fMRI raw dataset in BIDS format.

Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior

See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151

Construction Bids 13-14

List of currently available BIDS Apps.

Description: This data set contains non-confidential information on approved Non-Competitively Bid (NCB) contracts, Special Category NCB Requests (SCR), and Limited-to-Brand Requests (LTB) approved for $1 million or more. This dataset is limited to requests made to (and approved by) the California Department of General Services (DGS). It does not contain requests made to (or approved by) the California Department of Technology (CDT).

For definitions of key terms, please see the attached Data Dictionary.

If you have any questions regarding a specific NCB, SCR, or LTB, please contact the department or agency identified in the “Requesting Organization” column. For any other questions, please contact PDNCB@dgs.ca.gov.

This folder contains data organised in BIDS format to test BIDS Manager-Pipeline (https://github.com/Dynamap/BIDS_Manager/tree/dev).

The "Competitions, Bids & Dispatch Data" data table contains information of the competitions facilitated, bids received and dispatch instructions from the DPS (Piclo) platform. The table gives the following information:MWH tendered per licence areaMWH contracted per licence areaMWH dispatched per licence area For additional information on column definitions, please click the Dataset schema link below. DisclaimerWhilst all reasonable care has been taken in the preparation of this data, SP Energy Networks does not accept any responsibility or liability for the accuracy or completeness of this data, and is not liable for any loss that may be attributed to the use of this data. For the avoidance of doubt, this data should not be used for safety critical purposes without the use of appropriate safety checks and services e.g. LineSearchBeforeUDig etc. Please raise any potential issues with the data which you have received via the feedback form available at the Feedback tab above (must be logged in to see this).Data TriageAs part of our commitment to enhancing the transparency, and accessibility of the data we share, we publish the results of our Data Triage process.Our Data Triage documentation includes our Risk Assessments; detailing any controls we have implemented to prevent exposure of sensitive information. Click here to access the Data Triage documentation for the Flexibility Bids, Competitions and Registered Assets dataset. To access our full suite of Data Triage documentation, visit the SP Energy Networks Data & Information. Download dataset metadata (JSON)

This a sample BIDS dataset created for continous integration of the Connectome Mapper 3.

This dataset was acquired at the Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland, using a 3T Siemens Prisma MRI scanner.

It adopts the sub-/ses- structure and contains one T1w anatomical MRI (MPRAGE), one diffusion MRI (DSI) , and one resting-state functional MRI as well as additional Freesurfer derivatives.

It is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. (See https://creativecommons.org/licenses/by/4.0/ for more details)

Changes

Version 2.1

Fix issues with the resampling of the DWI and rfMRI scans with Slicer. They were regenerated in version 2.1 with mri_convert to better handle the 4th dimension.

For the sake of the size of the dataset, only 100 frames in the fMRI recording has been kept and the sourcedata/ folder has been dropped but can be easily be retrieved in the previous 2.0 version (https://zenodo.org/record/5788803#.Yb2-giYo8bV).

Version 2.0

For testing purposes, scans found in the root sub-01 directory have been downsampled to 2x2x2 mm3 (MPRAGE), and to 3x3x3 mm3 (DSI and rfMRI) with the ResampleScalarVolume module of Slicer 4.6.2. A copy of the output produced in the terminal by Slicer has been created in the code/ directory.

Original data have been placed in sourcedata/ in concordance to BIDS.

The original MEG dataset was acquired from all 306 sensors (204 gradiometers and 102 magnetometers) during two different sessions for each participant and recorded as .fif files. As each session consists of two data files due to the session break, for better handling of the data, we have merged these files to create one single '.fif' file for each session. Thus, there are two raw '.fif' data files for each participant (i.e. one for each session). It is worth to be noted the data is available in two data formats i.e. MEG-BIDS format '.fif' and MATLAB compatible '.mat' file at the repository. The data directory for MEG-BIDS is defined, where only one subject data structure is illustrated to avoid repetition. The folder named 'MEG_BIDS' contains two files named 'dataset_description.json' and participant.tsv'. Further, there are 17 sub-folders (one for each participant data), each having scan file_scan.tsv' and a sub-folder named meg'. Eachmeg' folder contains five files i.e. _coordsystem.json',_channels.tsv',_events.tsv',_meg.fif', and `_meg.json'.

The SLO_BIDDING_DATA dataset includes data regarding tendered bids, accepted bids and price of capacity bids (monthly aggregates). It is intended for market players and system operators to follow the prices on the market and amount of purchased flexibility.

Two data sets in the CIM XML format are available with information about bidding for DSOs. One document is covering the process type "congestion management", the other for "voltage control". Due to CGMES being TSO oriented, some attributes are missing to fully describe DSO processes. Therefore we had to extend the attribute "processType" to cover DSO needs.

Addition information about the Slovenian demo is available in the OneNet 10.4 deliverable (OneNet_D10.4_V1.0.pdf (onenet-project.eu)).

XSD is compliant with ReserveBid_Document defined by ENTSO-E (Reserve bid document UML model and schema (entsoe.eu)).

This dates set represents BIDS in the Borough of Brooklyn. The data is collected to keep track of the BIDS, which includes there leadership, address, contact, appointees and liaisons assigned to the BID.

Construction Bidding Cost Database Market Outlook

According to our latest research, the global Construction Bidding Cost Database market size reached USD 1.98 billion in 2024. The market is exhibiting robust momentum, propelled by the increasing digitization of construction processes and a heightened demand for cost transparency and efficiency. With a projected compound annual growth rate (CAGR) of 11.7% from 2025 to 2033, the market is forecasted to attain a value of USD 5.51 billion by 2033. This impressive growth trajectory is primarily driven by the widespread adoption of advanced software solutions in construction project management, a growing emphasis on minimizing bid errors, and the rising need for real-time data analytics to support accurate project estimation and cost control.

One of the primary growth factors for the Construction Bidding Cost Database market is the increasing complexity of construction projects globally. As projects become larger and more intricate, stakeholders demand precise cost estimation and bidding processes to ensure profitability and competitiveness. The integration of artificial intelligence and machine learning within construction bidding platforms has further enhanced accuracy and streamlined workflows. These technologies enable predictive analytics, automate repetitive tasks, and reduce human errors, thereby improving overall project outcomes. The need for robust cost databases is underscored by the rising frequency of design changes and scope modifications, which necessitate agile and responsive cost management solutions throughout the project lifecycle.

Another significant driver is the regulatory environment and the growing focus on compliance and risk management in construction. Governments and industry bodies are increasingly mandating transparent bidding processes and accurate cost reporting to mitigate risks of fraud, misallocation of funds, and project delays. The adoption of Construction Bidding Cost Database solutions enables stakeholders to maintain comprehensive audit trails, adhere to regulatory standards, and facilitate more effective communication among project participants. This is particularly evident in public infrastructure projects, where transparency and accountability are paramount. As a result, the market is witnessing accelerated adoption across both public and private sectors, further fueling its expansion.

The proliferation of cloud-based solutions is another key factor contributing to market growth. Cloud deployment offers unparalleled accessibility, scalability, and integration capabilities, allowing construction firms to manage bids and cost data across multiple locations and projects seamlessly. This has proven invaluable amidst the ongoing digital transformation of the construction industry, as organizations seek to leverage real-time data sharing and collaboration tools. Additionally, the shift towards integrated project delivery models and the use of Building Information Modeling (BIM) are reinforcing the need for comprehensive cost databases, enabling more accurate forecasting, budgeting, and resource allocation.

In the realm of construction project management, Construction Takeoff Software plays a pivotal role by automating the quantification process of materials and labor needed for a project. This software significantly reduces the time and effort required for manual takeoffs, thereby enhancing accuracy and efficiency. By integrating with construction bidding cost databases, takeoff software ensures that estimators have access to real-time data, facilitating more precise cost estimations and competitive bidding. The ability to quickly adjust to design changes and scope modifications is another advantage, as it allows construction firms to remain agile and responsive to client needs. As the industry continues to embrace digital transformation, the adoption of construction takeoff software is expected to rise, further driving the demand for comprehensive cost database solutions.

From a regional perspective, North America currently dominates the Construction Bidding Cost Database market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The United States leads in terms of technology adoption and investment in digital construction solutions, while the Asia Pacific region is experiencing the fastest growth, driven by rapid urbaniza

This is historical data. For current bids data, please see https://data.cambridgema.gov/Purchasing/Bid-list/gp98-ja4f/about_data

Bids for "Invitation for Bid," "Regular Request for Proposal," "Design Services Request for Proposal" and "Informal" bids.

Construction bids are available here: https://data.cambridgema.gov/Purchasing/Current-Bid-List-Construction/pmii-ykdf/about_data

For more information see: https://www.cambridgema.gov/bids

This folder contains data from a fictional participant that you can use to test BIDS Manager (https://github.com/Dynamap/BIDS_Manager).

Longitudinal study of pre-symptomatic Alzheimer's Disease

This report contains data since December 2019 and is refreshed once per day. Individual anonymized available decremental volumes and corresponding prices based on automatic Frequency Restoration Reserve (aFRR) and manual Frequency Restoration Reserve (mFRR) energy bids and nominations both day-ahead and intraday - submitted by Balance responsible Parties (BRPs) and Balance Service Providers (BSPs), taking into account the known technical and contractual constraints.This report is named Decrement ARC Merit Order in Data Download in Elia.be.This dataset contains data until 21/05/2024 (before MARI local go-live).

Financial values ​​of electronic equipment bids for each year

BIDS Phenotype Segregation Example COPY OF "The NIMH Healthy Research Volunteer Dataset" (ds003982)

Modality-agnostic files were copied over and the CHANGES file was updated. Data was segregated using:

python phenotype.py segregate subject -i ds003982 -o segregated_subject

phenotype.py came from the GitHub repository: https://github.com/ericearl/bids-phenotype

THE ORIGINAL DATASET ds003982 README FOLLOWS

A comprehensive clinical, MRI, and MEG collection characterizing healthy research volunteers collected at the National Institute of Mental Health (NIMH) Intramural Research Program (IRP) in Bethesda, Maryland using medical and mental health assessments, diagnostic and dimensional measures of mental health, cognitive and neuropsychological functioning, structural and functional magnetic resonance imaging (MRI), along with diffusion tensor imaging (DTI), and a comprehensive magnetoencephalography battery (MEG).

In addition, blood samples are currently banked for future genetic analysis. All data collected in this protocol are broadly shared in the OpenNeuro repository, in the Brain Imaging Data Structure (BIDS) format. In addition, blood samples of healthy volunteers are banked for future analyses. All data collected in this protocol are broadly shared here, in the Brain Imaging Data Structure (BIDS) format. In addition, task paradigms and basic pre-processing scripts are shared on GitHub. This dataset is unique in its depth of characterization of a healthy population in terms of brain health and will contribute to a wide array of secondary investigations of non-clinical and clinical research questions.

This dataset is licensed under the Creative Commons Zero (CC0) v1.0 License.

Recruitment

Inclusion criteria for the study require that participants are adults at or over 18 years of age in good health with the ability to read, speak, understand, and provide consent in English. All participants provided electronic informed consent for online screening and written informed consent for all other procedures. Exclusion criteria include:

• A history of significant or unstable medical or mental health condition requiring treatment
• Current self-injury, suicidal thoughts or behavior
• Current illicit drug use by history or urine drug screen
• Abnormal physical exam or laboratory result at the time of in-person assessment
• Less than an 8th grade education or IQ below 70
• Current employees, or first-degree relatives of NIMH employees

Study participants are recruited through direct mailings, bulletin boards and listservs, outreach exhibits, print advertisements, and electronic media.

Clinical Measures

All potential volunteers first visit the study website (https://nimhresearchvolunteer.ctss.nih.gov), check a box indicating consent, and complete preliminary self-report screening questionnaires. The study website is HIPAA compliant and therefore does not collect PII ; instead, participants are instructed to contact the study team to provide their identity and contact information. The questionnaires include demographics, clinical history including medications, disability status (WHODAS 2.0), mental health symptoms (modified DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure), substance use survey (DSM-5 Level 2), alcohol use (AUDIT), handedness (Edinburgh Handedness Inventory), and perceived health ratings. At the conclusion of the questionnaires, participants are again prompted to send an email to the study team. Survey results, supplemented by NIH medical records review (if present), are reviewed by the study team, who determine if the participant is likely eligible for the protocol. These participants are then scheduled for an in-person assessment. Follow-up phone screenings were also used to determine if participants were eligible for in-person screening.

In-person Assessments

At this visit, participants undergo a comprehensive clinical evaluation to determine final eligibility to be included as a healthy research volunteer. The mental health evaluation consists of a psychiatric diagnostic interview (Structured Clinical Interview for DSM-5 Disorders (SCID-5), along with self-report surveys of mood (Beck Depression Inventory-II (BD-II) and anxiety (Beck Anxiety Inventory, BAI) symptoms. An intelligence quotient (IQ) estimation is determined with the Kaufman Brief Intelligence Test, Second Edition (KBIT-2). The KBIT-2 is a brief (20-30 minute) assessment of intellectual functioning administered by a trained examiner. There are three subtests, including verbal knowledge, riddles, and matrices.

Medical Evaluation

Medical evaluation includes medical history elicitation and systematic review of systems. Biological and physiological measures include vital signs (blood pressure, pulse), as well as weight, height, and BMI. Blood and urine samples are taken and a complete blood count, acute care panel, hepatic panel, thyroid stimulating hormone, viral markers (HCV, HBV, HIV), C-reactive protein, creatine kinase, urine drug screen and urine pregnancy tests are performed. In addition, blood samples that can be used for future genomic analysis, development of lymphoblastic cell lines or other biomarker measures are collected and banked with the NIMH Repository and Genomics Resource (Infinity BiologiX). The Family Interview for Genetic Studies (FIGS) was later added to the assessment in order to provide better pedigree information; the Adverse Childhood Events (ACEs) survey was also added to better characterize potential risk factors for psychopathology. The entirety of the in-person assessment not only collects information relevant for eligibility determination, but it also provides a comprehensive set of standardized clinical measures of volunteer health that can be used for secondary research.

MRI Scan

Participants are given the option to consent for a magnetic resonance imaging (MRI) scan, which can serve as a baseline clinical scan to determine normative brain structure, and also as a research scan with the addition of functional sequences (resting state and diffusion tensor imaging). The MR protocol used was initially based on the ADNI-3 basic protocol, but was later modified to include portions of the ABCD protocol in the following manner:

1. The T1 scan from ADNI3 was replaced by the T1 scan from the ABCD protocol.
2. The Axial T2 2D FLAIR acquisition from ADNI2 was added, and fat saturation turned on.
3. Fat saturation was turned on for the pCASL acquisition.
4. The high-resolution in-plane hippocampal 2D T2 scan was removed and replaced with the whole brain 3D T2 scan from the ABCD protocol (which is resolution and bandwidth matched to the T1 scan).
5. The slice-select gradient reversal method was turned on for DTI acquisition, and reconstruction interpolation turned off.
6. Scans for distortion correction were added (reversed-blip scans for DTI and resting state scans).
7. The 3D FLAIR sequence was made optional and replaced by one where the prescription and other acquisition parameters provide resolution and geometric correspondence between the T1 and T2 scans.

At the time of the MRI scan, volunteers are administered a subset of tasks from the NIH Toolbox Cognition Battery. The four tasks include:

1. Flanker inhibitory control and attention task assesses the constructs of attention and executive functioning.
2. Executive functioning is also assessed using a dimensional change card sort test.
3. Episodic memory is evaluated using a picture sequence memory test.
4. Working memory is evaluated using a list sorting test.

MEG

An optional MEG study was added to the protocol approximately one year after the study was initiated, thus there are relatively fewer MEG recordings in comparison to the MRI dataset. MEG studies are performed on a 275 channel CTF MEG system (CTF MEG, Coquiltam BC, Canada). The position of the head was localized at the beginning and end of each recording using three fiducial coils. These coils were placed 1.5 cm above the nasion, and at each ear, 1.5 cm from the tragus on a line between the tragus and the outer canthus of the eye. For 48 participants (as of 2/1/2022), photographs were taken of the three coils and used to mark the points on the T1 weighted structural MRI scan for co-registration. For the remainder of the participants (n=16 as of 2/1/2022), a Brainsight neuronavigation system (Rogue Research, Montréal, Québec, Canada) was used to coregister the MRI and fiducial localizer coils in realtime prior to MEG data acquisition.

Specific Measures within Dataset

Online and In-person behavioral and clinical measures, along with the corresponding phenotype file name, sorted first by measurement location and then by file name.

Bids received in response to Competitive Sealed Bid (CSB) solicitations are opened publicly, at the time, date, and place designated in the Invitation for Bid (IFB). The name of each bidder, the bid price, and such other information as is deemed appropriate is read aloud or otherwise made available.

The bids are tabulated and made available for public inspection. The opened bids are made available for public inspection at a reasonable time after bid opening but in any case before vendor selection, except to the extent the bidder designates trade secrets or other proprietary data to be confidential.

BIDS Phenotype External Dataset Example COPY OF "The NIMH Healthy Research Volunteer Dataset" (ds003982)

Modality-agnostic files were copied over and the CHANGES file was updated.

THE ORIGINAL DATASET ds003982 README FOLLOWS

A comprehensive clinical, MRI, and MEG collection characterizing healthy research volunteers collected at the National Institute of Mental Health (NIMH) Intramural Research Program (IRP) in Bethesda, Maryland using medical and mental health assessments, diagnostic and dimensional measures of mental health, cognitive and neuropsychological functioning, structural and functional magnetic resonance imaging (MRI), along with diffusion tensor imaging (DTI), and a comprehensive magnetoencephalography battery (MEG).

In addition, blood samples are currently banked for future genetic analysis. All data collected in this protocol are broadly shared in the OpenNeuro repository, in the Brain Imaging Data Structure (BIDS) format. In addition, blood samples of healthy volunteers are banked for future analyses. All data collected in this protocol are broadly shared here, in the Brain Imaging Data Structure (BIDS) format. In addition, task paradigms and basic pre-processing scripts are shared on GitHub. This dataset is unique in its depth of characterization of a healthy population in terms of brain health and will contribute to a wide array of secondary investigations of non-clinical and clinical research questions.

This dataset is licensed under the Creative Commons Zero (CC0) v1.0 License.

Recruitment

Inclusion criteria for the study require that participants are adults at or over 18 years of age in good health with the ability to read, speak, understand, and provide consent in English. All participants provided electronic informed consent for online screening and written informed consent for all other procedures. Exclusion criteria include:

• A history of significant or unstable medical or mental health condition requiring treatment
• Current self-injury, suicidal thoughts or behavior
• Current illicit drug use by history or urine drug screen
• Abnormal physical exam or laboratory result at the time of in-person assessment
• Less than an 8th grade education or IQ below 70
• Current employees, or first-degree relatives of NIMH employees

Study participants are recruited through direct mailings, bulletin boards and listservs, outreach exhibits, print advertisements, and electronic media.

Clinical Measures

All potential volunteers first visit the study website (https://nimhresearchvolunteer.ctss.nih.gov), check a box indicating consent, and complete preliminary self-report screening questionnaires. The study website is HIPAA compliant and therefore does not collect PII ; instead, participants are instructed to contact the study team to provide their identity and contact information. The questionnaires include demographics, clinical history including medications, disability status (WHODAS 2.0), mental health symptoms (modified DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure), substance use survey (DSM-5 Level 2), alcohol use (AUDIT), handedness (Edinburgh Handedness Inventory), and perceived health ratings. At the conclusion of the questionnaires, participants are again prompted to send an email to the study team. Survey results, supplemented by NIH medical records review (if present), are reviewed by the study team, who determine if the participant is likely eligible for the protocol. These participants are then scheduled for an in-person assessment. Follow-up phone screenings were also used to determine if participants were eligible for in-person screening.

In-person Assessments

At this visit, participants undergo a comprehensive clinical evaluation to determine final eligibility to be included as a healthy research volunteer. The mental health evaluation consists of a psychiatric diagnostic interview (Structured Clinical Interview for DSM-5 Disorders (SCID-5), along with self-report surveys of mood (Beck Depression Inventory-II (BD-II) and anxiety (Beck Anxiety Inventory, BAI) symptoms. An intelligence quotient (IQ) estimation is determined with the Kaufman Brief Intelligence Test, Second Edition (KBIT-2). The KBIT-2 is a brief (20-30 minute) assessment of intellectual functioning administered by a trained examiner. There are three subtests, including verbal knowledge, riddles, and matrices.

Medical Evaluation

Medical evaluation includes medical history elicitation and systematic review of systems. Biological and physiological measures include vital signs (blood pressure, pulse), as well as weight, height, and BMI. Blood and urine samples are taken and a complete blood count, acute care panel, hepatic panel, thyroid stimulating hormone, viral markers (HCV, HBV, HIV), C-reactive protein, creatine kinase, urine drug screen and urine pregnancy tests are performed. In addition, blood samples that can be used for future genomic analysis, development of lymphoblastic cell lines or other biomarker measures are collected and banked with the NIMH Repository and Genomics Resource (Infinity BiologiX). The Family Interview for Genetic Studies (FIGS) was later added to the assessment in order to provide better pedigree information; the Adverse Childhood Events (ACEs) survey was also added to better characterize potential risk factors for psychopathology. The entirety of the in-person assessment not only collects information relevant for eligibility determination, but it also provides a comprehensive set of standardized clinical measures of volunteer health that can be used for secondary research.

MRI Scan

Participants are given the option to consent for a magnetic resonance imaging (MRI) scan, which can serve as a baseline clinical scan to determine normative brain structure, and also as a research scan with the addition of functional sequences (resting state and diffusion tensor imaging). The MR protocol used was initially based on the ADNI-3 basic protocol, but was later modified to include portions of the ABCD protocol in the following manner:

1. The T1 scan from ADNI3 was replaced by the T1 scan from the ABCD protocol.
2. The Axial T2 2D FLAIR acquisition from ADNI2 was added, and fat saturation turned on.
3. Fat saturation was turned on for the pCASL acquisition.
4. The high-resolution in-plane hippocampal 2D T2 scan was removed and replaced with the whole brain 3D T2 scan from the ABCD protocol (which is resolution and bandwidth matched to the T1 scan).
5. The slice-select gradient reversal method was turned on for DTI acquisition, and reconstruction interpolation turned off.
6. Scans for distortion correction were added (reversed-blip scans for DTI and resting state scans).
7. The 3D FLAIR sequence was made optional and replaced by one where the prescription and other acquisition parameters provide resolution and geometric correspondence between the T1 and T2 scans.

At the time of the MRI scan, volunteers are administered a subset of tasks from the NIH Toolbox Cognition Battery. The four tasks include:

1. Flanker inhibitory control and attention task assesses the constructs of attention and executive functioning.
2. Executive functioning is also assessed using a dimensional change card sort test.
3. Episodic memory is evaluated using a picture sequence memory test.
4. Working memory is evaluated using a list sorting test.

MEG

An optional MEG study was added to the protocol approximately one year after the study was initiated, thus there are relatively fewer MEG recordings in comparison to the MRI dataset. MEG studies are performed on a 275 channel CTF MEG system (CTF MEG, Coquiltam BC, Canada). The position of the head was localized at the beginning and end of each recording using three fiducial coils. These coils were placed 1.5 cm above the nasion, and at each ear, 1.5 cm from the tragus on a line between the tragus and the outer canthus of the eye. For 48 participants (as of 2/1/2022), photographs were taken of the three coils and used to mark the points on the T1 weighted structural MRI scan for co-registration. For the remainder of the participants (n=16 as of 2/1/2022), a Brainsight neuronavigation system (Rogue Research, Montréal, Québec, Canada) was used to coregister the MRI and fiducial localizer coils in realtime prior to MEG data acquisition.

Specific Measures within Dataset

Online and In-person behavioral and clinical measures, along with the corresponding phenotype file name, sorted first by measurement location and then by file name.

Bids and tenders for studies and implementation of wastewater projects