Objectives: To develop and pilot a tool to measure and improve pharmaceutical companies' clinical trial data sharing policies and practices. Design: Cross sectional descriptive analysis. Setting: Large pharmaceutical companies with novel drugs approved by the US Food and Drug Administration in 2015. Data sources: Data sharing measures were adapted from 10 prominent data sharing guidelines from expert bodies and refined through a multi-stakeholder deliberative process engaging patients, industry, academics, regulators, and others. Data sharing practices and policies were assessed using data from ClinicalTrials.gov, Drugs@FDA, corporate websites, data sharing platforms and registries (eg, the Yale Open Data Access (YODA) Project and Clinical Study Data Request (CSDR)), and personal communication with drug companies. Main outcome measures: Company level, multicomponent measure of accessibility of participant level clinical trial data (eg, analysis ready dataset and metadata); drug and trial level measures of registration, results reporting, and publication; company level overall transparency rankings; and feasibility of the measures and ranking tool to improve company data sharing policies and practices. Results: Only 25% of large pharmaceutical companies fully met the data sharing measure. The median company data sharing score was 63% (interquartile range 58-85%). Given feedback and a chance to improve their policies to meet this measure, three companies made amendments, raising the percentage of companies in full compliance to 33% and the median company data sharing score to 80% (73-100%). The most common reasons companies did not initially satisfy the data sharing measure were failure to share data by the specified deadline (75%) and failure to report the number and outcome of their data requests. Across new drug applications, a median of 100% (interquartile range 91-100%) of trials in patients were registered, 65% (36-96%) reported results, 45% (30-84%) were published, and 95% (69-100%) were publicly available in some form by six months after FDA drug approval. When examining results on the drug level, less than half (42%) of reviewed drugs had results for all their new drug applications trials in patients publicly available in some form by six months after FDA approval. Conclusions: It was feasible to develop a tool to measure data sharing policies and practices among large companies and have an impact in improving company practices. Among large companies, 25% made participant level trial data accessible to external investigators for new drug approvals in accordance with the current study's measures; this proportion improved to 33% after applying the ranking tool. Other measures of trial transparency were higher. Some companies, however, have substantial room for improvement on transparency and data sharing of clinical trials.

This data release presents the Yale stocks and flows database (YSTAFDB). Its data describe the use of 102 materials from the early 1800s to circa 2013 through anthropogenic cycles, their recycling and criticality properties, and on spatial scales ranging from suburbs to global. This data collection was previously scattered across multiple non-uniformly formatted files such as journal papers, reports, and unpublished spreadsheets. These data have been synthesized into YSTAFDB, which is presented as individual comma-separated text files and also in MySQL and PostgreSQL database formats. Consolidation of these data into a single database can increase their accessibility and reusability, which is relevant to diverse stakeholders ranging from researchers in sustainability science to government employees involved in national emergency planning.

for clarity, each initiative has been grouped under one of the five themes of Table 1, but several of these initiatives cater to more than one of the five themesAAAS: American Association for the Advancement of Science; BITSS: Berkeley Initiative for Transparency in the Social Sciences; BPS: Best Practices in Science; COPE: Committee on Publication Ethics; dbGAP: Database on Genotypes and Phenotypes; EQUATOR: Enhancing the quality and transparency of reporting; GEO: Gene Expression Omnibus; ICMJE: International Committee of Medical Journal Editors; ICSU: International Council for Science; NCPRE: National Center for Professional and Research Ethics; NIH: National Institutes of Health; REWARD: Reduce research waste and reward diligence; SRSM: Society for Research Synthesis Methodology; YODA: Yale University Open Data Access.A nonexhaustive list of initiatives that address various meta-research themes.

The Extended Yale B database consists of 2414 frontal-face images of 38 subjects. Each subject has around 64 images. The images are cropped and normalized to 192 × 168 under various laboratory-controlled lighting conditions.

The extended Yale Face Database B contains 16128 images of 28 human subjects under 9 poses and 64 illumination conditions. The data format of this database is the same as the Yale Face Database B. Please refer to the homepage of the Yale Face Database B for more detailed information of the data format. You are free to use the extended Yale Face Database B for research purposes. All publications which use this database should acknowledge the use of "the Exteded Yale Face Database B" and reference Athinodoros Georghiades, Peter Belhumeur, and David Kriegman s paper, "From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose", PAMI, 2001. The extended database as opposed to the original Yale Face Database B with 10 subjects was first reported by Kuang-Chih Lee, Jeffrey Ho, and David Kriegman in "Acquiring Linear Subspaces for Face Recognition under Variable Lighting, PAM

Public opinion poll on: Animals; Asia; Business; China; Communications Technology; Congress; Consumer; Economics; Elections; Energy; Environment; Europe; Family; Finances; Foreign Policy; Future; Government; Groups and Organizations; Health; Ideology; India; Information; Japan; Latin America; Local; Media; Mood; Notable People; Nuclear; Participation; Political Partisanship; Presidency; Regulation; Religion; Science; Social Media; Spending; States; Taxing; Technology; Television; Transportation.

This data was collected with support from J-PAL's Cash Transfers for Child Health (CaTCH) initiative with the aim to understand if mobile phones can improve women's awareness and take-up of maternity benefits. The data collected also is part of a larger study focused on understanding constraints to women's mobile phone use and how to close India’s digital gender gap. Under the CaTCH research, women were called and provided information about how to access public maternal health-focused conditional cash transfers (CCTs); phone and in-person surveys were used to understand knowledge changes. This dataset includes three waves of phone survey and a final follow-up survey conducted in-person. ***** Note for users ***** 1. There are a total of 13 files that are relevant to this dataset. Please download the full packet (data and documentation) for the best user experience. [Access Dataset > Original Format ZIP]. 2. Please read the "0. User guide.pdf" document first. It contains important information about the other files in the ZIP file. 3. Please also note that this dataset can be used to conduct descriptive analysis but does not contain treatment indicators.

Same as cropped images here, just converted to PNG instead http://vision.ucsd.edu/~leekc/ExtYaleDatabase/ExtYaleB.html

I do not own this data. All credits go to:

"From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose", PAMI, 2001, "Acquiring Linear Subspaces for Face Recognition under Variable Lighting", PAMI, May, 2005 "the Extended Yale Face Database B"

The cropped dataset only contains the single P00 pose.

Data format is like yaleBxx_P00A(+/-)aaaE(+/-)ee

• xx = Subject ID
• (+/-)aaa = Azimuth angle
• (+/-)ee = Elevation angle

For example the file yaleB38_P00A+035E+65.png is of subject 38, in pose 00, with light source at (+035, +65) degrees (azimuth, elevation) w.r.t the camera.

Objective: To determine the top 100-ranked (by impact factor) clinical journals' policies toward publishing research previously published on preprint servers (preprints).

Design: Cross sectional. Main outcome measures: Editorial guidelines toward preprints, journal rank by impact factor.

Results: 86 (86%) of the journals examined will consider papers previously published as preprints (preprints), 13 (13%) determine their decision on a case-by-case basis, and 1 (1%) does not allow preprints.

Conclusions: We found wide acceptance of publishing preprints in the clinical research community, although researchers may still face uncertainty that their preprints will be accepted by all of their target journals.

Methods We examined journal policies of the 100 top-ranked clinical journals using the 2018 impact factors as reported by InCites Journal Citation Reports (JCR). First, we examined all journals with an impact factor greater than 5, and then we manually screened by title and category do identify the first 100 clinical journals. We included only those that publish original research. Next, we checked each journal's editorial policy on preprints. We examined, in order, the journal website, the publisher website, the Transpose Database, and the first 10 pages of a Google search with the journal name and the term "preprint." We classified each journal's policy, as shown in this dataset, as allowing preprints, determining based on preprint status on a case-by-case basis, and not allowing any preprints. We collected data on April 23, 2020.

(Full methods can also be found in previously published paper.)

This dataset contains annual, summertime, and wintertime surface urban heat island (SUHI) intensities for day and night for over 10,000 urban clusters throughout the world. The dataset was created using the MODIS 8-day TERRA and AQUA land surface temperature (LST) products, the Landscan urban extent database, the Global Multi-resolution Terrain …

Objective To characterise experiences using clinical research data shared through the National Institutes of Health (NIH)'s Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) clinical research data repository, along with data recipients’ perceptions of the value, importance and challenges with using BioLINCC data. Design and setting Cross-sectional web-based survey. Participants All investigators who requested and received access to clinical research data from BioLINCC between 2007 and 2014. Main outcome measures Reasons for BioLINCC data request, research project plans, interactions with original study investigators, BioLINCC experience and other project details. Results There were 536 investigators who requested and received access to clinical research data from BioLINCC between 2007 and 2014. Of 441 potential respondents, 195 completed the survey (response rate=44%); 89% (n=174) requested data for an independent study, 17% (n=33) for pilot/preliminary analysis. Commonly cited reasons for requesting data through BioLINCC were feasibility of collecting data of similar size and scope (n=122) and insufficient financial resources for primary data collection (n=76). For 95% of respondents (n=186), a primary research objective was to complete new research, as opposed to replicate prior analyses. Prior to requesting data from BioLINCC, 18% (n=36) of respondents had contacted the original study investigators to obtain data, whereas 24% (n=47) had done so to request collaboration. Nearly all (n=176; 90%) respondents found the data to be suitable for their proposed project; among those who found the data unsuitable (n=19; 10%), cited reasons were data too complicated to use (n=5) and data poorly organised (n=5). Half (n=98) of respondents had completed their proposed projects, of which 67% (n=66) have been published. Conclusions Investigators were primarily using clinical research data from BioLINCC for independent research, making use of data that would otherwise have not been feasible to collect.

Open source system for storage, retrieval, and integrated analysis of large amounts of data from high throughput proteomic technologies. YPED currently handles LCMS, MudPIT, ICAT, iTRAQ, SILAC, 2D Gel and DIGE. The repository contains data sets which have been released for public viewing and downloading by the responsible Primary Investigators. It includes proteomic data generated by the Yale NIDA Neuroproteomics Center (http://medicine.yale.edu/keck/nida/index.aspx). Sample descriptions are compatible with the evolving MIAPE standards.

The Yale face database is a face dataset, mainly used for identification, which contains 15 subjects, each of which has 11 images, a total of 165 grayscale images in GIF format, and each subject contains different facial expressions: Center light, with glasses, happy, left light, without glasses, normal, right light, sad, sleepy, surprised and wink. This dataset was released by Yale University in 2001.

Solution Publishing by Allforce Ivy League Business Pros (ILBP) Elite Ivy League Graduate Database for Precision Networking Solution Publishing by Allforce offers a premium database connecting you to over 150,000 Ivy League alumni. This exclusive dataset enables targeted outreach to graduates from Harvard, Yale, Princeton, Columbia, Brown, Dartmouth, UPenn, and Cornell. Core Dataset Features

Comprehensive Alumni Coverage: Direct access to 150,000+ verified Ivy League graduates Detailed Educational Profiles: Information on degrees, graduation years, and specialized programs Advanced Segmentation Options: Filter by industry, job function, and seniority level Regular Data Verification: Continuous updates ensure data accuracy and compliance

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Institutional Coverage Our database spans prestigious institutions and their graduate schools, including:

Harvard (Law, Business, Medical, Education) Yale (Law, Management, Medicine, Divinity) Princeton (Public Affairs, Theological Seminary) Columbia (Law, Business, Medicine, Journalism) Brown (Medicine, Public Health, Graduate School) Dartmouth (Medicine, Tuck Business School) UPenn (Law, Wharton, Perelman School of Medicine) Cornell University

Solution Publishing by Allforce Ivy League Business Pros provides unmatched access to this elite professional network, enabling sophisticated marketing and recruitment strategies targeting this influential demographic.RetryClaude can make mistakes. Please double-check responses.

The Natural Resource Management Index (NRMI), 2011 Release is a composite index for 174 countries derived from the average of four proximity-to-target indicators for eco-region protection (weighted average percentage of biomes under protected status), access to improved sanitation, access to improved water and child mortality. The 2011 release of the NRMI includes a consistent time series of NRMIs for 2006 to 2011. In addition, the 2011 release includes two new indicators that will eventually supplant the NRMI: a Natural Resource Protection Indicator (NRPI) that is solely composed of the eco-region protection indicator, and a Child Health Indicator (CHI), which is an unweighted average of the proximtiy-to-target scores for access to water, access to sanitation, and child mortality. The data set is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the Yale Center for Environmental Law and Policy (YCELP), Yale University.

Abstract

The Ghana Socioeconomic Panel Survey is a joint effort between the Economic Growth Centre at Yale University and the Institute of Statistical, Social and Economic Research (ISSER), at the University of Ghana (Legon, Ghana). The survey is meant to remedy a major constraint on the understanding of development in low-income countries - the absence of detailed, multi-level and long-term scientific data that follows individuals over time and describes both the natural and man-made environment in which the individuals reside. Most data collection efforts are short-term - carried out at one point in time; and limited in scope – collecting information on only a few aspects of the lives of the persons in the study; and when there are multiple rounds of data collection, individuals who leave the study area are dropped. This means that the most mobile people are not included in existing surveys and studies, perhaps substantially biasing inferences about who benefits from and who bears the cost of the development process. The goal of this project is to follow all individuals, or a random subset, over time using a comprehensive set of survey instruments to shed new light on long-run processes of economic development.

The 2009 survey is the first in a series that is intended to include 5 surveys over the next 15-21 years. Surveys will be implemented approximately every 3 years. In subsequent waves of the panel, a sample of moved households and individuals who have moved out of original households to form new households or joined other households originally not in the panel sample, will be interviewed in addition to the original sample. The number of households in the Panel Study thus has the potential of increasing due to the nature of the design; tracking wholly moved and split households.

The principal objective of the panel survey is to provide a comprehensive data base for carrying out a wide range of studies of the medium- and long-term changes, or lack of changes, that take place during the process of development. The information gathered from the survey is expected to inform decision makers in the formulation of economic and social policies to: - Identify target groups for government assistance; - Construct models to stimulate the impact on individual groups of the various policy options and to analyze the impact of decisions that have already been implemented; - Access the economic situation on living conditions of households; and - Provide benchmark data for district assemblies.

Geographic coverage

The survey provides regionally representative data for the 10 regions of Ghana. In all, 5010 households from 334 Enumeration Areas (EAs) were sampled. Fifteen households were selected from each of the EAs. The number of EAs for each region was proportionately allocated based on estimated 2009 population share for each region. EAs for Upper East and Upper West regions, which have relatively smaller population sizes, were over sampled to allow for a reasonable number of households to be interviewed in these regions.

Analysis unit

Households, individuals, agricultural plots, household enterprises

Universe

Nationally representative, regionally representative for all 10 regions.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey provides regionally representative data for the 10 regions of Ghana. In all, 5010 households from 334 Enumeration Areas (EAs) were sampled. Fifteen households were selected from each of the EAs. The distribution of the enumeration areas across the regions in Ghana is presented in Table 1. The number of EAs for each region was proportionately allocated based on estimated 2009 population share for each region. EAs for Upper East and Upper West regions, which have relatively smaller population sizes, were over sampled to allow for a reasonable number of households to be interviewed in these regions.

A two-stage stratified sample design was used for the survey. Stratification was based on the regions of Ghana. The first stage involved selecting geographical precincts or clusters from an updated master sampling frame constructed from the 2000 Ghana Population and Housing Census. A total of 334 clusters (census enumeration areas) were selected from the master sampling frame. The clusters were randomly selected from the list of EAs in each region. The selection was based on a simple random sampling technique. A complete household listing was conducted in 2009 in all the selected clusters to provide a sampling frame for the second stage selection of households.

The second stage of selection involved a simple random sampling of 15 of the listed households from each selected cluster. The primary objective of the second stage of selection was to ensure adequate numbers of completed individual interviews to provide estimates for key indicators with acceptable precision at the regional level. Other sampling objectives were to facilitate manageable interviewer workload within each sample area and to reduce the effects of intra-class correlation within a sample area on the variance of the survey estimates.

Mode of data collection

Face-to-face [f2f]

Research instrument

The information gathered from the survey will assist decision makers in the formulation of economic and social policies to: - Identify target groups for government assistance - Construct models to stimulate the impact on individual groups of the various policy options and to analyze the impact of decisions that have already been implemented - Access the economic situation on living conditions of households - Provide benchmark data for district assemblies

To achieve these objectives, detailed data has been collected in the following subject areas: 1. Demographic characteristics: employment, education, migration

1. Information about non-resident spouses and relatives

2. Assets:

3. Household assets: (i) Livestock (ii) Tools (iii) Durable Goods Financial assets: (i) Borrowing (ii) Lending (iii) In-transfers (iv) Out-transfers (v) Savings

4. Agricultural Production

5. Land information: (i) Plot background (ii) Size (iii) Fallowing information, soil type, irrigation (iv) Investment, ownership, rental status (v) Crops (vi) Chemical inputs (vii) Tractor use (viii) Seeds (ix) Labour inputs

6. Sales and storage: (ii) Revenues from crop production (ii) Crop stores

7. Non-farm Household Enterprise

8. Basic Information and Assets (i) Basic information (ii) Enterprise assets

9. Information about employees (i) Information about all employees (ii) Information about four important employees (iii) Enterprises operating in the past 1 month (iv) Enterprise in a typical month

10. Accounting: General enterprise

11. Accounting: Trade/wholesale enterprise

12. Accounting: Food enterprise

13. Accounting: Services

14. Household Health

15. Insurance

16. Anthropometry

17. Immunization

18. Activities of daily living

19. Miscellaneous health

20. Health in the past 2 weeks

21. Health in the past 12 month

22. Womens' Health

23. Fertility

24. Power

25. Mens' Health

26. Reproductive Health

27. Power

28. Children's Module

29. Young child health - children younger than 5 years old

30. Digit span test- children aged 5-15

31. Raven's Pattern Cognitive Assessment- children aged 5-15

32. Math questions- children aged 9-26

33. English questions- children aged 9-26

34. Psychology/Social Networking

35. Psychology (i) Depression (ii) Subjective social welfare (iii) Regretted consumption (iv) Townsend questions (v) Trust and solidarity (vi) Time use

36. Big 5 personality questions

37. Social networking

38. Information seeking (i) Interaction with organizations (ii) Extension services (iii) Volunteerism

39. Consumption Module

40. Food items consumed

41. Clothing and footwear

42. Expenditure on other items in last 12 months

43. Fuel and other lubricants

44. Housing Characteristics

45. Part A - Rent, water, light, cooking, waste disposal, building materials

46. Part B - Dwelling type, ownership, living conditions, power supply, surroundings

The community inventory documents a broad range of natural and institutional features of the community, including political organizations, financial institutions, the presence of various development programs, and community infrastructure. There was also a questionnaire for Districts and Municipal Assemblies. As of December 2015, Seperate documentation for the Community survey and the data will be made available later.

Cleaning operations

The processing of the survey data began shortly after the fieldwork commenced. The first stage of data processing involved office editing and post-coding. Questionnaires were edited to double-check for completeness and consistency in the questionnaires returned, while the post-coding served to define new response categories to pre-coded question or define a response set for open ended questions. Once the editing and post-coding were done, the questionnaires were passed on for data entry.

The data entry program was designed in CSPro version 4.0. The entry program was designed with the necessary skip patterns and consistency checks to ensure adequate data quality and validity. All questionnaires were entered twice (100 percent verification) and the two files were compared for entry errors which were subsequently verified and corrected with the questionnaires. The data entry was completed in August of 2010. The consolidated data files in CSPro format were then converted to STATA format for further consistency checks and cleaning.

International Journal of Business and Management Abstract & Indexing - ResearchHelpDesk - International Journal of Business and Management (IJBM) is an international, double-blind peer-reviewed, open-access journal published by the Canadian Center of Science and Education. The journal aims at encouraging theoretical and applied research in the field of business and management, promoting the exchange of ideas between science and practice. In addition to original theoretical and empirical work, excellent state of the art contributions will also be considered. The journal focuses on the topics: Corporate Governance; Human Resource Management; Marketing & Strategic Management; Financial Management; Information Technology Management; Production & Operations Management. It provides an academic platform for professionals and researchers to contribute innovative work in the field. IJBM carries original and full-length articles that reflect the latest research and developments in both theoretical and practical aspects of business and management. Abstract & indexing Academic Journals Database COPAC EBSCOhost Electronic Journals Library Elektronische Zeitschriftenbibliothek (EZB) Excellence in Research for Australia (ERA) Genamics JournalSeek GETIT@YALE (Yale University Library) Google Scholar IBZ Online Infotrieve JournalTOCs Library and Archives Canada LOCKSS MIAR National Library of Australia NewJour Open J-Gate PKP Open Archives Harvester Publons ROAD SHERPA/RoMEO Standard Periodical Directory UCR Library Ulrich's Universe Digital Library WorldCat ZBW-German National Library of Economics