D-HaploDB genome-wide definitive haplotypes, determined using a collection of 100 Japanese complete hydatidiform moles (CHMs), each carrying a genome derived from a single sperm. The haplotypes incorporate 281 k (D-Haplo Phase I: D1), 581k (D-Haplo Phase II: D2), or 1M (D-Haplo Phase III: D3) SNPs, genotyped with high throughput array-based oligonucleotide hybridization techniques. The Definitive Haplotype Browser can be used to view various information, such as SNP alleles, haplotype blocks, LD-bins and extended shared haplotypes (ESHs) in our study.

The University of Wisconsin Antarctic Soils Database contains data collected by Dr. James G. Bockheim and his colleagues from 1975 through 1987. Data include site information, air and soil temperature measurements, soil profile features, and surface boulder weathering features for 482 sites in the McMurdo Sound area of Antarctica. Soil profile descriptions are provided for soils inside the McMurdo Dry Valleys from 23 December 1975 to 22 December 1987, and outside the Dry Valleys from 13 November 1978 to 04 January 1986. Chemical and physical properties of soils at 214 sites are also provided. The study area is confined to 77 deg 7.5 min S to 78 deg S, 160 deg E to 164 deg E. Data are in tab-delimited ASCII text format, and are available via ftp.

The functional traits of arable weeds in Eurasia and North Africa database contains functional trait values for specific leaf area, canopy height, canopy diameter, leaf area per node thickness, vegetative propagation, and plant life history for 928 arable weed species. The number of accessions used to calculate the trait values are provided. The data was collected up until 2021 from locations around Europe, Western Asia and North Africa, with minor collections in other parts of Eurasia (e.g., Japan), in order to characterise species growing as arable weeds in cereal and pulse crops managed under traditional agricultural regimes (that is, organically, without chemical fertilisers and herbicides, and in some cases minimal mechanisation) in these regions. This database iteration is version 1. The data are used by the R package WeedEco[1] to assign functional trait values to inputted species from archaeobotanical samples or other sources, allowing comparison through discriminant to three arable regime models. Details on the use of the R package can be found in Stroud et al.[2]

Full details regarding the methods used for data collection and calculations will be available in a data paper published at a later date.

References:

[1] Stroud, E., Charles, M., Hodgson, J., Jones, G., and Bogaard, A. (2023). WeedEco: Classification of unknown cases using linear discriminant analysis to understand farming regimes. R package version 1.0.0, https://github.com/WeedEco/WeedEco

[2] Stroud, E., Charles, M., Hodgson, J., Jones, G., and Bogaard, A. (accepted) See the fields through the weeds: introducing the WeedEco R package for comparing past and present arable farming systems using functional weed ecology. Vegetation History and Archaeobotany.

The Stanford University HIV Drug Resistance Database is a curated public database designed to represent, store, and analyze the different forms of data underlying HIVs drug resistance. HIVDB has three main types of content: (1) Database queries and references, (2) Interactive programs, and (3) Educational resources. Database queries are designed primarily for researchers studying HIV drug resistance. The interactive programs and educational resources are designed for both researchers and those wishing to learn more about HIV drug resistance. 1.DATABASE QUERY AND REFERENCE PAGES Genotype-Treatment Correlations This Genotype-Treatment section of the database links to 15 interactive query pages that explore the relationship between treatment with HIV-1 antiretroviral drugs (ARVs) and mutations in HIV reverse transcriptase (RT), protease, and integrase. There are five types of interactive query pages: Treatment Profiles (Protease and RT inhibitors) Mutation Profiles (Protease and RT mutations) Detailed Treatment Queries (Protease, RT, and integrase inhibitors) Detailed Mutation Queries (Protease, RT, and integrase mutations) Mutation Prevalence According to Subtype and Treatment Genotype-Phenotype Correlations The main page of the Genotype-Phenotype Correlations section links to four interactive query pages: three dynamically updated data summaries and one regularly updated downloadable dataset. Drug Resistance Positions Query for levels of resistance associated with known drug resistance mutations Detailed Phenotype Queries Queries for levels of resistance associated with individual mutations or mutation combinations at all positions of protease, RT, and integrase Patterns of Drug Resistance Mutations Downloadable Reference Dataset Genotype-Clinical Correlations This part of the database has two main sections: Clinical Trials Datasets Summaries of Clinical Studies References This part of the database has two main sections: one with summaries of the data from each of the references in HIVDB and one in which every primate immunodeficiency virus sequence in GenBank is annotated according to its presence or absence in HIVDB. Studies in HIVDB GenBank HIVDB New Submissions Approximately every three months, the New Submissions section lists the studies that have been entered into HIVDB. The study title links to the introductory page of the study in the References section. Database Statistics (http://hivdb.stanford.edu/pages/HIVdbStatistics.html) 2. INTERACTIVE PROGRAMS HIVDB has seven main interactive programs. 1. HIVdb Program Mutation List Analysis Sequence Analysis HIVdb Output Sierra Web Service Release Notes Algorithm Specification Interface (ASI) 2. HIValg Program 3. HIVseq Program 4. Calibrated Population Resistance (CPR) tool 5. Mutation ARV Evidence Listing (MARVEL) 6. ART-AiDE 7. Rega HIV-1 Subtyping tool Three programs in the HIV Drug Resistance Database share a common code base: HIVseq, HIVdb, and HIValg. HIVseq accepts user-submitted protease, RT, and integrase sequences, compares them to the consensus subtype B reference sequence, and uses the differences as query parameters for interrogating the HIV Drug Resistance database (Shafer, D Jung, & B Betts, Nat Med 2000; Rhee SY et al. AIDS 2006). The query result provides users with the prevalence of protease, RT and integrase mutations according to subtype and PI, nucleoside RT inhibitor (NRTI), non-nucleoside RT inhibitor (NNRTI), and integrase inhibitor (INI) exposure. This allows users to detect unusual sequence results immediately so that the person doing the sequencing can check the primary sequence output while it is still on the desktop. In addition, unexpected associations between sequences or isolates can be discovered by immediately retrieving data on isolates sharing one or more mutations with the sequence. There are three ways in which the HIVdb program can be used: (i) entering a list of protease and RT mutations, (ii) entering a complete sequence containing protease, RT, and/or integrase, and (iii) using a Web Service. HIVdb is an expert system that accepts user-submitted HIV-1 pol sequences and returns inferred levels of resistance to 20 FDA-approved ARV drugs including 8 PIs, 7 NRTIs, 4 NNRTIs, and - with this update - one INI. In the HIVdb system, each HIV-1 drug resistance mutation is assigned a drug penalty score and a comment; the total score for a drug is derived by adding the scores of each mutation associated with resistance to that drug. Using the total drug score, the program reports one of the following levels of inferred drug resistance: susceptible, potential low-level resistance, low-level resistance, intermediate resistance, and high-level resistance. HIValg is designed for users interested in comparing the results of different algorithms or who are interested in comparing and evaluating existing and newly developed algorithms. The ability to develop new algorithms that can be run on the HIV Drug Resistance Database depends on the Algorithm Specific Interface (ASI) compiler (Shafer & Betts JCM 2003). Submission of Sequences and Mutations For each of the three programs, sequences can be entered using either the Sequence Analysis Form or the Mutation List form. 3. EDUCATIONAL RESOURCES HIVDB contains several regularly updated sections summarizing data linking RT, protease, and integrase mutations and antiretroviral drugs (ARVs). These sections include (i) tabular summaries of the major mutations associated with each ARV class, (ii) detailed summaries of the major, minor, and accessory mutations associated with each ARV, (iii) the comments used by the HIVdb program, (iv) the scores used by the HIVdb program, (v) clinical studies in which baseline drug resistance mutations have been correlated with the virological response (clinical outcome) to a specific ARV, (vi) mutations that can be used for drug resistance surveillance, and (vii) a two-page PDF handout. 1. Drug Resistance Summaries Tabular Drug Resistance Summaries by ARV Class Detailed Drug Resistance Summaries by ARV Drug Resistance Mutation Comments Used by the HIVdb Program Drug Resistance Mutation Scores Used by the HIVdb Program Genotype-Clinical Outcome Correlation Studies 2. Surveillance Drug-Resistance Mutation List Section 3. PDF Handout Grant Support 1. National Institute for Allergy and Infectious Diseases (NIAID, NIH): Online HIV Drug Resistance Database (PI: Robert W. Shafer, MD, 1R01AI68581-01A1), 04/01/06 - 3/31/11 2. National Institute for Allergy and Infectious Diseases (NIAID, NIH) supplement to the grant Identification of Multidrug-Resistant HIV-1 Isolates (PI: Robert W. Shafer, MD, AI46148-01): Supplement provided 1999-2005. 3. NIH/NIGMS Program Project on AIDS Structural Biology Program Project: Targeting Ensembles of Drug Resistant Protease Variants (PI: Celia Schiffer, PhD, University of Massachusetts): 2002-2007 4. University-wide AIDS Research Program (CR03-ST-524). Community collaborative award: Optimizing Clinical HIV Genotypic Resistance Interpretation: Principal Investigators: Robert W. Shafer, MD and W. Jeffrey Fessel MD (Kaiser Permanente Medical Care Program): 2004-2005 5. Stanford University Bio-X Interdisciplinary Initiative: HIV Gene Sequence Analysis for Drug Resistance Studies: A Pharmacogenetic Challenge Principal Investigators: Robert W. Shafer, MD and Daphne Koller, Ph.D. (Computer Science): 2000-2002

The American College Catalog Study Database (CCS) contains academic data on 286 four-year colleges and universities in the United States. CCS is one of two databases produced by the Colleges and Universities 2000 project based at the University of California-Riverside. The CCS database comprises a sampled subset of institutions from the related Institutional Data Archive (IDA) on American Higher Education (ICPSR 34874). Coding for CCS was based on college catalogs obtained from College Source, Inc. The data are organized in a panel design, with measurements taken at five-year intervals: academic years 1975-76, 1980-81, 1985-86, 1990-91, 1995-96, 2000-01, 2005-06, and 2010-11. The database is based on information reported in each institution's college catalog, and includes data regarding changes in major academic units (schools and colleges), departments, interdisciplinary programs, and general education requirements. For schools and departments, changes in structure were coded, including new units, name changes, splits in units, units moved to new schools, reconstituted units, consolidated units, departments reduced to program status, and eliminated units.

To database is available in two versions. The first, [unprocessed], consists of images for five of the objects that contain both the object and the background. The second, [processed], contains images for all of the objects in which the background has been discarded (and the images consist of the smallest square that contains the object). For formal documentation look at the corresponding compressed technical report "Columbia Object Image Library (COIL-20)," S. A. Nene, S. K. Nayar and H. Murase, Technical Report CUCS-005-96, February 1996.

The Shiraz University (SU) fetal heart sounds database (SUFHSDB) contains fetal and maternal PCG recordings from 109 pregnant women.

Distribution of plants in Poland derived from vegetation plots (phytosociological releves)

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The study constructed a comprehensive, longitudinal dataset of all counties nested within U.S. States from 1970 to 2012. The study's main purpose was to facilitate research that would further understanding on firearm legislation and its impacts on violence. This comprehensive data collection effort included information on firearm legislation implemented across U.S. States over time in combination with multiple measures of firearm-related violence and injury. Moreover, to better understand the conditions under which firearm legislation is more or less effective, incorporation of county characteristics allowed for examination of whether the effectiveness of state-level firearm legislation depends upon particular characteristics of counties. The researchers conducted a secondary analysis utilizing a variety of archived external government and census sources. The Study's Dataset Include two Stata Files: CJRC_firearms_research.dta (95 Variables, 129,027 Cases) state_law_data.dta (19 Variables, 2,168 Cases)

Databases with information on Latin American universities according to the webometrics ranking.

This repository contains an open source database of Spatial Room Impulse Responses (SRIR) captured at three different performance spaces of the Detmold University of Music. It includes the following rooms:

• Detmold Konzerthaus (medium sized concert hall, ~600 seats).
• Brahmssaal (small music chamber room, ~100 seats).
• Detmold Sommertheater (theater, ~300 seats).

The collection contains approximately 600 multichannel RIRs corresponding to several source and receiver configurations. For each room we include measurement positions on stage and at the audience area captured with both an artificial head and an open microphone array compatible with the Spatial Decomposition Method (SDM).

The Detmold Konzerthaus holds a large scale Wave Field Synthesis system and a Room Acoustic Enhancement System. SRIRs of an ensemble of focused sources on stage and with conditions of increased artificial reverberation are also included.

If you use this dataset for your research, please cite our work:

Amengual Gari, S. V.; Sahin, B.; Eddy, D; Kob, M.: "Open Database of Spatial Room Impulse Responses at Detmold University of Music", 149th Convention of the Audio Engineering Society, 2020.

The database is organized in 3 sets:

- Set A:

Source: Single Source measurements.

Receiver: Open Array and Dummy Head.

Rooms: BS, DST, KH

Special configurations: Artificial reverberation, music stand on stage

- Set B:

Source: Loudspeaker and WFS orchestra

Receiver: Open Array.

Rooms: KH

- Set C:

Source: Loudspeaker orchestra

Receiver: Dummy Head and Omni8 array

Rooms: KH

Further details on the measurement procedure and acoustical analysis of the RIRs can be found in the following publications:

Set A

Amengual Gari, S. V., Investigations on the Influence of Acoustics on Live Music Performance using Virtual Acoustic Methods, Ph.D. thesis, 2017.

Amengual Garí, S. V.; Kob, M: "Investigating the impact of a music stand on stage using spatial impulse responses". 142nd Convention of the Audio Engineering Society, Berlin, May 2017.

Set B

Amengual Garí, S. V.; Pätynen, J.; Lokki, T.: "Physical and perceptual comparison of real and focused sound sources in a concert hall". Journal of the Audio Engineering Society, vol. 64 (12), pp. 1014-1025, December 2016.

Set C

Sahin, B., ““Investigation of the Detmold Concert Hall auditorium acoustics by comparing preference ratings and objective measurements.”, M.Sc. Thesis, 2017.

Sahin, B., Amengual, S. V., and Kob, M., “Investigating listeners’ preferences in Detmold Concert Hall by comparing sensory evaluation and objective measurements,” Proc. 43th DAGA, Kiel, 2017.

The International Registry of Reproductive Pathology Database is part of pioneering work done by Dr. Kenneth McEntee to comprehensively document thousands of disease cases studies. His large and comprehensive collection of case reports and physical samples was complimented by development of the International Registry of Reproductive Pathology Database in the 1980s. The original FoxPro Database files and a migrated access version were completed by the College of Veterinary Medicine in 2016. Access CSV files were completed by the University of Illinois Library in 2017.

The COVID-19 U.S. State Policy Database tracks state policies in response to the COVID-19 pandemic. The study was created by researchers at the Boston University School of Public Health and includes data on closures, shelter-in-place orders, housing protections, changes to Medicaid and SNAP, physical distancing closures, reopening, and more. Policies included are state-wide directives or mandates, not guidance or recommendations. In order for a policy to be included, it must have applied to the entire state.

The State Firearm Database catalogs the presence or absence of 134 firearm safety laws in 14 categories covering the 26-year period from 1991 to 2019. The classification system categorizes state firearm provisions using a methodology that both captures differences and maintains a level of comparability between states. Because of this, the database is not the most detailed nor the most comprehensive record of all state firearm policies. Other resources may provide users with a deeper understanding of individual provisions, while this database serves as an efficient way to compare the broad scope of state firearm laws across the country. These provisions covered 14 aspects of state policies, including regulation of the process by which firearm transfers take place, ammunition, firearm possession, firearm storage, firearm trafficking, and liability of firearm manufacturers. In addition, descriptions of the criteria used to code each provision have been provided so that there is transparency in how various law exemptions, exceptions, and other nuances were addressed.

The Integrated Postsecondary Education Data System (IPEDS) is a system of interrelated surveys conducted annually by the U.S. Department of Education's National Center for Education Statistics (NCES). IPEDS annually gathers information from about 6,400 colleges, universities, and technical and vocational institutions that participate in the federal student aid programs.

Access Database: To eliminate the step of downloading IPEDS separately by survey component or select variables, IPEDS has made available the entire survey data for one collection year in the Microsoft Access format beginning with the 2004-05 IPEDS data collection year. Each database contains the relational data tables as well as the metadata tables that describe each data table, the variable titles, descriptions and variables types. Value codes and value labels are also available for all categorical variables. When downloading an IPEDS Access Database, the file is compressed using WinZip.

This data collection is an expanded version of UNITED STATES SUPREME COURT JUDICIAL DATABASE, 1953-1996 TERMS (ICPSR 9422), encompassing all aspects of United States Supreme Court decision-making from the beginning of the Vinson Court in 1946 to the end of the Warren Court in 1968. Two major differences distinguish the expanded version of the database from the original collection: the addition of data on the decisions of the Vinson Court, and the inclusion of the conference votes of the Vinson and Warren courts. Whereas the original collection contained only the vote as reported in the UNITED STATES SUPREME COURT REPORTS, the expanded database includes all votes cast in conference. Concomitant with the expansion of the database is a shift in its basic unit of analysis. The original collection contained every case in which at least one justice wrote an opinion, and cases without opinions were excluded. This version includes every case in which the Court cast a conference vote, with and without opinions. The justices cast many more votes than they wrote opinions, and hence, the number of Warren Court records in this version increased by more than a factor of two over the original version. As in the original collection, distinct aspects of the Court's decisions are covered by six types of variables: (1) identification variables including case citation, docket number, unit of analysis, and number of records per unit of analysis, (2) background variables offering information on origin of case, source of case, reason for granting cert, parties to the case, direction of the lower court's decision, and manner in which the Court takes jurisdiction, (3) chronological variables covering date of term of court, chief justice, and natural court, (4) substantive variables including multiple legal provisions, authority for decision, issue, issue areas, and direction of decision, (5) outcome variables supplying information on form of decision, disposition of case, winning party, declaration of unconstitutionality, and multiple memorandum decisions, and (6) voting and opinion variables pertaining to the vote in the case and to the direction of the individual justices' votes.

Comprehensive list containing 70 verified University library businesses in North Carolina, United States with lastest contact information, ratings, reviews, and location data.

United States agricultural researchers have many options for making their data available online. This dataset aggregates the primary sources of ag-related data and determines where researchers are likely to deposit their agricultural data. These data serve as both a current landscape analysis and also as a baseline for future studies of ag research data. Purpose As sources of agricultural data become more numerous and disparate, and collaboration and open data become more expected if not required, this research provides a landscape inventory of online sources of open agricultural data. An inventory of current agricultural data sharing options will help assess how the Ag Data Commons, a platform for USDA-funded data cataloging and publication, can best support data-intensive and multi-disciplinary research. It will also help agricultural librarians assist their researchers in data management and publication. The goals of this study were to establish where agricultural researchers in the United States-- land grant and USDA researchers, primarily ARS, NRCS, USFS and other agencies -- currently publish their data, including general research data repositories, domain-specific databases, and the top journals compare how much data is in institutional vs. domain-specific vs. federal platforms determine which repositories are recommended by top journals that require or recommend the publication of supporting data ascertain where researchers not affiliated with funding or initiatives possessing a designated open data repository can publish data Approach The National Agricultural Library team focused on Agricultural Research Service (ARS), Natural Resources Conservation Service (NRCS), and United States Forest Service (USFS) style research data, rather than ag economics, statistics, and social sciences data. To find domain-specific, general, institutional, and federal agency repositories and databases that are open to US research submissions and have some amount of ag data, resources including re3data, libguides, and ARS lists were analysed. Primarily environmental or public health databases were not included, but places where ag grantees would publish data were considered. Search methods We first compiled a list of known domain specific USDA / ARS datasets / databases that are represented in the Ag Data Commons, including ARS Image Gallery, ARS Nutrition Databases (sub-components), SoyBase, PeanutBase, National Fungus Collection, i5K Workspace @ NAL, and GRIN. We then searched using search engines such as Bing and Google for non-USDA / federal ag databases, using Boolean variations of “agricultural data” /“ag data” / “scientific data” + NOT + USDA (to filter out the federal / USDA results). Most of these results were domain specific, though some contained a mix of data subjects. We then used search engines such as Bing and Google to find top agricultural university repositories using variations of “agriculture”, “ag data” and “university” to find schools with agriculture programs. Using that list of universities, we searched each university web site to see if their institution had a repository for their unique, independent research data if not apparent in the initial web browser search. We found both ag specific university repositories and general university repositories that housed a portion of agricultural data. Ag specific university repositories are included in the list of domain-specific repositories. Results included Columbia University – International Research Institute for Climate and Society, UC Davis – Cover Crops Database, etc. If a general university repository existed, we determined whether that repository could filter to include only data results after our chosen ag search terms were applied. General university databases that contain ag data included Colorado State University Digital Collections, University of Michigan ICPSR (Inter-university Consortium for Political and Social Research), and University of Minnesota DRUM (Digital Repository of the University of Minnesota). We then split out NCBI (National Center for Biotechnology Information) repositories. Next we searched the internet for open general data repositories using a variety of search engines, and repositories containing a mix of data, journals, books, and other types of records were tested to determine whether that repository could filter for data results after search terms were applied. General subject data repositories include Figshare, Open Science Framework, PANGEA, Protein Data Bank, and Zenodo. Finally, we compared scholarly journal suggestions for data repositories against our list to fill in any missing repositories that might contain agricultural data. Extensive lists of journals were compiled, in which USDA published in 2012 and 2016, combining search results in ARIS, Scopus, and the Forest Service's TreeSearch, plus the USDA web sites Economic Research Service (ERS), National Agricultural Statistics Service (NASS), Natural Resources and Conservation Service (NRCS), Food and Nutrition Service (FNS), Rural Development (RD), and Agricultural Marketing Service (AMS). The top 50 journals' author instructions were consulted to see if they (a) ask or require submitters to provide supplemental data, or (b) require submitters to submit data to open repositories. Data are provided for Journals based on a 2012 and 2016 study of where USDA employees publish their research studies, ranked by number of articles, including 2015/2016 Impact Factor, Author guidelines, Supplemental Data?, Supplemental Data reviewed?, Open Data (Supplemental or in Repository) Required? and Recommended data repositories, as provided in the online author guidelines for each the top 50 journals. Evaluation We ran a series of searches on all resulting general subject databases with the designated search terms. From the results, we noted the total number of datasets in the repository, type of resource searched (datasets, data, images, components, etc.), percentage of the total database that each term comprised, any dataset with a search term that comprised at least 1% and 5% of the total collection, and any search term that returned greater than 100 and greater than 500 results. We compared domain-specific databases and repositories based on parent organization, type of institution, and whether data submissions were dependent on conditions such as funding or affiliation of some kind. Results A summary of the major findings from our data review: Over half of the top 50 ag-related journals from our profile require or encourage open data for their published authors. There are few general repositories that are both large AND contain a significant portion of ag data in their collection. GBIF (Global Biodiversity Information Facility), ICPSR, and ORNL DAAC were among those that had over 500 datasets returned with at least one ag search term and had that result comprise at least 5% of the total collection. Not even one quarter of the domain-specific repositories and datasets reviewed allow open submission by any researcher regardless of funding or affiliation. See included README file for descriptions of each individual data file in this dataset. Resources in this dataset:Resource Title: Journals. File Name: Journals.csvResource Title: Journals - Recommended repositories. File Name: Repos_from_journals.csvResource Title: TDWG presentation. File Name: TDWG_Presentation.pptxResource Title: Domain Specific ag data sources. File Name: domain_specific_ag_databases.csvResource Title: Data Dictionary for Ag Data Repository Inventory. File Name: Ag_Data_Repo_DD.csvResource Title: General repositories containing ag data. File Name: general_repos_1.csvResource Title: README and file inventory. File Name: README_InventoryPublicDBandREepAgData.txt

As a genre, 'Books of Secrets' (Libri di Secreti or, more generically, ricettari) first flourished during the middle ages. They were technical, crafts-based 'how-to-do it' manuals, 'secret' because they were written in Latin and available only to the privileged few. With the advent of the printing press, vernacular editions started to appear—the first in Italian was the Opera Nuova intitolata Dificio di ricette in 15271 —and by the mid-sixteenth century secrets books were flooding off the presses. They tended to contain instructions for the making of medicines, recipes for preserving food, recipes pertaining to domestic management (such as making inks and removing stains), some for cosmetics and some 'alchemical' recipes, for refining chemicals. This mix was to remain characteristic of the genre, (although some dispensed with cookery and others with household management), which persisted well into the nineteenth century. The importance of the genre lies in the fact that, as manuals for 'domestic' medicine with a huge circulation, they are central to the history of medicine and health. They reveal much about the kind of medical practices, approaches and ingredients adopted in the home amongst the general population, which may well have been quite different to those taught in Latin, at the university, or advocated by official pharmacopoeias. Closer study will enable us to track the dissemination of key developments in medical history, such as the shift from herbal to chemical medicine and from the 'humoral' to the 'modern' body. Italy was at the vanguard of medical developments during the Renaissance and although the genre soon became popular in other European countries, many of these were Italian texts in translation. Despite this, there has been little research on Italian recipes and 'secrets' themselves, particularly in English, a state which this project was devised to rectify. Given the thousands of 'books of secrets' and ricettari which appeared in print and manuscript between the sixteenth and nineteenth centuries, this database cannot claim to be representative of the genre as a whole. We have nonetheless sought to include representative samples of different kinds of texts across the period so as to enable us to consider chronological changes and developments within the genre as a whole, as well as to compare the various kinds of text, such as the printed pamphlets, and manuscripts with the larger printed books. The 'Italian Books of Secrets Database' project was initiated and overseen by Professor David Gentilcore (School of Historical Studies, University of Leicester) as a pilot study based on sources held in London libraries, mainly the Wellcome Library and British Library. It was carried out and funded within the auspices of the Wellcome Trust Strategic Award in the 'Cultures and Practices of Health', which was based at the Universities of Warwick and Leicester, during the period 2003-8. The construction of the database and data entry were carried out by Dr Tessa Storey, whilst a research assistant in the School of Historical Studies, University of Leicester. Sandy Pearson, senior computer officer in the Faculty of Social Sciences, has provided invaluable advice and assistance throughout the preparation of the database. We would like to take this opportunity to thank both the Wellcome Trust and the University of Leicester for providing funds and infrastructural support in the realisation of this project.

Patent pledges are voluntary public commitments that patent holders make to limit the enforcement or exploitation of their patent rights. Such pledges have been made for decades and appear in industries ranging from software to automotive to green tech to biotech. Originally compiled by Prof. Jorge L. Contreras (University of Utah) and now curated by the Center for Advanced Studies in Bioscience Innovation Law (CeBIL) at the University of Copenhagen, this dataset offers the most comprehensive public record of patent pledges to date. The database covers more than 300 pledges spanning software, telecommunications, green technology, automotive, biotechnology, medical devices, and AI. Each record includes: Pledgor name Date of pledge (exact or best‐estimate) Excerpt of the pledge text Patent families / technologies covered Pledge type (e.g., non-assert, FRAND-style) Source URLTracking number (an ID that matches the filename of the archived snapshot capturing the pledge as it appeared online) Available for download Master spreadsheet of all pledge metadata PDF, PNG snapshot or MP4 of each pledge at time of collection The CeBIL research team, led by Dr. Gabriela Lenarczyk in close collaboration with Professor Timo Minssen (CeBIL Director), will update the dataset quarterly and welcome community submissions of new pledges or errata. (Initial public release: V1, June 2025; subsequent versions will follow Dataverse semantic-versioning conventions.) Patent Pledge literature Jorge L. Contreras, Patent Pledges in Elgar Encyclopedia of Intellectual Property Law, Paul Torremans, Irini Stamatoudi, Peter K. Yu, Bernd Justin Jütte (eds.), Edward Elgar (2025), linkJorge L. Contreras, Patent Pledges as Portfolio Management Tools: Benefits, Obligations and Enforcement in A Modern Guide to Patenting. Challenges of Patenting in the 21st Century, Nicholas Thumm & Knut Blind (eds.), Edward Elgar (Jun. 2025), linkChih-Chieh Yang, IP pledges and the good faith principle in civil law in The Interface of Intellectual Property Law with other Legal Disciplines, Christophe Geiger (eds.), Edward Elgar (May 2025), link Gabriela Lenarczyk, Mateo Aboy, OpenAI's Patent Pledge: A Post-Moderna Analysis, Journal of Intellectual Property Law & Practice 006 (2025), linkChih-Chieh Yang,IP pledges and the good faith principle in civil law in The Interface of Intellectual Property Law with other Legal Disciplines, Christophe Geiger (eds.), Edward Elgar (May 2025), link Jorge L. Contreras, The Prospects for Green Patent Commons in The Environmental Knowledge Commons: Cases and Lessons for Knowledge Sharing, Anjanette Raymond, Scott Shackelford, Jessica Steinberg, and Michael Mattioli (eds.), Cambridge University Press (forthcoming 2025), linkZiming Wang, Patent Pledge and Technological Innovation: The “Good Faith” of Tesla, EPRG Working Paper (2025), link Jorge L. Contreras, Voluntary Intellectual Property Pledges and COVID-19 in Intellectual Property, COVID-19 and the Next Pandemic, Haochen Sun & Madhavi Sunder (eds.), Cambridge University Press (Dec. 2024), link Gabriela Lenarczyk, Timo Minssen, Mateo Aboy, The nature, scope and validity of patent pledges, Journal of Intellectual Property Law & Practice 805, 19(11) (2024), link Gabriela Lenarczyk,Patent pledges na tle polskich instytucji prawnych, ze szczególnym uwzględnieniem licencji otwartej [‘Patent Pledges in the Context of Polish Legal Institutions, with Special Emphasis on Licences of Right’ book written in Polish] Publishing House of ILS PAS (2024), link Gaétan de Rassenfosse, Alfons Palangkaraya, Do Patent Pledges Accelerate Innovation?, Research Policy 52(5), (2023), linkYasuhiro Arai, Patent Pledges: Why Do Corportations Make Patents Available to the Public?, Harvard Program on U.S.-Japan Relations, Occasional Paper Series, (2023), linkEmanuel Slettengren, Lukas Wenger, Patent Pledges in the Automotive Industry, Master’s thesis in Intellectual Capital Management (2023), link Débora Cristina De Andrade Vicente, The Impact of Tesla’s Patent Opening, Master’s thesis in European Master in Law & Economics (2023), linkJorge L. Contreras, No Take-Backs: Moderna’s Attempt to Renege on Its Vaccine Patent Pledge, Bill of Health blog, Aug. 29, 2022, link Richard Li-dar Wang, Chung-Lun Shen, Tung-Che Wu & Wesley Wei-Wen Hsiao, A concise framework to facilitate open COVID pledge of non-disclosed technologies: In terms of non-disclosed patent applications and trade secrets, Journal of the Formosan Medical Association, 121(8), (Aug. 2022), link Jorge L. Contreras, The Open COVID Pledge: Design, Implementation and Preliminary Assessment of an Intellectual Property Commons, 2021 Utah L. Rev. 833 (2021), link Ginevra Assia Antonelli, Maria Isabella Leone, Riccardo Ricci, Exploring the Open COVID Pledge in the fight against COVID-19: a semantic analysis of the Manifesto, the pledgors and the featured patents, R&D Management Special Issue: Providing solutions in emergencies: R&D and innovation...