the claim was by a territory that was treated as its own GeoArea rather than a dependency of a sovereign state, such as the overlapping claim of the United Kingdom and Argentina, which was assigned to the GeoArea Falkland Islands.

Depth Zones | GeoArea EEZs were also broken down into the oceanographic depth zones:

  • Epipelagic Zone: 0-200 mbsl

  • Mesopelagic Zone: 200-1,000 mbsl

  • Bathyal Zone: 1,000-2,000 mbsl

  • Bathyal Zone: 2,000-4,000 mbsl

  • Abyssal Zone: 4,000-6,000 mbsl

  • Hadal Zone: >6,000 mbsl

The bathyal zone was split into two groups because 2,000 m is a common depth rating of deep submergence vehicles, such as Argo floats.

2.2 Survey Responses & Demographics

2.2.1 Geographic & Demographic Representation

Survey data only

Respondents were asked four questions about their geographic and demographic representation: which GeoArea they represent, in what GeoArea they live, their gender identification, and their age group. For each of the following questions, we calculated the total number of each response and the percent of each response for each subregion for regional results and region for global results.

Which GeoArea would you like to represent for this survey? (Q1)
Respondents selected the GeoArea they wanted to represent for the survey from a list of coastal countries and territories; they were also allowed to enter free text if their GeoArea was not an option. Our survey software limited the number of options, and we, therefore, could not list all GeoAreas with deep ocean in their EEZs.

As what gender do you identify? (Q41)
Respondents selected their gender identity from a list of gender identity options and could enter free text if they preferred to describe themselves.

What is your age? (Q39)
Respondents selected their age range from a list of age group options.

2.2.2 Professional Representation

Survey data only

Respondents were asked four questions about their professional identity: what is their highest level of education completed, in what organizational sector do they work, what are their primary roles, and in what marine environments do they work.

What is the highest degree or education level you have completed? (Q42)
Respondents selected the highest degree or educational level that they had completed from a list of education options. They were also allowed to enter free text if their educational level was not an option. The number of responses for each of the following categories was less than 4% of the total: High School, Some college, Some graduate school, and Trade School. We, therefore, grouped these selections with “Other.”

What is the organizational sector of your affiliation? (Q43)
Respondents selected the organizational sector of their affiliation from a list of organizational sector options. They were also allowed to enter free text if their sector was not an option. The number of responses for Industry and Philanthropy were less than 4% of the total. We, therefore, grouped these selections with “Other.”

What are the primary roles you represent in your GeoArea? (Q5)
Respondents selected up to three roles they represented in their GeoArea from a list of primary role options. They were also allowed to enter free text if their role was not an option. Less than 1% of respondents selected Government; we, therefore, combined Government with Policy/Law/Management.

If you carry out field research, in what marine environment(s) do you work? (Q6)
Respondents selected all marine environments in which they do field research from a list of marine environment options. They were also allowed to enter free text if their field-work environment was not an option.

2.3 Issues, Challenges, & Opportunities

Survey data only

Respondents were asked three questions about the deep-sea issues, challenges, and opportunities they considered most important for their GeoArea. For each region and subregion, we calculated the percent of each question's total number of selections. We then identified the three most frequently selected issues, challenges, and opportunities for each region and subregion.

What are the three most important deep-sea issues in your GeoArea? (Q3)
Respondents were asked to select up to three deep-sea issues that they considered most important for their GeoArea from a list of deep-sea issues. They were also allowed to enter free text if any issues important in their community were not included in the list.

What are the top three challenges to deep-sea exploration and research in your GeoArea? (Q33)
Respondents were asked to select up to three deep-sea exploration and research challenges that they considered most important for their GeoArea from a list of challenges. They were also allowed to enter free text if any challenges important in their community were not included in the list.

What are you most excited about in the next 5-10 years for deep-sea exploration and research in your GeoArea? (Q34)
Respondents were asked to select up to three opportunities in the next 5-10 years that they were most excited about for their GeoArea from a list of near- to long-term opportunities. They were also allowed to enter free text if any opportunities important in their community were not included in the list. There was an error in the format of this question in that while we asked respondents to select up to three options, they were allowed to choose as many as they wished; most respondents chose three, while some chose more.

2.4 Status of Deep-sea Exploration & Research

2.4.1 Importance, Tools, & Expertise

Survey data only

Survey respondents were asked to assess the status of deep-sea exploration and research in their GeoArea.

How would you assess the status of deep-sea (>200 m) exploration and research in your GeoArea? (Q4)
Respondents stated to what extent they agreed, on a 5-point scale, with the following statements:

  1. Deep-sea exploration and research are considered important in my GeoArea.

  2. We have in-country tools/technology to conduct deep-sea exploration and research.

  3. We have in-country expertise to conduct deep-sea exploration and research.

With this survey data, we:

  • Plotted all responses for each region and subregion using a five-point Likert scale; and,

  • Calculated the percentages of respondents who (1) agree or strongly agree, (2) do not agree nor disagree, and (3) disagree or strongly disagree.

2.4.2 Deep-Sea Capacity Status Parameters

Calculations based on Q4

We calculated three Status Parameters (SPs)—Importance, Tools, and Expertise—based on survey responses to Q4. We added the percent of agree or strongly agree responses for each statement for each subregion to calculate total agreement. We did not use GeoArea-level calculations SPs because, in many cases, we received only one survey response for a given GeoArea, which was not enough information to assess the status of a location.

The Importance Agreement is the percent of respondents who agreed or strongly agreed that deep-sea exploration and research was considered important in their GeoArea.

The Technology Agreement is the percent of respondents who agreed or strongly agreed that they had deep-sea tools/technology in their GeoArea.

The Expertise Agreement is the percent of respondents who agreed or strongly agreed that they had deep-sea expertise in their GeoArea.

After calculating each statement's overall agreement, we binned the resulting values into a status parameter scale of 1 to 5 for each question, using bins of 20% (Table 2).

Table 2

Conversion from percent of agreement to Status Assessment questions to Status Parameters.

Agreement

Status Parameter (SP)

0-20%

1

21-40%

2

41-60%

3

61-80%

4

81-100%

5

Each SP (Importance, Tools, Expertise) was then assigned to its corresponding subregions. For example, for Eastern Africa, 26% of respondents agreed, and 37% strongly agreed that deep-sea exploration and research were considered important in their GeoArea. This is a total of 63% agreement and an Importance SP of 4. 

Using this method, we: 

  • Calculated the ImportanceSP for each subregion;

  • Calculated the TechSP for each subregion; and,

  • Calculated the ExpertiseSP for each subregion.

2.4.3 Status Parameter Groups

Using the Importance, Tech, and Expertise Status Parameters, subregions were divided into six groups (Table 3).

Table 3

SP Group

Subregion

ImportanceSP

TechSP

ExpertiseSP

A

Eastern Asia

5

5

5

Western Europe

5

5

5

Northern Europe

4

5

5

B

Northern America

3

5

5

Australia & New Zealand

2

4

5

C

Southern Europe

2

3

4

South America

2

1

3

Eastern Europe

2

1

4

Northern Africa

3

2

3

Western Asia

3

3

3

D

Western Africa

4

1

3

Southeastern Asia

5

2

3

E

Eastern Africa

4

1

2

Melanesia

4

1

2

Micronesia

5

1

1

Southern Asia

4

2

2

F

Polynesia

3

1

1

Caribbean

2

1

2

Central America

2

1

2

Middle Africa

3

1

2

Southern Africa

3

1

2

By averaging the individual parameters for each group of subregions, we can also visually display the groups and how they compare to each other.

Figure 1

Average Technology (x-axis), Expertise (y-axis), and Importance (bubble size) Status Parameters for each subregional Status Parameter Group.

2.5 Organizations & Industries

2.5.1 Organizations

Survey and research data

Which universities and/or research labs, government agencies/ministries, and other organizations in your GeoArea study the deep sea or deal with deep-sea issues? (Q7-9, Q7R-9R)
We surveyed respondents and conducted research to identify deep-sea and marine organizations, including universities and research laboratories (Q7, Q7R), government agencies and ministries (Q8, Q8R), and other organizations (Q9, Q9R). Responses were open-text.

For each organization type, respondents could provide up to five organization names each. We also searched for additional organizations in our research. For example, we received two surveys for Chile and also researched that country. We, therefore, could have collected a maximum of 15 research institutions (10 from surveys and five from research) and a total of 45 organizations (3 organization types) for the GeoArea. 

In some cases, respondents and research results provided the names of the same organizations. In those cases, we removed duplicates and noted that both survey and research resulted in the same information. We also ensured that organizations were at the institutional level and not, for example,  a specific department or laboratory within an institution. Finally, the survey specifically asked for deep-sea-related organizations, while the research identified both deep-sea and marine-related organizations.

Using the cleaned and de-duplicated organizational data, we calculated the following for each region and subregion:

  • Number of each type of organization (academic, government, other);

  • Percent of each type of organization (academic, government, other);

  • Number of organizations identified by survey alone, research alone, and both survey and research;

  • Percent of organizations identified by survey alone, research alone, and both survey and research; and,

  • Number of organizations per data source per GeoArea.

2.5.2 Marine Industries

Survey and research data

What marine industries exist in each GeoArea? (Q10, Q10R)
We surveyed respondents and researched the presence of marine industries in each GeoArea: fisheries & aquaculture, marine transportation, tourism, conservation & protection, offshore oil & gas, safety & surveillance, marine construction, marine research & development, ocean renewable energy, and deep-sea mining [6]. Survey respondents were asked to select from a list of marine industries. They were also allowed to enter free text if any marine industries present in their GeoArea were not provided as an option. Researchers only focused on the industries provided in the list.

In the survey, there were originally thirteen industry options. In the data analysis process, we aggregated six categories into three. If a respondent selected one or both industries, it was counted as one:

  • Fisheries and/or Aquaculture -> Fisheries & Aquaculture

  • Marine transport and/or Shipping -> Marine Transportation

  • Marine R&D and/or Marine biotechnology -> Marine R&D

All other categories remained the same. In the end, there were a total of 10 marine industry categories.

Respondents and researchers could select which type of industries are present in the GeoArea of interest and specify if none of them or if other types of industries than those listed were accessible or present. 

With the research data, we:

  • Calculated the percent of GeoAreas within a subregion (or percent of GeoAreas within a region for global results) in which each type of industry was found; 

  • Identified in which GeoArea all types of industries were found, and in which five or fewer were found; and,

  • Identified the most and least commonly found industries in each subregion and region. 

With the survey data, we:

  • Calculated the most and least common marine industries in each region and subregion identified by respondents; 

  • Compared it to the research data to identify the biggest differences between survey and research results; and, 

  • Noted additional marine industries provided by respondents. 

2.6 Technical Capacity

We researched the presence of various types of vessels, deep submergence vehicles (DSVs), sensor systems, and data tools in each GeoArea. Survey respondents were asked about the importance of their access to, satisfaction with, and potential impact of the same types of tools. For these tools, survey responses allowed us to assess the access to those capacities within each country. At the same time, research results were used to establish what capacity is present in the GeoArea and whether it was accessible.

2.6.1 Importance

Survey data only

How important are ships/vessels for your work? (Q11)
How important are deep submergence vehicles (DSVs) for your work? (Q17)
How important are deep-sea sensors for your work? (Q23)
How important are data analysis & access tools for your work? (Q28)
Respondents were asked how important ships and vessels (Q11), DSVs(Q17), deep-sea sensor systems (Q23), and data analysis and access tools (Q28) are for their work on a five-point scale, from very important to not important. 

For each type of tool in each region and subregion, we:

  • Plotted all responses for each region and subregion using a five-point Likert scale;

  • Calculated the number of respondents who considered it important or very important for their work; and,

  • Calculated the percent of respondents who considered it important or very important for their work.

2.6.2 Presence

Research data only

What types of vessels are present in each GeoArea? (Q12R)
We searched for the types of vessels present in each GeoArea, specifically if the GeoArea has research, fishing, cruise ships, recreational, traditional, navy, and/or other types of vessels. 

What types of deep submergence vehicles are present in each GeoArea? (Q18R)
We researched the types of DSVs present in each GeoArea, specifically whether the GeoArea had remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), human-occupied vehicles (HOVs), benthic landers, drifters, or towsleds. 

What types of deep-sea sensor systems are present in each GeoArea? (Q24R)
We searched for the types of sensor systems present in each GeoArea, specifically if the GeoArea has CTDs, O2, pH, and/or eH sensors, water sampling systems, navigation systems, seafloor mapping systems, and/or imaging systems. We recorded if the tools were qualified for deep-sea or shallow work for the regions of Asia, the Americas, and Europe. However, we did not fully record shallow versus deep capabilities for Africa and Oceania.  

What kinds of data analysis & access tools are present in each GeoArea? (Q29R)
We researched specific types of data tools present in each GeoArea, including GIS, data management tools, data storage capacity, data visualization tools, machine learning/artificial intelligence (AI/ML), cloud computing, and/or genomic sequencing tools. 

For each type of tool in each GeoArea, we recorded its presence or absence, with presence meaning that at least one system of a given technology was found in the GeoArea. 

Using this research data, we:

  • Calculated the percent of GeoAreas within a subregion (or percent of GeoAreas within a region for global results) where each type of technology was found; 

  • Identified in which GeoArea all types of technologies were found, and in which half or fewer were found; and,

  • Identified which were the most and least commonly found technologies in each subregion and region. 

2.6.3 Access

Survey data only

What kinds of vessels do you have access to for deep-sea work? (Q12/13)
Respondents were asked to select all types of vessels to which they had access for deep-sea work in their GeoArea: research vessels, fishing vessels, recreational vessels, traditional vessels, cruise ships, or none of the above. They were also allowed to enter free text if a type of vessel they had access to was not an option. In the initial survey, there was an error in that respondents were not allowed to select more than one option; because the survey was underway, we could not change the question directly but added the same question with the correct settings for unlimited selections. We did not include naval vessels as an option in the survey but did include them in our research on vessel presence.

What kinds of DSVs do you have access to for deep-sea work? (Q18)
Respondents were asked to select all types of DSVs to which they had access in their GeoArea: ROVs, AUVs, benthic landers, drifters, towsleds, HOVs, or none of the above. They were also allowed to enter free text if a type of DSV to which they had access was not an option.

What kinds of deep-sea sensors do you have access to for deep-sea work? (Q24)
Respondents were asked to select all types of deep-sea sensor systems to which they have access in their GeoArea: CTDs, water sampling, oxygen/pH/eH, seafloor mapping, imaging, navigation, eDNA, or none of the above. They were also allowed to enter free text if a type of sensor system they had access to was not an option.

What kinds of data analysis & access tools do you have access to? (Q29)
Respondents were asked to select all types of data tools to which they had access in their GeoArea: GIS, data management, data storage, data visualization, cloud computing, genomic sampling, machine learning/artificial intelligence, or none of the above. They were also allowed to enter free text if a type of data tool they had access to was not an option.

Using this survey data, we:

  • Calculated the most commonly available types of tools for each subregion and region;

  • Calculated the number and percentage of respondents who did not have access to any of the types of tools; and,

  • Noted additional technologies to which respondents had access, as well as barriers that prevented them from accessing vessels, DSVs, sensor systems, and data tools.

What is the approximate depth range of DSVs in your GeoArea? (Q19)
Respondents were asked how deep the vehicles they had access to could operate from a list of five depth ranges, or not applicable. 

To correlate DSV depth capabilities to oceanographic depth zones, we converted them to the most closely related depth zone (Table 4). When converting, we only replaced respondents' answers with a response shallower to avoid assuming DSVs could go deeper than the respondent's selection.

Table 4

Conversion from respondent-selected depth zones to oceanographic depth zones.

Respondent Selection

Corresponding Depth Zone

0-300 m

0 - 200 m

0-1,000 m

200 - 1,000 m

0-3,000 m

1,000 - 2,000 m

0-5,000 m

2,000 - 4,000 m

0-11,000 m

>4,000 m

2.6.4 Satisfaction

Survey data only

How well do the vessels meet your needs? (Q14)
Respondents were asked how satisfied they were with vessels in their GeoArea regarding cost, availability, capabilities, size, and duration on a five-point scale, from very satisfied to very dissatisfied.

How well do the DSVs meet your needs? (Q20)
Respondents were asked how satisfied they were with DSVs in their GeoArea in terms of cost, availability, capabilities, depth rating, and duration on a five-point scale, from very satisfied to very dissatisfied. 

How well do deep-sea sensors meet your needs? (Q25)
Respondents were asked how satisfied they were with deep-sea sensor systems in their GeoArea in terms of cost, availability, capabilities, depth rating, ease of use, and accuracy on a five-point scale, from very satisfied to very dissatisfied. 

How well do data analysis & access tools meet your needs? (Q30)
Respondents were asked how satisfied they were with data analysis and access tools in their GeoArea regarding cost, availability, capabilities, ease of use, and bandwidth on a five-point scale, from very satisfied to very dissatisfied. 

Using this survey data, we: 

  • Calculated the response rate to these questions because they were optional;

  • Calculated the overall satisfaction of each type of tool for each region and subregion by adding the number of respondents who were satisfied or very satisfied (overall satisfaction) and dissatisfied or very dissatisfied (overall dissatisfaction) with every aspect of each tool;

  • Calculated the number and percentage of respondents for each region and subregion who were satisfied or very satisfied, and dissatisfied or very dissatisfied with each aspect of vessel, DSV, sensor, and data tool operation; and,

  • Noted additional comments provided by respondents with regard to barriers to access for vessels, DSVs, sensors, and data tools in their GeoArea.

2.6.5 Potential Impact

Survey data only

What is the potential impact of increased access to vessels? (Q15)
What is the potential impact of increased access to DSVs in your GeoArea? (Q21)
What is the potential impact of increased access to deep-sea sensors? (Q26)
What is the potential impact of increased access to data analysis & access tools in your GeoArea? (Q31)
Respondents were asked what impact increased access to vessels (Q15), DSVs (Q21), sensor systems (Q26), and data tools (Q31) would have on their work on a five-point scale, from no impact to transformative. 

For each type of tool in each region and subregion, we:

  • Plotted all responses for each region and subregion using a Likert scale; 

  • Calculated the number of respondents who thought that increased access would have a high impact or be transformative for their work; and,

  • Calculated the percent of respondents who thought that increased access would have a high impact or be transformative for their work.

2.7 Deep-Sea Capacity Indices & Groups

2.7.1 Presence Index

The Deep-Sea Capacity Presence Index (DSCPI) is a relative index of organizations, industries, and technical capacities present in a single GeoArea. Using data from the Technical Capacity Presence research, we calculated the DSCPI for each GeoArea. To calculate the DSCPI, we added the total number of capacities present for each type of capacity (organizations, industries, vessels, DSVs, etc.), and divided by the maximum number of possibilities to get a scale of 0 to 1 for each (Equations 1-7).

The organizational presence index (orgPI) is the sum of organizations present in a GeoArea divided by the maximum total possible (orgmax), based on number of data sources for that GeoArea:

orgPI=eduP+govP+orgPorgmax(1){\scriptsize org_{PI} = \frac{edu_P + gov_P + org_P}{org_{max}}} \tag{1}


The marine industry presence index (indPI) is the sum of types of industries present in a GeoArea (typeP) divided by the maximum total possible types (indmax = 10):

indPI=fishP+transP+tourP+consP+oilP+safeP+constP+R&DP+renewP+dsmPindmax(2){\tiny ind_{PI} = \frac{fish_P + trans_P + tour_P + cons_P + oil_P + safe_P + const_P + R\&D_P + renew_P + dsm_P}{ind_{max}}} \tag{2}


The vessel presence index (vesselPI) is the sum of types of vessels present in a GeoArea (typeP) divided by the maximum total possible types (vesselmax = 6):

vesselPI=researchP+fishP+cruiseP+recP+tradP+navyPvesselmax(3){\scriptsize vessel_{PI} = \frac{research_{P} + fish_{P} + cruise_{P} + rec_{P} + trad_{P} + navy_{P}}{vessel_{max}}} \tag{3}


The DSV presence index (vesselPI) is the sum of types of DSVs present in a GeoArea (typeP) divided by the maximum total possible types (dsvmax = 6):

dsvPI=rovP+auvP+hovP+landerP+drifterP+towsledPdsvmax(4){\scriptsize dsv_{PI} = \frac{rov_{P} + auv_{P} + hov_{P} + lander_{P} + drifter_{P} + towsled_{P}}{dsv_{max}}} \tag{4}


The sensor presence index (sensorPI) is the sum of types of sensor systems present in a GeoArea (typeP) divided by the maximum total possible types (sensormax = 7):

sensorPI=ctdP+waterP+chemP+mapP+navP+imageP+ednaPsensormax(5){\scriptsize sensor_{PI} = \frac{ctd_{P} + water_{P} + chem_{P} + map_{P} + nav_{P} + image_{P} + edna_{P}}{sensor_{max}}} \tag{5}


The data presence index (dataPI) is the sum of types of data tools present in a GeoArea (typeP) divided by the maximum total possible types (datamax = 7):

dataPI=gisP+storageP+mgtP+vizP+cloudP+mlaiP+genomePdatamax(6){\scriptsize data_{PI} = \frac{gis_{P} + storage_{P} + mgt_{P} + viz_{P} + cloud_{P} + mlai_{P} + genome_{P}}{data_{max}}} \tag{6}


Where typeP is 1 for presence of the technology type or 0 for absence. If any of the resulting presence indices was 0, we replaced it with 0.01. We calculated took the geometric mean of the presence variables:

geoPI=(vesselPIdsvPIsensorPIdataPIorgPIindPI)1numPI(7){\scriptsize geo_{PI} = (vessel_{PI}*dsv_{PI}*sensor_{PI}*data_{PI}*org_{PI}*ind_{PI})^\frac{1}{num_{PI}}} \tag{7}


The geoPI results were again on a scale of 0 to 1, which we divided into 5 groups to attain the DSCPI, which was assigned to each GeoArea (Table 5). A DSCPI of 5 means that we found a very high amount of organizational and technical infrastructure in that GeoArea; a DSCPI of 1 means that we found a very low amount of organizational and technical infrastructure. Globally, the highest number of GeoAreas had an overall DSCPI of 2; the fewest had an overall DSCPI of 5 (Figure 2).

Table 5

Conversion from geoPI to Deep-Sea Capacity Presence Index (DSCPI)

geoPI

DSCPI

0 - 0.15

1

0.16-0.40

2

0.41-0.65

3

0.66-0.90

4

0.01-1.00

5

Figure 2

Distribution of the Deep-Sea Capacity Presence Index (DSCPI), a relative index of organizations, industries, and technical capacities present in a single GeoArea. A DSCPI of 5 indicates the most presence of infrastructure and capacities while a DSCPI of 1 indicates the least capacity present in a GeoArea.

2.7.2 Accessibility Index

The vessel accessibility index (vesselAI) is the sum of the types of vessels available to all respondents in a subregion (typeA), divided by the maximum number of vessel types of available (vesselmax = 5), divided by the number of respondents (respondentsnum):

vesselAI=researchA+fishA+recA+cruiseA+traditionalAvesselmaxrespondentsnum(8){\scriptsize vessel_{AI} = \frac{research_A + fish_A + rec_A + cruise_A + traditional_A}{\frac{vessel_{max}}{respondents_{num}}}} \tag{8}


The DSV accessibility index (dsvAI) is the sum of the types of DSVs available to all respondents in a subregion (typeA), divided by the maximum number of DSV types of available (dsvmax = 6), divided by the number of respondents (respondentsnum):

dsvAI=rovA+auvA+landerA+drifterA+hovA+towsledAdsvmaxrespondentsnum(9){\scriptsize dsv_{AI} = \frac{rov_A + auv_A + lander_A + drifter_A + hov_A + towsled_A}{\frac{dsv_{max}}{respondents_{num}}}} \tag{9}


The sensor accessibility index (sensorAI) is the sum of the types of sensor systems available to all respondents in a subregion (typeA), divided by the maximum number of sensor types of available (sensormax = 7), divided by the number of respondents (respondentsnum):

sensorAI=ctdA+waterA+chemA+navA+mapA+imageA+ednaAsensormaxrespondentsnum(10){\scriptsize sensor_{AI} = \frac{ctd_A + water_A + chem_A + nav_A + map_A + image_A + edna_A}{\frac{sensor_{max}}{respondents_{num}}}} \tag{10}


The data accessibility index (dataAI) is the sum of the types of data tools available to all respondents in a subregion (typeA), divided by the maximum number of data tool types of available (datamax = 7), divided by the number of respondents (respondentsnum):

dataAI=gisA+mgtA+storageA+cloudA+vizA+mlaiA+genomicsAdatamaxrespondentsnum(11){\scriptsize data_{AI} = \frac{gis_A + mgt_A + storage_A + cloud_A + viz_A + mlai_A + genomics_A}{\frac{data_{max}}{respondents_{num}}}} \tag{11}


Where typeA is 1 for available of the technology type or 0 for not available. If any of the accessibility indices was 0, we replaced it with 0.01. We then calculated the geometric mean of this set of values:

geoAI=(vesselAIdsvAIsensorAIdataAI)1numAI(12){\scriptsize geo_{AI} = (vessel_{AI}*dsv_{AI}*sensor_{AI}*data_{AI})^\frac{1}{num_{AI}}} \tag{12}


The geoAI resulted in a range of values 0.02 to 0.64. We then divided the results into 5 groups to attain the DSCAI for each subregion (Table 6). A DSCAI of 5 means that we found a very high level of access to vessels, DSVs, sensors, and data tools in that subregion; a DSCAI of 1 means that we found a very low level of access to those tools. Globally, the highest number of subregions had an overall DSCAI of 2; the fewest had an overall DSCAI of 1 (Figure 3).

Table 6

Conversion from geoAI to Deep-Sea Capacity Accessibility Index (DSCAI)

geoAI

DSCAI

0.02 - 0.13

1

0.14-0.26

2

0.27-0.39

3

0.40-0.52

4

0.53-0.65

5

Figure 3

Distribution of the Deep-Sea Capacity Accessibility Index (DSCAI), a relative index of respondent access to four technical capacities present in a subregion: vessels, DSVs, sensor systems, and data tools. A DSCAI of 5 indicates the most access to technical capacities while a DSCAI of 1 indicates the least technical capacity access in a GeoArea.

2.7.3 Satisfaction Index

The Deep-Sea Capacity Satisfaction Index (DSCSI) is a relative index of satisfaction with four technical capacities to which respondents had access in a subregion: vessels, DSVs, sensor systems, and data tools. We calculated the DSCSI using responses from the Technical Capacity Satisfaction survey questions. Each DSCSI was then assigned to its corresponding subregion. We did not use GeoArea-level calculations for the DSCSI because we often received only one survey response for a given GeoArea, which was not enough information to assess the respondents’ satisfaction with the tools of a location. To determine the DSCAI, we first summed the percent of satisfied and very satisfied responses for each aspect of each deep-sea technology to calculate satisfaction for that type of tool (Equations 13-17). 

Vessel satisfaction (vesselSI) is the percent of respondents satisfied or very satisfied with cost, availability, capabilities, size, and duration (variable%S+VS) of vessels:

vesselSI=cost%S+VS+avail%S+VS+cap%S+VS+size%S+VS+dur%S+VS(13){\scriptsize vessel_{SI} = cost_{\%S+VS} + avail_{\%S+VS} + cap_{\%S+VS} + size_{\%S+VS} + dur_{\%S+VS}} \tag{13}


DSV satisfaction (dsvSI) is the percent of respondents satisfied or very satisfied with cost, availability, capabilities, depth rating, and duration (variable%S+VS) of DSVs:

dsvSI=cost%S+VS+avail%S+VS+cap%S+VS+depth%S+VS+dur%S+VS(14){\scriptsize dsv_{SI} = cost_{\%S+VS} + avail_{\%S+VS} + cap_{\%S+VS} + depth_{\%S+VS} + dur_{\%S+VS}} \tag{14}


Sensor satisfaction (sensorSI) is the percent of respondents satisfied or very satisfied with cost, availability, capabilities, depth rating, ease of use, and accuracy (variable%S+VS) of sensor systems:

sensorSI=cost%S+VS+avail%S+VS+cap%S+VS+depth%S+VS+ease%S+VS+acc%S+VS(15){\tiny sensor_{SI} = cost_{\%S+VS} + avail_{\%S+VS} + cap_{\%S+VS} + depth_{\%S+VS} + ease_{\%S+VS} + acc_{\%S+VS}} \tag{15}


Data tool satisfaction (dataSI) is the percent of respondents satisfied or very satisfied with cost, availability, capabilities, ease of use, and bandwidth (variable%S+VS) of data tools:

dataSI=cost%S+VS+avail%S+VS+cap%S+VS+ease%S+VS+bw%S+VS(16){\scriptsize data_{SI} = cost_{\%S+VS} + avail_{\%S+VS} + cap_{\%S+VS} + ease_{\%S+VS} + bw_{\%S+VS}} \tag{16}


If any of the satisfaction indices was 0, we replaced it with 0.01. We then calculated the geometric mean of these values to determine the overall satisfaction level for each GeoArea:

geoSI=(vesselSIdsvSIsensorSIdataSI)1numSI(17){\scriptsize geo_{SI} = (vessel_{SI}*dsv_{SI}*sensor_{SI}*data_{SI})^\frac{1}{num_{SI}}} \tag{17}


The geoSI resulted in a minimum of 0.03 and a maximum of 0.79; we then divided the results into five groups within this range to attain the DSCSI, which was assigned to each subregion (Table 7). A DSCSI of 5 means that respondents in the subregion were most satisfied with the tools to which they have access. A DSCSI of 1 means that respondents in the given subregion were least satisfied with the vessels, DSVs, sensors, and data tools available to them. Globally, the highest number of subregions had an overall DSCSI of 2; the fewest had an overall DSCSI of 5 (Figure 4). 

Table 7

Conversion from geoSI to Deep-Sea Capacity Satisfaction Index (DSCSI)

geoSI

DSCSI

0.0 - 0.16

1

0.17-0.32

2

0.33-0.48

3

0.49-0.64

4

0.65-0.80

5

Figure 4

Distribution of the Deep-Sea Capacity Satisfaction Index (DSCSI), a relative index of respondent satisfaction with four technical capacities present in a subregion: vessels, DSVs, sensor systems, and data tools. A DSCSI of 5 indicates the most respondent satisfaction with technical capacities while a DSCSI of 1 indicates the least satisfaction with technical capacities in a GeoArea.

2.7.4 DSC Groups

Using the average Deep-Sea Capacity Presence Indices, Accessibility Indices, and Satisfaction Indices, subregions were divided into four groups (Table 8).

Table 8

DSC Group

Subregion

Presence Index

Accessibility Index

Satisfaction Index

A

Northern Europe

4.1

5.0

5.0

Northern America

3.4

5.0

4.0

B

Southeastern Asia

3.3

3.0

3.0

Australia & New Zealand

2.8

4.0

3.0

Western Europe

3.5

3.0

4.0

Southern Europe

3.7

4.0

4.0

Eastern Asia

3.8

4.0

4.0

C

South America

3.3

2.0

2.0

Southern Africa

3.3

3.0

2.0

Eastern Europe

3.5

3.0

2.0

Southern Asia

3.7

3.0

2.0

Northern Africa

3.3

2.0

3.0

Western Asia

2.8

3.0

3.0

D

Micronesia

2.4

1.0

1.0

Melanesia

2.6

2.0

1.0

Middle Africa

2.1

2.0

2.0

Caribbean

2.1

2.0

2.0

Western Africa

2.3

2.0

2.0

Eastern Africa

2.5

2.0

2.0

Polynesia

1.9

2.0

3.0

Central America

2.8

2.0

3.0

Using the Deep-Sea Indices for each subregion, we can visually display the groups and how their indices compare to each other.

Figure 5

Subregions plotted by Deep-Sea Capacity Presence Index (x-axis), Accessibility Index (y-axis), and Satisfaction Index (bubble size). Colors indicate Deep-Sea Capacity Index Groups, based on the combination of indices.

3 Room for Improvement

The way the data was collected has its limitations and, as a result, impacts some of our analysis. This calls for care when interpreting the results. Here, we describe the limitations that may have impacted our results, which could be addressed in future capacity assessments. 

3.1 The Survey

We searched for contact information online to reach marine professionals from as many countries as possible. Some unconscious biases might have been introduced in selecting those contacts, for example, towards more senior professionals or those with a significant online presence.

Although the survey was shared in four broadly-used languages, language may have been a barrier to some professionals’ ability to participate.

3.2 The Research

Some information about the capacity for deep-sea exploration and research is not explicitly available online. In such cases, the ability of the researcher to connect with professionals in the GeoArea of interest was crucial but not always possible. In addition, we limited the manual research to four hours per GeoArea. Therefore, we may not have obtained an exhaustive list of all the human and technological capacities that could be used for deep-sea exploration and research. We also encountered difficulties finding information for some GeoAreas where access to information online is protected, such as the Democratic People's Republic of Korea (North Korea). However, we believe that combining the survey and manual research data may have overcome some of those issues.  

The fact that eight different researchers each worked on a selection of GeoAreas may have introduced some variation in the way data was collected and recorded. Even though we tried to remain as consistent as possible by having a fixed research protocol, there could be variations in how the researchers interpreted the protocol. For example, each researcher may have had different approaches to defining types of institutions, whether or not capacity is foreign or local, especially for territories under the regulation of another nation, and other specificities. Therefore, some questions were more challenging to answer than others because the options were relatively broad and left open to the researchers' interpretation. 

In addition, some options of capacities, like data tools, were challenging to find evidence for during the online search unless there was a website from a corporate organization available. For example, the evidence found in a paper that GIS was used for analysis, or a company providing GIS services, does not mean that this tool is readily available. 

Additionally, the nomenclature, data formats, and information access vary widely among GeoAreas. Therefore, we do not claim that we have created an exhaustive or fully representative list of global deep-sea capacities. Another reason the current capacity assessment cannot be exhaustive is that we had to limit our search for the list of institutions within each GeoArea to five institutions per question, i.e., per category (Q7R-Q9R), due to time constraints.   

Finally, for an overseas territory, we considered the capacities of its sovereign country as foreign capacities because they are not present in the territory itself (e.g., French capacities were not considered local in French Polynesia unless they were physically located and operated there). However, the distinction between technical and organizational capacities that overseas territories have (or do not have) was not always straightforward, as some territories are still partially or largely dependent on the resources from the sovereign country. We used our best judgment to differentiate between local and foreign capacity and tried to follow the same rules across regions. Still, the ultimate decision was left open for the researcher's interpretation.

3.3 Complementary Approaches

The survey was openly shared, but we did not receive answers for all coastal GeoAreas with deep-sea in their EEZ, so the manual research was a way to fill that gap. We also received responses from GeoAreas that are not in the list of GeoAreas for which we did research because they have <1%  deep-sea area in their EEZ (e.g., Bahrain, Belgium, Germany, or Cambodia). The discrepancies in the list of GeoAreas that we have data for between the survey and the manual research make it difficult to directly compare results from both data sources at global, regional, and subregional levels. Still, we believe that the general trends can be examined. 

The two methodologies—the online survey and manual research—are complementary in terms of GeoArea and the type of capacities covered. Both approaches allowed us to build a more substantial basis to understand the extent and distribution of capacities for deep-sea exploration and research worldwide. Additionally, because the researchers were from each GeoArea region, they could surface information others may have overlooked, thanks to their cultural and personal context.

Future capacity assessments will be an opportunity to include modifications and new questions to remedy the ambiguities and difficulties associated with the limits of information collected for the 2022 Global Deep-Sea Capacity Assessment.

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