A file containing the location and character of cycle lanes within DLR. Data provided by Dún Laoghaire-Rathdown County Council. Please note this data is for information purposes only and may not be an exact representation of the infrastructure. Changes and upgrades occurring since then may not be represented.

Data Center Life Cycle Services Market Outlook

The global data center life cycle services market size was valued at approximately USD 5.8 billion in 2023 and is projected to reach an impressive USD 11.2 billion by 2032, reflecting a robust compound annual growth rate (CAGR) of 7.4% during the forecast period. This growth is predominantly driven by the increasing reliance on data centers in various industries, necessitating comprehensive life cycle services to ensure optimal performance, cost-effectiveness, and sustainability. The demand for cloud services, advancements in IT infrastructure, and the rapid digital transformation of businesses globally are pivotal elements propelling this market forward. As organizations strive for enhanced operational efficiency, the adoption of data center life cycle services becomes a strategic imperative, ensuring that data centers are planned, built, managed, and eventually decommissioned effectively.

One of the significant growth factors for the data center life cycle services market is the escalating volume of data generation across industries. With the proliferation of IoT devices, big data analytics, and the increasing use of artificial intelligence and machine learning, data centers are becoming central to business operations. This surge in data necessitates advanced data center infrastructure, which in turn fuels demand for life cycle services. These services provide a holistic approach to managing data centers from inception to retirement, ensuring that they remain efficient, secure, and aligned with organizational goals. Additionally, the growing emphasis on sustainability and energy efficiency in data centers is prompting businesses to adopt life cycle services to reduce carbon footprints and operational costs.

Another critical growth driver is the global shift towards cloud computing, which has transformed the data center landscape. As more organizations migrate to cloud platforms, there is a heightened need for effective data center life cycle services to manage this transition. These services are crucial in facilitating seamless integration, optimizing existing infrastructure, and ensuring data security and compliance during and after the migration process. Furthermore, the trend of edge computing, which involves processing data closer to its source, is creating new opportunities for data center life cycle services. As edge data centers proliferate, they require specialized services to manage their unique operational challenges and integration with larger cloud ecosystems.

Technological advancements and innovations in data center infrastructure also contribute to the growth of the life cycle services market. The advent of technologies such as software-defined data centers (SDDCs), hyper-converged infrastructure, and advanced cooling solutions is reshaping the way data centers are designed and managed. These technologies necessitate specialized knowledge and expertise, driving demand for comprehensive life cycle services that can support complex infrastructure and ensure seamless operation. Moreover, the need for data center modernization, driven by aging infrastructure and evolving business needs, is compelling organizations to seek life cycle services that can facilitate upgrades and modernization efforts without disrupting operations.

Managed Data Center Service is becoming increasingly important as organizations strive to optimize their IT operations while focusing on core business activities. By outsourcing data center management to specialized service providers, companies can benefit from expert handling of their infrastructure, ensuring high availability, security, and performance. These services encompass a wide range of activities, including monitoring, maintenance, and support, allowing businesses to leverage advanced technologies without the need for significant in-house resources. As the complexity of data center environments grows, Managed Data Center Service offers a strategic solution to manage these challenges efficiently, enabling organizations to scale their operations seamlessly and adapt to evolving technological demands.

Regionally, North America holds a significant share of the data center life cycle services market, driven by the high concentration of data centers and cloud service providers in the region. The United States, in particular, is a critical player, with major investments in data center infrastructure and a robust technology ecosystem. Europe follows closely, with countries like Germany, the UK, and the Netherlands leading in data cente

Cycle average and aggregation of river reach pass data within predefined hydrological basins. Basin for each cycle. Available in Shapefile file format.

(i) The CPM LCA Database is developed within the Swedish Life Cycle Center, and is a result of the continuous work to establish transparent and quality reviewed LCA data. The Swedish Life Cycle Center (founded in 1996 and formerly called CPM) is a center of excellence for the advance of life cycle thinking in industry and other parts of society through research, implementation, communication and exchange of experience on life cycle management. The mission is to improve the environmental performance of products and services, as a natural part of sustainable development. The Center has been instrumental for the development and adoption the life cycle perspective in Swedish companies and has made important contributions to international standardization in the life cycle field. More information about the Center, see www.lifecyclecenter.se. The Swedish Life Cycle Center owns the CPM LCA Database, which is today maintained by Environmental Systems Analysis at the Department of Energy and Environment at Chalmers University of Technology. (ii) All LCI datasets can be viewed in in three formats: the SPINE format, a format compatible with the ISO/TS 14048 LCA data documentation format criteria, and in the ILCD format. Three impact assessment models: EPS, EDIP, and ECO-Indicator, can be viewed in the IA98 format. Also a simple IA calculator is provided where the environmental impact of each LCI dataset can be calculated based on the three different IA methods. (iii) unknown (iv) unknown

The Total Product Life Cycle (TPLC) database integrates premarket and postmarket data about medical devices. It includes information pulled from CDRH databases including Premarket Approvals (PMA), Premarket Notifications (510[k]), Adverse Events, and Recalls. You can search the TPLC database by device name or procode to receive a full report about a particular product line.

This repository contains the collected resources submitted to and created by the NIST Collaborative Research Cycle (CRC) Data and Metrics Archive. The NIST Collaborative Research Cycle (CRC) is an ongoing effort to benchmark, compare, and investigate deidentification technologies. The program asks the research community to deidentify a compact and interesting dataset called the NIST Diverse Communities Data Excerpts, demographic data from communities across the U.S. sourced from the American Community Survey. This repository contains all of the submitted deidentified data instances each accompanied by a detailed abstract describing how the deidentified data were generated. We conduct an extensive standardized evaluation of each deidentified instance using a host of fidelity, utility, and privacy metrics, using out tool, SDNist. We?ve packaged the data, abstracts, and evaluation results into a human- and machine-readable archive.

London’s Cycling Infrastructure Database (CID) is the world’s largest and most comprehensive database of cycling infrastructure, containing comprehensive details of cycling infrastructure in the Capital. The CID is intended to address barriers to cycling by providing Londoners with clear and accurate information about cycling infrastructure, helping them plan cycle journeys with confidence. The CID is a core part of our Cycling Action Plan , which sets out how TfL, boroughs and others will work together to make London the world’s best big city for cycling.

To create the database, TfL have surveyed every street in every London borough to collect information on over 240,000 pieces of infrastructure, covering an area of 1,595 square kilometres.

The database also contains 480,000 photographs of cycling infrastructure, allowing users to see exactly what can be found on street. For example, cycle parking users will be able to see what type of parking is available. TfL collected data of 146,000 cycle parking spaces across London, as well as gathering information on 2,000km of cycle routes and 58,000 wayfinding signs.

An update to TfL's own Journey Planner means that people using the planner for cycle journeys can now see the nearest and most convenient place to park for every journey. Third party developers will be able to use the data for their own journey planning tools, which will make it simpler for Londoners to plan cycle journeys using their preferred apps. We’re excited to see how developers can use the data to help make cycling in the Capital easier, and to kick-start this we will invite app developers to a hackathon this autumn to see how this data can be maximised to benefit people cycling.

As well as making it easier for Londoners to plan cycle journeys, the database will help TfL and boroughs to plan future cycling investment. For example, the database has already been used to develop TfL's Cycle Parking Implementation Plan, which sets out how TfL will work with partners across the capital to deliver 50,000 cycle parking spaces over the next six years where they are needed most, to meet the growing demand for safe places to park cycles.

The following types of asset are included in the database:

• Cycle lanes and tracks – including whether they are segregated or painted lanes
• Cycle parking, including the type and capacity of parking
• Signalised crossings for cycles
• Restricted route - Modal filters and traffic gates which allow cycles to pass but restrict car traffic
• Traffic calming, including the location of all speed humps in Greater London
• Advanced stop lines – boxes at junctions for people cycling
• Signals - early-release signals at junctions
• Signage - Signed cycle routes and other wayfinding
• Restricted Points – points where people cycling will have to dismount Paths through parks and other green spaces that can, and cannot, be cycled on

This dataset contains timeseries data (time, current, voltage, temperature) of a drive cycle aging test of 28 18650 high energy NCA/C+Si round cells. The aging test was conducted with all cells at the same aging condition at room temperature. The cells were cycled individually but with the same profile. They were charged with a CCCV regime and discharged using a recorded drive cycle profile. Regular check-ups every 30 cycles are also included in the data.

The Rapid Update Cycle analysis/model system at a 20-km horizontal resolution (RUC20) provides short-range numerical weather guidance for general forecasting, as well as for the special short-term needs of aviation and severe-weather forecasting. This data set consists of 60 meteorological and soil parameters at 50 computational levels.

Cycle Lanes DLR. Published by Dún Laoghaire-Rathdown County Council. Available under the license cc-by (CC-BY-4.0).A file containing the location and character of cycle lanes within DLR. Data provided by Dún Laoghaire-Rathdown County Council. Please note this data is for information purposes only and may not be an exact representation of the infrastructure. Changes and upgrades occurring since then may not be represented.

...

Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) was developed by the Centre National d'Etudes Spatiales (CNES) with cooperation from other French government agencies. The system was developed to provide precise orbit determination and high accuracy location of ground beacons for point positioning. DORIS is a dual-frequency Doppler system that has been included as an experiment on various space missions such as TOPEX/Poseidon, SPOT-2, -3, -4, and -5, Envisat, and Jason satellites. Unlike many other navigation systems, DORIS is based on an uplink device. The receivers are on board the satellite with the transmitters are on the ground. This creates a centralized system in which the complete set of observations is downloaded by the satellite to the ground center, from where they are distributed after editing and processing. An accurate measurement is made of the Doppler shift on radiofrequency signals emitted by the ground beacons and received on the spacecraft.

Dixie Valley production data for January 2014, for a DOE Report. Used to demonstrate the techno-economic feasibility of utilizing the available unused heat to generate additional electric power from a binary power plant. *Note - This data is incomplete. See link below "Monthly Production Data September 2014" for more complete data set.

Additional data for paper "Treating the End of the Data Life Cycle as a First-Class Citizen in Data Engineering".

This work is primarily being undertaken through the development of eleven regional long term cycle network (LTCN) strategies, also known as regional 2050 cycling strategies. These strategies seek to identify gaps in existing cycling networks, plan for future growth corridors, and produce strategic and operational plans for identified regional centres and surrounding areas. Each strategy is developed in partnership with respective local government authorities and aims to ensure State and Local Governments continue to work together towards the delivery of a continuous cycling network providing additional transport options, recreational opportunities and support for tourism and commercial activity.

Additional data for paper "Structuring the End of the Data Life Cycle".

This dataset contains cycle infrastructure in the Greater Dublin Area (GDA). Data stems from work undertaken on behalf of the NTA to: re-categorise the 2013 street survey with infrastructure types: segregated cycle track, bus lane with cycle lane, etc. include links inputted by the NTA in the course of developing and maintaining the journey planner include NTA funded completed cycle infrastructure 2013-2021 The Zipped files may be downloaded and opened with software such as QGIS and Google Earth. The categorisation methodology and attributes are provided as attachments. See the attributes document for a description of the fields. The original dataset first published in 2020 with data provided by the NTA here: https://www.nationaltransport.ie/bike-life-2019-dublin-metropolitan-area/ This has been updated with data provided by the NTA in November 2021. To convert these files to other formats, or different projects, please see the wiki here: https://wiki.data.smartdublin.ie/doku.php?id=public:converting_geolocated_data

Description: This dataset contains historical economic data spanning from 1871 to 2024, used in Jaouad Karfali’s research on Economic Cycle Analysis with Numerical Time Cycles. The study aims to improve economic forecasting accuracy through the 9-year cycle model, which demonstrates superior predictive capabilities compared to traditional economic indicators.

Dataset Contents: The dataset includes a comprehensive range of economic indicators used in the research, such as:

USGDP_1871-2024.csv – U.S. Gross Domestic Product (GDP) data. USCPI_cleaned.csv – U.S. Consumer Price Index (CPI), cleaned and processed. USWAGE_1871-2024.csv – U.S. average wages data. EXCHANGEGLOBAL_cleaned.csv – Global exchange rates for the U.S. dollar. EXCHANGEPOUND_cleaned.csv – U.S. dollar to British pound exchange rates. INTERESTRATE_1871-2024.csv – U.S. interest rate data. UNRATE.csv – U.S. unemployment rate statistics. POPTOTUSA647NWDB.csv – U.S. total population data. Significance of the Data: This dataset serves as a foundation for a robust economic analysis of the U.S. economy over multiple decades. It was instrumental in testing the 9-year economic cycle model, which demonstrated an 85% accuracy rate in economic forecasting when compared to traditional models such as ARIMA and VAR.

Applications:

Economic Forecasting: Predicts a 1.5% decline in GDP in 2025, followed by a gradual recovery between 2026-2034. Economic Stability Analysis: Used for comparing forecasts with estimates from institutions like the IMF and World Bank. Academic and Institutional Research: Supports studies in economic cycles and long-term forecasting. Source & Further Information: For more details on the methodology and research findings, refer to the full paper published on SSRN:

https://ssrn.com/author=7429208 https://orcid.org/0009-0002-9626-7289

• Jaouad Karfali

Data tables for Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis - 2022: Annual Supplement to NIST Handbook 13Starting in the 2022 Annual Supplement to Handbook 135, the data tables within the text document has been extracted and provided in a supplemental spreadsheet. The reasons for creating a separate data file is to (1) make the text document smaller and easier to navigate, (2) provide the data in a format that is more accessible to a user, particularly those that want to incorporate the data tables into their own calculations or tools, and (3) streamline the process for the annual release of the data.There are numerous data sources used in developing these data tables, including EIA, OMB, and Federal Reserve. Process is discussed in Annual Supplement to Handbook 135.

ATTENTION: As of 09/08/2023, the Bicycle counting - Counter data data set is subject to change. malfunctions which may alter the veracity of the information transmitted. Our technical teams are mobilized to resolve the problem as quickly as possible.

Dataset of hourly bicycle counts by counter and location of counting sites in J- 1 in 13 rolling months

< font face="Arial, sans-serif">A counting site can be equipped with one meter in the case of a unidirectional cycling facility or two counters in the case of a bi-directional cycling facility.

The City of Paris has been deploying permanent bicycle counters for several years evaluate the development of cycling.

This dataset presents all hourly bicycle counts on 13 rolling months (D-13 months), updated to D-1.

The counters are located on cycle paths and in certain bus lanes open to bicycles. Other vehicles (e.g. scooters, etc.) are not counted.

This dataset is uploaded daily to our API partner Eco Compteur.

As the Eco Counter API does not natively provide counting by direction, processing by aggregation was carried out for </ font>rebuild.

You will find here:< /p>

- Counter ID

- Counter name

- < /font>Count site identifier

- < /span>Counting site name

- Time counter

- Count date and time

- Date installation of the counting site

- Link to photo of the counting site

- Geographic coordinates</ p>

A join has been carried out with the dataset Bike counting - Counters in order to retrieve all the information < /span>descriptions of the metering site and its meters, including the location and date of installation.

< span style="font-family: Arial, sans-serif; font-size: medium;">

WARNING: The number of counters changes over time

The number of counters changes as cycling developments progress. Some counters can be deactivated to work or occasionally suffer a breakdown.

More cycling information on Paris.fr

Access to the Cycle route network

Sensors from the following sites:

- 69 Boulevard Ornano (temporary)

- 69 Boulevard Ornano

- 74 Boulevard Ornano

- 100 rue La Fayette

- 105 rue La Fayette

- 254 rue de Vaugirard

<font

re-categorise the 2013 street survey with infrastructure types: segregated cycle track, bus lane with cycle lane, etc. include links inputted by the NTA in the course of developing and maintaining the journey planner include NTA funded completed cycle infrastructure 2013-2021 The Zipped files may be downloaded and opened with software such as QGIS and Google Earth. The categorisation methodology and attributes are provided as attachments. See the attributes document for a description of the fields. The original dataset first published in 2020 with data provided by the NTA here: https://www.nationaltransport.ie/bike-life-2019-dublin-metropolitan-area/ This has been updated with data provided by the NTA in November 2021. To convert these files to other formats, or different projects, please see the wiki here: https://wiki.data.smartdublin.ie/doku.php?id=public:converting_geolocated_data