Abstract

Estache and Goicoechea present an infrastructure database that was assembled from multiple sources. Its main purposes are: (i) to provide a snapshot of the sector as of the end of 2004; and (ii) to facilitate quantitative analytical research on infrastructure sectors. The related working paper includes definitions, source information and the data available for 37 performance indicators that proxy access, affordability and quality of service (most recent data as of June 2005). Additionally, the database includes a snapshot of 15 reform indicators across infrastructure sectors.

This is a first attempt, since the effort made in the World Development Report 1994, at generating a database on infrastructure sectors and it needs to be recognized as such. This database is not a state of the art output—this is being worked on by sector experts on a different time table. The effort has however generated a significant amount of new information. The database already provides enough information to launch a much more quantitative debate on the state of infrastructure. But much more is needed and by circulating this information at this stage, we hope to be able to generate feedback and fill the major knowledge gaps and inconsistencies we have identified.

Geographic coverage

The database covers the following countries: - Afghanistan - Albania - Algeria - American Samoa - Andorra - Angola - Antigua and Barbuda - Argentina - Armenia - Aruba - Australia - Austria - Azerbaijan - Bahamas, The - Bahrain - Bangladesh - Barbados - Belarus - Belgium - Belize - Benin - Bermuda - Bhutan - Bolivia - Bosnia and Herzegovina - Botswana - Brazil - Brunei - Bulgaria - Burkina Faso - Burundi - Cambodia - Cameroon - Canada - Cape Verde - Cayman Islands - Central African Republic - Chad - Channel Islands - Chile - China - Colombia - Comoros - Congo, Dem. Rep. - Congo, Rep. - Costa Rica - Cote d'Ivoire - Croatia - Cuba - Cyprus - Czech Republic - Denmark - Djibouti - Dominica - Dominican Republic - Ecuador - Egypt, Arab Rep. - El Salvador - Equatorial Guinea - Eritrea - Estonia - Ethiopia - Faeroe Islands - Fiji - Finland - France - French Polynesia - Gabon - Gambia, The - Georgia - Germany - Ghana - Greece - Greenland - Grenada - Guam - Guatemala - Guinea - Guinea-Bissau - Guyana - Haiti - Honduras - Hong Kong, China - Hungary - Iceland - India - Indonesia - Iran, Islamic Rep. - Iraq - Ireland - Isle of Man - Israel - Italy - Jamaica - Japan - Jordan - Kazakhstan - Kenya - Kiribati - Korea, Dem. Rep. - Korea, Rep. - Kuwait - Kyrgyz Republic - Lao PDR - Latvia - Lebanon - Lesotho - Liberia - Libya - Liechtenstein - Lithuania - Luxembourg - Macao, China - Macedonia, FYR - Madagascar - Malawi - Malaysia - Maldives - Mali - Malta - Marshall Islands - Mauritania - Mauritius - Mayotte - Mexico - Micronesia, Fed. Sts. - Moldova - Monaco - Mongolia - Morocco - Mozambique - Myanmar - Namibia - Nepal - Netherlands - Netherlands Antilles - New Caledonia - New Zealand - Nicaragua - Niger - Nigeria - Northern Mariana Islands - Norway - Oman - Pakistan - Palau - Panama - Papua New Guinea - Paraguay - Peru - Philippines - Poland - Portugal - Puerto Rico - Qatar - Romania - Russian Federation - Rwanda - Samoa - San Marino - Sao Tome and Principe - Saudi Arabia - Senegal - Seychelles - Sierra Leone - Singapore - Slovak Republic - Slovenia - Solomon Islands - Somalia - South Africa - Spain - Sri Lanka - St. Kitts and Nevis - St. Lucia - St. Vincent and the Grenadines - Sudan - Suriname - Swaziland - Sweden - Switzerland - Syrian Arab Republic - Tajikistan - Tanzania - Thailand - Togo - Tonga - Trinidad and Tobago - Tunisia - Turkey - Turkmenistan - Uganda - Ukraine - United Arab Emirates - United Kingdom - United States - Uruguay - Uzbekistan - Vanuatu - Venezuela, RB - Vietnam - Virgin Islands (U.S.) - West Bank and Gaza - Yemen, Rep. - Yugoslavia, FR (Serbia/Montenegro) - Zambia - Zimbabwe

Kind of data

Aggregate data [agg]

Mode of data collection

Face-to-face [f2f]

Response rate

Sector Performance Indicators

Energy The energy sector is relatively well covered by the database, at least in terms of providing a relatively recent snapshot for the main policy areas. The best covered area is access where data are available for 2000 for about 61% of the 207 countries included in the database. The technical quality indicator is available for 60% of the countries, and at least one of the perceived quality indicators is available for 40% of the countries. Price information is available for about 41% of the countries, distinguishing between residential and non residential.

Water & Sanitation Because the sector is part of the Millennium Development Goals (MDGs), it enjoys a lot of effort on data generation in terms of the access rates. The WHO is the main engine behind this effort in collaboration with the multilateral and bilateral aid agencies. The coverage is actually quite high -some national, urban and rural information is available for 75 to 85% of the countries- but there are significant concerns among the research community about the fact that access rates have been measured without much consideration to the quality of access level. The data on technical quality are only available for 27% of the countries. There are data on perceived quality for roughly 39% of the countries but it cannot be used to qualify the information provided by the raw access rates (i.e. access 3 hours a day is not equivalent to access 24 hours a day).

Information and Communication Technology The ICT sector is probably the best covered among the infrastructure sub-sectors to a large extent thanks to the fact that the International Telecommunications Union (ITU) has taken on the responsibility to collect the data. ITU covers a wide spectrum of activity under the communications heading and its coverage ranges from 85 to 99% for all national access indicators. The information on prices needed to make assessments of affordability is also quite extensive since it covers roughly 85 to 95% of the 207 countries. With respect to quality, the coverage of technical indicators is over 88% while the information on perceived quality is only available for roughly 40% of the countries.

Transport The transport sector is possibly the least well covered in terms of the service orientation of infrastructure indicators. Regarding access, network density is the closest approximation to access to the service and is covered at a rate close to 90% for roads but only at a rate of 50% for rail. The relevant data on prices only cover about 30% of the sample for railways. Some type of technical quality information is available for 86% of the countries. Quality perception is only available for about 40% of the countries.

Institutional Reform Indicators

Electricity The data on electricity policy reform were collected from the following sources: ABS Electricity Deregulation Report (2004), AEI-Brookings telecommunications and electricity regulation database (2003), Bacon (1999), Estache and Gassner (2004), Estache, Trujillo, and Tovar de la Fe (2004), Global Regulatory Network Program (2004), Henisz et al. (2003), International Porwer Finance Review (2003-04), International Power and Utilities Finance Review (2004-05), Kikukawa (2004), Wallsten et al. (2004), World Bank Caribbean Infrastructure Assessment (2004), World Bank Global Energy Sector Reform in Developing Countries (1999), World Bank staff, and country regulators. The coverage for the three types of institutional indicators is quite good for the electricity sector. For regulatory institutions and private participation in generation and distribution, the coverage is about 80% of the 207 counties. It is somewhat lower on the market structure with only 58%.

Water & Sanitation The data on water policy reform were collected from the following sources: ABS Water and Waste Utilities of the World (2004), Asian Developing Bank (2000), Bayliss (2002), Benoit (2004), Budds and McGranahan (2003), Hall, Bayliss, and Lobina (2002), Hall and Lobina (2002), Hall, Lobina, and De La Mote (2002), Halpern (2002), Lobina (2001), World Bank Caribbean Infrastructure Assessment (2004), World Bank Sector Note on Water Supply and Sanitation for Infrastructure in EAP (2004), and World Bank staff. The coverage for institutional reforms in W&S is not as exhaustive as for the other utilities. Information on the regulatory institutions responsible for large utilities is available for about 67% of the countries. Ownership data are available for about 70% of the countries. There is no information on the market structure good enough to be reported here at this stage. In most countries small scale operators are important private actors but there is no systematic record of their existence. Most of the information available on their role and importance is only anecdotal.

Information and Communication Technology The report Trends in Telecommunications Reform from ITU (revised by World Bank staff) is the main source of information for this sector. The information on institutional reforms in the sector is however not as exhaustive as it is for its sector performance indicators. While the coverage on the regulatory institutions is 100%, it varies between 76 and 90% of the countries for more of the other indicators. Quite surprisingly also, in contrast to what is available for other sectors, it proved difficult to obtain data on the timing of reforms and of the creation of the regulatory agencies.

Transport Information on transport institutions and reforms is not systematically generated by any agency. Even though more data are needed to have a more comprenhensive picture of the transport sector, it was possible to collect data on railways policy reform from Janes World Railways (2003-04) and complement it with

This feature class contains road data derived from applying Infra data to a national forest's road GIS data. Infrastructure (Infra) is a collection of applications which house information related to an assets managed by the Forest Service (including but not limited to, Roads, Bridges, Buildings, Water Systems, Waste Water Systems, Dams, Trails, and Recreation Sites). The feature class contains records for all roads that are in each database and are correctly configured. This data would include only existing roads, ones that permit motorized use as well as those that do not. For roads that are legally open for motorized use, it identifies the authorized modes of travel and season of use. This data may not represent a forest's currently published Motor Vehicle Use Map (MVUM). This feature class is derived from the Infra table II_MVUM_ROAD_ALLOW. Access and Travel Management (ATM) data included is pulled from the Allowed Uses tab in the Infra ATM for Roads form. Since this feature class is a current snapshot of Infra data, it is different than the currently published MVUM data and thus is for internal use only, primarily for review of Infra data during development or update of MVUM. This feature class will not be published for public use.

This dataset contains information about Africa's Infrastructure National Data for 1990-2008.

Data from The World Bank.

Notes:

The Africa Infrastructure Country Diagnostic (AICD) has data collection and analysis on the status of the main network infrastructures. The AICD database provides cross-country data on network infrastructure for nine major sectors: air transport, information and communication technologies, irrigation, ports, power, railways, roads, water and sanitation. The indicators are defined as to cover key areas for policy making: affordability, access, pricing as well as institutional, fiscal and financial aspects. The analysis encompasses public expenditure trends, future investment needs and sector performance reviews. It offers users the opportunity to view AICD results, download documents and materials, search databases and perform customized analysis.

This dataset contains the detailed information about the individual asset linear features such as roads and trails that make up Great American Outdoors Act (GAOA) projects. This data can be used together with the project summary data to display general project locations. The data is refreshed on a nightly basis from the US Forest Service database of infrastructure projects which is stewarded by the individual National Forests and Grasslands. For more information about Forest Service GAOA projects visit our website: https://www.fs.usda.gov/managing-land/gaoaMetadata and DownloadsThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.

The global data center infrastructure management market size is expected to reach USD 4.49 Billion by 2030 according to a new study by Polaris Market Research.

Designates boundaries to establish extent of livestock distribution and management within the allotment. This is a published layer created by combining GIS data managed by each National Forest and attribute data stored in the Forest Service Infra database application. This dataset is designed for reporting and analysis and is not used to enter or edit data.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.

The Physical Vulnerability Database for Critical Infrastructure Hazard Risk Assements is a database that contains fragility and vulnerability curves that can be used to evaluate the expected or potential damages to infrastructure assets due to flooding, earthquakes, windstorms and landslides. The database consists of three Excel-spreadsheets:

Table_D1_Summary_CI_Vulnerability_Data: summary table with information on hazard, exposure, and vulnerability characteristics as well as a number of details regarding reliability and reference purposes.

Table_D2_Hazard_Fragility_and_Vulnerability Curves: collection of fragility and vulnerability curves

Table_D3_Costs: cost values that can be used in combination with the curves for the estimation of asset damages

Please consult the following publication for detailed information: Nirandjan, S., Koks, E.E., Menqi, Y., Pant, R., van Ginkel, K.C.H., Aerts, J.C.J.H., Ward, P.J. (2024). Review article: Physical Vulnerability Database for Critical Infrastructure Hazard Risk Assessments – A systematic review and data collection. [Manuscript submitted for publication].

This dataset displays the approximate location of US Forest Service, Great American Outdoors Act (GAOA) projects. The data is refreshed on a nightly basis from the US Forest Service database of infrastructure projects which is stewarded by the individual National Forests and Grasslands. This dataset is a spatial data layer of points representing the approximate or general location where the project takes place. The point location is intended for use in small scale maps to indicate the general location of the projects across the country. The location data is maintained by staff on the individual National Forest or Grassland using the database of record. Because a project can be made up of many assets distributed across a land area, a single project location point will not always reflect the specific location and extent of the work in the project. The project detail data can be used to display the individual assets that make up the project. For more information about Forest Service GAOA projects visit our website: https://www.fs.usda.gov/managing-land/gaoaMetadata and DownloadsThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.

Designates boundaries to establish extent of livestock distribution and management within pastures. This is a published layer created by combining GIS data managed by each National Forest and attribute data stored in the Forest Service Infra database application. This dataset is designed for reporting and analysis and is not used to enter or edit data.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.

The size and share of the market is categorized based on Application (Data centers, Cloud computing, Enterprise IT infrastructure, AI and machine learning) and Product (Servers, Storage systems, Networking equipment, Data processing software, Cloud services) and geographical regions (North America, Europe, Asia-Pacific, South America, and Middle-East and Africa).

Key indicators of broadband adoption, service and infrastructure in New York City. Data Limitations: Data accuracy is limited as of the date of publication and by the methodology and accuracy of the original sources. The City shall not be liable for any costs related to, or in reliance of, the data contained in these datasets.

This dataset contains the detailed information about the individual asset point features such as recreation sites, that make up Great American Outdoors Act (GAOA) projects. This data can be used together with the project summary data to display general project and asset locations. The data is refreshed on a nightly basis from the US Forest Service database of infrastructure projects which is stewarded by the individual National Forests and Grasslands. For more information about Forest Service GAOA projects visit our website: https://www.fs.usda.gov/managing-land/gaoaMetadata and DownloadsThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.

A route feature stores the spatial locations (geography) of the road. These feature classes have an (M) value or measure on their vertices. A route system depicts all roads within or in close proximity to an administrative unit. A road is a motor vehicle travel way over 50 inches wide, unless classified and managed as a trail. This feature is only SPATIAL ROAD DATA, other data (open, closed, jurisdiction, maintenance level) is stored in INFRA. Used to link spatial roads to INFRA data, ROAD NO., BMP, EMP and Calibration. Routed roads are a single spatial line, all have data in INFRA and this data must be attached. Routed roads need to have INFRA data table attached by use of R10 Geospatial Interface (GI) tool and Visualization named Roads with Core Attributes RSW - This creates an output roads layer and adds the following fields from the INFRA database at NITC: name, lanes, service life, system, surface type, jurisdiction, objective maintenance level, operational maintenance level, route status, functional class and primary maintainer. Routed ROADS CAN HAVE OTHER DATA TABLES ATTACHED, (R10 Stream Data Point-RSW, Road Points -RSW, Bridges-RSW, MVUM Roads and Transportation Atlas. A road may be classified or unclassified. Classified roads are roads within the National Forest System lands planned and managed for motor vehicle access including State roads, county roads, private roads, permitted roads, and Forest Service roads. Unclassified roads are roads not intended to be a part of nor managed as a part of the forests transportation system, such as temporary roads, and unplanned, unengineered, unauthorized off-road vehicle tracks and abandoned travel ways. Route measurements and route directions must correspond to those stored in the INFRA Oracle table RTE_BASICS. Associated National Application: INFRA Travel Routes. IWeb Infra Roads webpage http://basenet.fs.fed.us/support/help/roads/. All routed roads are required to have data in INFRA and all roads having data in INFRA are required to be routed.

Designates boundaries to establish extent of distribution and management of Wild Horse and Burro territories. This is a published layer created by combining GIS data managed by each National Forest and attribute data stored in the Forest Service Infra database application. This dataset is designed for reporting and analysis and is not used to enter or edit data.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.

In 2024, Europe had the highest number of Oracle Cloud Infrastructure zones with 15 availability zones (AZs), closely followed up by North America with 12 AZs. Oracle Cloud Infrastructure operates a total of 50 data centers worldwide.

Northern Virginia is by far the largest data center market in the United States when measured by total inventory. The region had capacity of around 2,600 megawatts in the first half of 2024, a significant increase on the previous year. The Dallas/Ft. Worth region had the second-highest capacity, followed by Chicago. Northern Virginia could face a slowdown in construction Situated close to major east coast urban centers, the Northern Virginia region is considered a key hyperscale data center hub. The region had a reported 1,540 megawatts of data center capacity under construction as of the second half of 2023, far more than any other U.S. market. However, future expansion may be hindered by shifting local infrastructure conditions, with the growing impact of large-scale facilities leading local decision makers to reassess planning legislation. Rental rates on the rise The average monthly rental rate for data center capacity in primary U.S. markets surged to over $174 per kilowatt in 2024. This is partially due to increased demand, with digital transformation driving the adoption of cloud services, and with the adoption of data intensive artificial intelligence (AI) applications. However, data centers operators are also experiencing difficulties in data center construction, as rising utilities costs and supply chain continue to apply pressure.

Responding to a 2023 survey, a third of IT and data center managers across the globe said that their digital infrastructure management teams were very concerned by the need to improve energy performance for facilities equipment. Power usage effectiveness (PUE) figures suggest that energy efficiency gains in the data center industry have levelled off in recent years, with further improvements requiring significant capital investment.

Internet infrastructure. Provided by the Office of Digital Inclusion

Groundwater wells are critical infrastructure that enable the monitoring, extraction, and use of groundwater, which has important implications for the environment, water security, and economic development. Despite the importance of wells, a unified database collecting and standardizing information on the characteristics and locations of these wells across the United States has been lacking. To bridge this gap, we have created a comprehensive database of groundwater well records collected from state and federal agencies, which we call the United States Groundwater Well Database (USGWD). Presented in both tabular form and as vector points, the USGWD comprises over 14.2 million well records with attributes such as well purpose, location, depth, and capacity for wells constructed as far back as 1763 to 2023. Rigorous cross-verification steps have been applied to ensure the accuracy of the data. The USGWD stands as a valuable tool for improving our understanding of how groundwater is accessed and managed across various regions and sectors within the United States.

The average monthly rental rate for data center capacity in primary markets in the United States rose sharply to over 174 U.S. dollars per kilowatt in the first half of 2024. The surge in rental rates reflects the increasing pressure on data center capacity due to rising demand and supply chain constraints. Northern Virginia leads the U.S. data center market As of the second half of 2023, the Northern Virginia region boasted the lowest data center vacancy rate among major markets in North America at just 0.8 percent. Spread across Loudon, Fairfax, Fauquier, and Prince William Counties, the region has long been a leading data center hub, with hyperscale operators attracted by favorable local infrastructure conditions and proximity to major metropolitan areas. Challenges and opportunities in data center construction The second half of 2023 saw 1,540 megawatts of data center capacity under construction in Northern Virginia. However, the market could face limitations in future expansion, with the growing impact on local resources prompting local officials to rethink approaches to data center planning processes. Meanwhile, the Portland and Eastern Oregon region has emerged as an important west coast hub. Sometimes referred to as the Silicon Forest, the region has a reported 542 megawatts under construction as of the second half of 2023.