Objective: Routine primary care data may be used for the derivation of clinical prediction rules and risk scores. We sought to measure the impact of a decision support system (DSS) on data completeness and freedom from bias.

Materials and Methods: We used the clinical documentation of 34 UK General Practitioners who took part in a previous study evaluating the DSS. They consulted with 12 standardized patients. In addition to suggesting diagnoses, the DSS facilitates data coding. We compared the documentation from consultations with the electronic health record (EHR) (baseline consultations) vs. consultations with the EHR-integrated DSS (supported consultations). We measured the proportion of EHR data items related to the physician’s final diagnosis. We expected that in baseline consultations, physicians would document only or predominantly observations related to their diagnosis, while in supported consultations, they would also document other observations as a result of exploring more diagnoses and/or ease of coding.

Results: Supported documentation contained significantly more codes (IRR=5.76 [4.31, 7.70] P<0.001) and less free text (IRR = 0.32 [0.27, 0.40] P<0.001) than baseline documentation. As expected, the proportion of diagnosis-related data was significantly lower (b=-0.08 [-0.11, -0.05] P<0.001) in the supported consultations, and this was the case for both codes and free text.

Conclusions: We provide evidence that data entry in the EHR is incomplete and reflects physicians’ cognitive biases. This has serious implications for epidemiological research that uses routine data. A DSS that facilitates and motivates data entry during the consultation can improve routine documentation.

MEASURE Evaluation is the USAID Global Health Bureau's primary vehicle for supporting improvements in monitoring and evaluation in population, health and nutrition worldwide. They help to identify data needs, collect and analyze technically sound data, and use that data for health decision making. Some MEASURE Evaluation activities involve the collection of innovative evaluation data sets in order to increase the evidence-base on program impact and evaluate the strengths and weaknesses of recent evaluation methodological developments. Many of these data sets may be available to other researchers to answer questions of particular importance to global health and evaluation research. Some of these data sets are being added to the Dataverse on a rolling basis, as they become available. This collection on the Dataverse platform contains a growing variety and number of global health evaluation datasets.

Resources has the highest rate of some data governance measures taken regarding AI in 2024 with some 93 percent of respondents saying measures were taken. Products had the least amount of measures against data governance, with 18 percent of respondents saying no measures were taken.

Performance measures are data metrics defined and tracked by city departments to measure the city government’s effectiveness and efficiency of service delivery. Data for the performance measures are derived from the biennial Resident Survey as well as department data tracking systems. Each performance measure is connected to one of the strategic goals and objectives that the City has defined as a high priority. The performance measures will be reviewed and refined annually to ensure they are representative of the priorities set out by City Council and the community.

Overview   This dataset provides the measurements of raw water storage levels in reservoirs crucial for public water supply, The reservoirs included in this dataset are natural bodies of water that have been dammed to store untreated water.    Key Definitions   Aggregation  The process of summarizing or grouping data to obtain a single or reduced set of information, often for analysis or reporting purposes.    Capacity The maximum volume of water a reservoir can hold above the natural level of the surrounding land, with thresholds for regulation at 10,000 cubic meters in England, Wales and Northern Ireland and a modified threshold of 25,000 cubic meters in Scotland pending full implementation of the Reservoirs (Scotland) Act 2011. Current Level The present volume of water held in a reservoir measured above a set baseline crucial for safety and regulatory compliance. Current Percentage The current water volume in a reservoir as a percentage of its total capacity, indicating how full the reservoir is at any given time. Dataset  Structured and organized collection of related elements, often stored digitally, used for analysis and interpretation in various fields.   Granularity  Data granularity is a measure of the level of detail in a data structure. In time-series data, for example, the granularity of measurement might be based on intervals of years, months, weeks, days, or hours  ID  Abbreviation for Identification that refers to any means of verifying the unique identifier assigned to each asset for the purposes of tracking, management, and maintenance.   Open Data Triage  The process carried out by a Data Custodian to determine if there is any evidence of sensitivities associated with Data Assets, their associated Metadata and Software Scripts used to process Data Assets if they are used as Open Data.   Reservoir Large natural lake used for storing raw water intended for human consumption. Its volume is measurable, allowing for careful management and monitoring to meet demand for clean, safe water. Reservoir Type The classification of a reservoir based on the method of construction, the purpose it serves or the source of water it stores. Schema  Structure for organizing and handling data within a dataset, defining the attributes, their data types, and the relationships between different entities. It acts as a framework that ensures data integrity and consistency by specifying permissible data types and constraints for each attribute.   Units  Standard measurements used to quantify and compare different physical quantities.     Data History   Data Origin   Reservoir level data is sourced from water companies who may also update this information on their website and government publications such as the Water situation reports provided by the UK government. Data Triage Considerations  Identification of Critical Infrastructure Special attention is given to safeguard data on essential reservoirs in line with the National Infrastructure Act, to mitigate security risks and ensure resilience of public water systems. Currently, it is agreed that only reservoirs with a location already available in the public domain are included in this dataset. Commercial Risks and Anonymisation The risk of personal information exposure is minimal to none since the data concerns reservoir levels, which are not linked to individuals or households. Data Freshness It is not currently possible to make the dataset live. Some companies have digital monitoring, and some are measuring reservoir levels analogically. This dataset may not be used to determine reservoir level in place of visual checks where these are advised. Data Triage Review Frequency   Annually unless otherwise requested  Data Specifications  Data specifications define what is included and excluded in the dataset to maintain clarity and focus. For this dataset: Each dataset covers measurements taken by the publisher. This dataset is published periodically in line with the publisher’s capabilities Historical datasets may be provided for comparison but are not required The location data provided may be a point from anywhere within the body of water or on its boundary. Reservoirs included in the dataset must be: Open bodies of water used to store raw/untreated water Filled naturally Measurable Contain water that may go on to be used for public supply Context  This dataset must not be used to determine the implementation of low supply or high supply measures such as hose pipe bans being put in place or removed. Please await guidance from your water supplier regarding any changes required to your usage of water. Particularly high or low reservoir levels may be considered normal or as expected given the season or recent weather. This dataset does not remove the requirement for visual checks on reservoir level that are in place for caving/pot holing safety. Some water companies calculate the capacity of reservoirs differently than others. The capacity can mean the useable volume of the reservoir or the overall volume that can be held in the reservoir including water below the water table. Data Publish Frequency   Annually

As part of the Mayor's Social Integration Strategy published in March 2018, one of the commitments was to develop a more comprehensive set of measures for social integration and to carry out bespoke and innovative data collection for London to achieve this.

This scoping study conducted by the Centre for Analysis of Social Media at Demos and commissioned by the GLA is the first step towards looking at more innovative data collection methods.

The report highlights the potential opportunities and pitfalls in using digital and online data in measuring social integration in London, identifies a diverse selection of sources available and provides an outline of potential use cases for this data across the breadth of social integration measures.

A handy one-page matrix of all of the evaluated sources is also available to download separately.

As per data from a recent report, in 2019, 56 percent of respondents claimed that overall performance or utilization was their primary method of measuring success in relation to data center infrastructure, whilst a return on investment (ROI) was cited by 38 percent. These measures do not have a focus on reducing energy usage or lowering the environmental impact - measurements like total cost to the environment (TCE) or IT assets lifecycle, which would contribute toward this, were cited less often by respondents. Just 11 percent stated IT asset lifecycles as being a method of measuring the success of data center infrastructure.

This indicator measures the percent of citizens living within one-quarter mile walking distance of a park or accessible open space if inside the urban core or half-mile walking distance of a park or accessible opens space if outside the urban core. This data set supports HE.C.1. of SD23. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/etbz-5muf

December 6, 2023 (Final DWR Data) The 2018 Legislation required DWR to provide or otherwise identify data regarding the unique local conditions to support the calculation of an urban water use objective (CWC 10609. (b)(2) (C)). The urban water use objective (UWUO) is an estimate of aggregate efficient water use for the previous year based on adopted water use efficiency standards and local service area characteristics for that year. UWUO is calculated as the sum of efficient indoor residential water use, efficient outdoor residential water use, efficient outdoor irrigation of landscape areas with dedicated irrigation meter for Commercial, Industrial, and Institutional (CII) water use, efficient water losses, and an estimated water use in accordance with variances, as appropriate. Details of urban water use objective calculations can be obtained from DWR’s Recommendations for Guidelines and Methodologies document (Recommendations for Guidelines and Methodologies for Calculating Urban Water Use Objective - https://water.ca.gov/-/media/DWR-Website/Web-Pages/Programs/Water-Use-And-Efficiency/2018-Water-Conservation-Legislation/Performance-Measures/UWUO_GM_WUES-DWR-2021-01B_COMPLETE.pdf). The datasets provided in the links below enable urban retail water suppliers calculate efficient outdoor water uses (both residential and CII), agricultural variances, variances for significant uses of water for dust control for horse corals, and temporary provisions for water use for existing pools (as stated in Water Boards’ draft regulation). DWR will provide technical assistance for estimating the remaining UWUO components, as needed. Data for calculating outdoor water uses include: • Reference evapotranspiration (ETo) – ETo is evaporation plant and soil surface plus transpiration through the leaves of standardized grass surfaces over which weather stations stand. Standardization of the surfaces is required because evapotranspiration (ET) depends on combinations of several factors, making it impractical to take measurements under all sets of conditions. Plant factors, known as crop coefficients (Kc) or landscape coefficients (KL), are used to convert ETo to actual water use by specific crop/plant. The ETo data that DWR provides to urban retail water suppliers for urban water use objective calculation purposes is derived from the California Irrigation Management Information System (CIMIS) program (https://cimis.water.ca.gov/). CIMIS is a network of over 150 automated weather stations throughout the state that measure weather data that are used to estimate ETo. CIMIS also provides daily maps of ETo at 2-km grid using the Spatial CIMIS modeling approach that couples satellite data with point measurements. The ETo data provided below for each urban retail water supplier is an area weighted average value from the Spatial CIMIS ETo. • Effective precipitation (Peff) - Peff is the portion of total precipitation which becomes available for plant growth. Peff is affected by soil type, slope, land cover type, and intensity and duration of rainfall. DWR is using a soil water balance model, known as Cal-SIMETAW, to estimate daily Peff at 4-km grid and an area weighted average value is calculated at the service area level. Cal-SIMETAW is a model that was developed by UC Davis and DWR and it is widely used to quantify agricultural, and to some extent urban, water uses for the publication of DWR’s Water Plan Update. Peff from Cal-SIMETAW is capped at 25% of total precipitation to account for potential uncertainties in its estimation. Daily Peff at each grid point is aggregated to produce weighted average annual or seasonal Peff at the service area level. The total precipitation that Cal-SIMETAW uses to estimate Peff comes from the Parameter-elevation Relationships on Independent Slopes Model (PRISM), which is a climate mapping model developed by the PRISM Climate Group at Oregon State University. • Residential Landscape Area Measurement (LAM) – The 2018 Legislation required DWR to provide each urban retail water supplier with data regarding the area of residential irrigable lands in a manner that can reasonably be applied to the standards (CWC 10609.6.(b)). DWR delivered the LAM data to all retail water suppliers, and a tabular summary of selected data types will be provided here. The data summary that is provided in this file contains irrigable-irrigated (II), irrigable-not-irrigated (INI), and not irrigable (NI) irrigation status classes, as well as horse corral areas (HCL_area), agricultural areas (Ag_area), and pool areas (Pool_area) for all retail suppliers.

Abstract: How can we measure and explain the precision of international organizations’ (IOs) founding treaties? We define precision by its negative – imprecision – as indeterminate language that intentionally leaves a wide margin of interpretation for actors after agreements enter into force. Compiling a “dictionary of imprecision” from almost 500 scholarly contributions and leveraging insight from linguists that a single vague word renders the whole sentence vague, we introduce a dictionary-based measure of imprecision (DIMI) that is replicable, applicable to all written documents, and yields a continuous measure bound between zero and one. To demonstrate that DIMI usefully complements existing approaches and advances the study of (im-)precision, we apply it to a sample of 76 IOs. Our descriptive results show high face validity and closely track previous characterizations of these IOs. Finally, we explore patterns in the data, expecting that imprecision in IO treaties increases with the number of states, power asymmetries, and the delegation of authority, while it decreases with the pooling of authority. In a sample of major IOs, we find robust empirical support for the power asymmetries and delegation propositions. Overall, DIMI provides exciting new avenues to study precision in International Relations and beyond. The files uploaded entail the material necessary to replicate the results from the article and Online appendix published in: Gastinger, M. and Schmidtke, H. (2022) ‘Measuring precision precisely: A dictionary-based measure of imprecision’, The Review of International Organizations, available at Doi: 10.1007/s11558-022-09476-y. Please let us know if you spot any mistakes or if we may be of any further assistance!

Although it is recommended that the Tableau online dashboards be the primary method of access to Measure Up! LOCUS, the underlying data is available for download. Submit a request for access via the contact page.

The California System Performance Measures (CA SPMs) are a series of metrics developed by the California Interagency Council on Homelessness (Cal ICH), pursuant to Health and Safety Code §50220.7, that help the state and local jurisdictions assess their progress toward preventing, reducing, and ending homelessness. All measures except for Measure 1b are generated using data from the state’s Homelessness Data Integration System. Measure 1b and Point in Time (PIT) Count data are sourced from each Continuum of Care’s PIT Count. Measure 1b and PIT Count data are not shown for 2021 because of irregularities in that year’s counts. For more information about the measures and how they are calculated, please see the California System Performance Measures Guide and Glossary: https://www.bcsh.ca.gov/calich/documents/california_system_performance_measures_guide.pdf

For more information about Measure 1b and PIT Count data, please see the Department of Housing and Urban Development’s website: https://www.hudexchange.info/programs/hdx/pit-hic.

American Community Survey Public Use Micro Sample, augmented by NYC Opportunity.

The catalogue provides a means for a user to determine which management measures and management targets are suitable to effectively manage a specific threat to the quality or quantity of source water, allowing the user to take local conditions into consideration.

The dataset contains all the current and historical performance measures submitted as part of ONC;s annual budget formulation process. These measures track agency priorities for electronic health record adoption, health information exchange, patient engagement, and privacy and security. Each measure contains the annual estimate and a measure target, if applicable, for all the years the measure was reported in the ONC Budget.

Data/code files for the following project: I study the viability of Twitter-based measures for measuring public attitudes about the police. I find that Twitter-based measures track Gallup's measure of public attitudes starting around 2014, when Twitter user base stabilized, but not before 2014. Increases in Black Lives Matter protests are also associated with increases in negative sentiment measures from Twitter. The findings suggest that Twitter-based measures can be used to acquire granular evaluations of police performance, but they can be more useful in analyzing panel data of multiple agencies over time than in tracking a single geographical area over time.

During a global October 2023 survey among communications specialists, almost four out of five (or 79 percent) of respondents said they used engagement data such as comments, views, shares and likes, to measure the individual success of each influencer marketing campaign. Around 46 percent of interviewees mentioned product sales, while 44 turned to impressions as a metric for success rate.

215137 Global export shipment records of Measure Tool with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

A standing issue is how to measure bias in Large Language Models (LLMs) like ChatGPT. We devise a novel method of sampling, bootstrapping, and impersonation that addresses concerns about the inherent randomness of LLMs and test if it can capture political bias in ChatGPT. Our results indicate that, by default, ChatGPT is aligned with Democrats in the US. Placebo tests indicate that our results are due to bias, not noise or spurious relationships. Robustness tests show that our findings are valid also for Brazil and the UK, different professions, and different numerical scales and questionnaires.

This data set contains the replication data for the article "Knowing and doing: The development of information literacy measures to assess knowledge and practice." This article was published in the Journal of Information Literacy, in June 2021. The data was collected as part of the contact author's PhD research on information literacy (IL). One goal of this study is to assess students' levels of IL using three measures: 1) a 21-item IL test for assessing students' knowledge of three aspects of IL: evaluating sources, using sources, and seeking information. The test is multiple choice, with four alternative answers for each item. This test is a "KNOW-measure," intended to measure what students know. 2) a source-evaluation measure to assess students' abilities to critically evaluate information sources in practice. This is a "DO-measure," intended to measure what students do in practice, in actual assignments. 3) a source-use measure to assess students' abilities to use sources correctly when writing. This is a "DO-measure," intended to measure what students do in practice, in actual assignments. The data set contains survey results from 626 Norwegian and international students at three levels of higher education: bachelor, master's and PhD. The data was collected in Qualtrics from fall 2019 to spring 2020. In addition to the data set and this README file, two other files are available here: 1) test questions in the survey, including answer alternatives (IL_knowledge_tests.txt) 2) details of the assignment-based measures for assessing source evaluation and source use (Assignment_based_measures_assessing_IL_skills.txt) Publication abstract: This study touches upon three major themes in the field of information literacy (IL): the assessment of IL, the association between IL knowledge and skills, and the dimensionality of the IL construct. Three quantitative measures were developed and tested with several samples of university students to assess knowledge and skills for core facets of IL. These measures are freely available, applicable across disciplines, and easy to administer. Results indicate they are likely to be reliable and support valid interpretations. By measuring both knowledge and practice, the tools indicated low to moderate correlations between what students know about IL, and what they actually do when evaluating and using sources in authentic, graded assignments. The study is unique in using actual coursework to compare knowing and doing regarding students’ evaluation and use of sources. It provides one of the most thorough documentations of the development and testing of IL assessment measures to date. Results also urge us to ask whether the source-focused components of IL – information seeking, source evaluation and source use – can be considered unidimensional constructs or sets of disparate and more loosely related components, and findings support their heterogeneity.