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opencc-by-4.0Jun 2023View details →

Malware Finances and Operations: a Data-Driven Study of the Value Chain for Infections and Compromised Access

Description The datasets demonstrate the malware economy and the value chain published in our paper, <a href="https://doi.org/10.1145/3600160.3605047">Malware Finances and Operations: a Data-Driven Study of the Value Chain for Infections and Compromised Access</a>, at the 12th International Workshop on Cyber Crime (IWCC 2023), part of the ARES Conference, published by the International Conference Proceedings Series of the ACM ICPS. Using the well-documented scripts, it is straightforward to reproduce our findings. It takes an estimated 1 hour of human time and 3 hours of computing time to duplicate our key findings from MalwareInfectionSet; around one hour with VictimAccessSet; and minutes to replicate the price calculations using AccountAccessSet. See the included README.md files and Python scripts. We choose to represent each victim by a single JavaScript Object Notation (JSON) data file. Data sources provide sets of victim JSON data files from which we've extracted the essential information and omitted Personally Identifiable Information (PII). We collected, curated, and modelled three datasets, which we publish under the <a href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>. 1. MalwareInfectionSet We discover (and, to the best of our knowledge, document scientifically for the first time) that malware networks appear to dump their data collections online. We collected these infostealer malware logs available for free. We utilise 245 malware log dumps from 2019 and 2020 originating from 14 malware networks. The dataset contains 1.8 million victim files, with a dataset size of 15 GB. 2. VictimAccessSet We demonstrate how Infostealer malware networks sell access to infected victims. Genesis Market focuses on user-friendliness and continuous supply of compromised data. Marketplace listings include everything necessary to gain access to the victim's online accounts, including passwords and usernames, but also detailed collection of information which provides a clone of the victim's browser session. Indeed, Genesis Market simplifies the import of compromised victim authentication data into a web browser session. We measure the prices on Genesis Market and how compromised device prices are determined. We crawled the website between April 2019 and May 2022, collecting the web pages offering the resources for sale. The dataset contains 0.5 million victim files, with a dataset size of 3.5 GB. 3. AccountAccessSet The Database marketplace operates inside the anonymous Tor network. Vendors offer their goods for sale, and customers can purchase them with Bitcoins. The marketplace sells online accounts, such as PayPal and Spotify, as well as private datasets, such as driver's licence photographs and tax forms. We then collect data from Database Market, where vendors sell online credentials, and investigate similarly. To build our dataset, we crawled the website between November 2021 and June 2022, collecting the web pages offering the credentials for sale. The dataset contains 33,896 victim files, with a dataset size of 400 MB. Credits Authors <ul> <li>Billy Bob Brumley (Tampere University, Tampere, Finland)</li> <li>Juha Nurmi (Tampere University, Tampere, Finland)</li> <li>Mikko Niemelä (Cyber Intelligence House, Singapore)</li> </ul> Funding This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under project numbers 804476 (SCARE) and 952622 (SPIRS). Alternative links to download: <a href="https://mega.nz/folder/aJwVyIYJ#9SWh-Z3-TpPfjHZeFxbeew">AccountAccessSet</a>, <a href="https://mega.nz/folder/iUQ3RaKB#48ZkXnFYSR0qXLcbkrZLqw">MalwareInfectionSet</a>, and <a href="https://mega.nz/folder/aNYCFCrK#pbDkJL-PNWjn1ABXbtdR4w">VictimAccessSet</a>.

opencc-by-4.0Jun 2023View details →

Raw data: Specialized metabolites accumulation pattern in buckwheat is strongly influenced by accession choice and co-existing weeds

Screening suitable allelopathic crops and crop genotypes that are competitive with weeds can be a sustainable weed control strategy to reduce the massive use of herbicides. In this study, three accessions of common buckwheat Fagopyrum esculentum Moench. (Gema, Kora, and Eva) and one of Tartary buckwheat Fagopyrum tataricum Gaertn. (PI481671) were screened against the germination and growth of the herbicide-resistant weeds Lolium rigidum Gaud. and Portulaca oleracea L. The chemical profile of the four buckwheat accessions was characterised in their shoots, roots, and root exudates in order to know more about their ability to sustainably manage weeds and the relation of this ability with the polyphenol accumulation and exudation from buckwheat plants. Our results show that different buckwheat genotypes may have different capacities to produce and exude several types of specialized metabolites, which lead to a wide range of allelopathic and defence functions in the agroecosystem to sustainably manage the growing weeds in their vicinity. The ability of the different buckwheat accessions to suppress weeds was accession-dependent without differences between species, as the common (Eva, Gema, and Kora) and Tartary (PI481671) accessions did not show any species-dependent pattern in their ability to control the germination and growth of the target weeds. Finally, Gema appeared to be the most promising accession to be evaluated in organic farming due to its capacity to sustainably control target weeds while stimulating the root growth of buckwheat plants.

opencc-byMay 2023View details →

Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - RESULTS DATASET (with Mega Journals)

The dataset contains all the data produced running the research software for the study:"Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta". Disclaimer: these results are not considered to be representative, because we have fount that Mega Journals skewed significantly some of the data. The result datasets without Mega Journals are published <a href="https://zenodo.org/record/8249907">here</a>. Description of datasets: <ul> <li>SSH_Publications_in_OC_Meta_and_Open_Access_status.csv: containing information about OpenCitations Meta coverage of ERIH PLUS Journals as well as their Open Access availability. In this dataset, every row holds data for a Journal of ERIH PLUS also covered by OpenCitations Meta database. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "OC_omid", the internal OpenCitations Meta identifier for the venue; "issn", numbers of publications in each venue; "Open Access", a value to represent if the journal is OA or not, either "True" or "Unknown".</li> <li>SSH_Publications_by_Discipline.csv: containing information about number of publications per discipline (in addition, number of journals per discipline are also included). The dataset has three columns, the first, labeled "Discipline", contains single disciplines of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li>SSH_Publications_and_Journals_by_Country: containing information about number of publications and journals per country. The dataset has three columns, the first, labeled "Country", contains single countries of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li>result_disciplines.json: the dictionary containing all disciplines as key and a list of related ERIH PLUS venue identifiers as value.</li> <li>result_countries.json: the dictionary containing all countries as key and a list of related ERIH PLUS venue identifiers as value.</li> <li>duplicate_omids.csv: a dataset containing the duplicated Journal entries in OpenCitations Meta, structured with two columns: "OC_omid", the internal OC Meta identifier; "issn", the issn values associated to that identifier</li> <li>eu_data.csv: contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "Original_Title", "Country_of_Publication","ERIH_PLUS_Disciplines", "disc_count", the number of disciplines per Journal.</li> <li>eu_disciplines_count.csv: containing information about number of publications per discipline and number of journals per discipline of european countries. The dataset has three columns, the first, labeled "Discipline", contains single disciplines of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li>meta_coverage_eu.csv: contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "OC_omid", the internal OpenCitations Meta identifier for the venue; "issn", numbers of publications in each venue; "Open Access", a value to represent if the journal is OA or not, either "True" or "Unknown".</li> <li>us_data.csv: contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "Original_Title", "Country_of_Publication","ERIH_PLUS_Disciplines", "disc_count", the number of disciplines per Journal.</li> <li>us_disciplines_count.csv: containing information about number of publications per discipline and number of journals per discipline of the United States. The dataset has three columns, the first, labeled "Discipline", contains single disciplines of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li>meta_coverage_us.csv: contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "OC_omid", the internal OpenCitations Meta identifier for the venue; "issn", numbers of publications in each venue; "Open Access", a value to represent if the journal is OA or not, either "True" or "Unknown".</li> </ul>   Abstract of the research:  Purpose: this study aims to investigate the representation and distribution of Social Science and Humanities (SSH) journals within the OpenCitations Meta database, with a particular emphasis on their Open Access (OA) status, as well as their spread across different disciplines and countries. The underlying premise is that open infrastructures play a pivotal role in promoting transparency, reproducibility, and trust in scientific research. Study Design and Methodology: the study is grounded on the premise that open infrastructures are crucial for ensuring transparency, reproducibility, and fostering trust in scientific research. The research methodology involved the use of secondary data sources, namely the OpenCitations Meta database, the ERIH PLUS bibliographic index, and the DOAJ index. A custom research software was developed in Python to facilitate the processing and analysis of the data. Findings: the results reveal that 78.1% of SSH journals listed in the European Reference Index for the Humanities (ERIH-PLUS) are included in the OpenCitations Meta database. The discipline of Psychology has the highest number of publications. The United States and the United Kingdom are the leading contributors in terms of the number of publications. However, the study also uncovers that only 38% of the SSH journals in the OpenCitations Meta database are OA. Originality: this research adds to the existing body of knowledge by providing insights into the representation of SSH in open bibliographic databases and the role of open access in this domain. The study highlights the necessity for advocating OA practices within SSH and the significance of open data for bibliometric studies. It further encourages additional research into the impact of OA on various facets of citation patterns and the factors leading to disparity across disciplinary representation. Related resources: Ghasempouri S., Ghiotto M., & Giacomini S. (2023). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - RESEARCH ARTICLE. <a href="https://doi.org/10.5281/zenodo.8263908">https://doi.org/10.5281/zenodo.8263908</a> Ghasempouri, S., Ghiotto, M., Giacomini, S., (2023).  Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - DATA MANAGEMENT PLAN (Version 4). Zenodo. <a href="https://doi.org/10.5281/zenodo.8174644">https://doi.org/10.5281/zenodo.8174644</a> Ghasempouri, S., Ghiotto, M., Giacomini, S. (2023e). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - PROTOCOL. V.5. (<a href="https://dx.doi.org/10.17504/protocols.io.5jyl8jo1rg2w/v5">https://dx.doi.org/10.17504/protocols.io.5jyl8jo1rg2w/v5</a>)

opencc-byMay 2023View details →

Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - RESULTS DATASET (without Mega Journals)

The dataset contains all the data produced running the research software for the study Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta, a research carried out in the contest of the Open Science course 22/23 at the University of Bologna. Mega Journals have been excluded form the datasets, since we found they were significantly skewing the results, the only datasets not interested by this exclusion are SSH_Publications_in_OC_Meta_and_Open_Access_status and duplicate_omids. The result datasets with Mega Journals included are published <a href="https://doi.org/10.5281/zenodo.8250858">here</a> The Journals excluded from the results are: PLOS ONE (issn:1932-6203), PNAS (issn:1091-6490), Science (issn:1095-9203), Nature(issn:0028-0836). Description of datasets: <ul> <li>SSH_Publications_in_OC_Meta_and_Open_Access_status.csv: containing information about OpenCitations Meta coverage of ERIH PLUS Journals as well as their Open Access availability. In this dataset, every row holds data for a Journal of ERIH PLUS also covered by OpenCitations Meta database. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "OC_omid", the internal OpenCitations Meta identifier for the venue; "issn", numbers of publications in each venue; "Open Access", a value to represent if the journal is OA or not, either "True" or "Unknown".</li> <li>SSH_Publications_by_Discipline.csv: containing information about number of publications per discipline (in addition, number of journals per discipline are also included). The dataset has three columns, the first, labeled "Discipline", contains single disciplines of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li>SSH_Publications_and_Journals_by_Country: containing information about number of publications and journals per country. The dataset has three columns, the first, labeled "Country", contains single countries of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li>result_disciplines.json: the dictionary containing all disciplines as key and a list of related ERIH PLUS venue identifiers as value.</li> <li>result_countries.json: the dictionary containing all countries as key and a list of related ERIH PLUS venue identifiers as value.</li> <li>duplicate_omids.csv: a dataset containing the duplicated Journal entries in OpenCitations Meta, structured with two columns: "OC_omid", the internal OC Meta identifier; "issn", the issn values associated to that identifier</li> <li>eu_data.csv: contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "Original_Title", "Country_of_Publication","ERIH_PLUS_Disciplines", "disc_count", the number of disciplines per Journal.</li> <li>eu_disciplines_count.csv: containing information about number of publications per discipline and number of journals per discipline of european countries. The dataset has three columns, the first, labeled "Discipline", contains single disciplines of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li>meta_coverage_eu.csv: contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "OC_omid", the internal OpenCitations Meta identifier for the venue; "issn", numbers of publications in each venue; "Open Access", a value to represent if the journal is OA or not, either "True" or "Unknown".</li> <li>us_data.csv: contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "Original_Title", "Country_of_Publication","ERIH_PLUS_Disciplines", "disc_count", the number of disciplines per Journal.</li> <li>us_disciplines_count.csv: containing information about number of publications per discipline and number of journals per discipline of the United States. The dataset has three columns, the first, labeled "Discipline", contains single disciplines of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li>meta_coverage_us.csv: contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns:  "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "OC_omid", the internal OpenCitations Meta identifier for the venue; "issn", numbers of publications in each venue; "Open Access", a value to represent if the journal is OA or not, either "True" or "Unknown".</li> </ul>   Abstract of the research:  Purpose: this study aims to investigate the representation and distribution of Social Science and Humanities (SSH) journals within the OpenCitations Meta database, with a particular emphasis on their Open Access (OA) status, as well as their spread across different disciplines and countries. The underlying premise is that open infrastructures play a pivotal role in promoting transparency, reproducibility, and trust in scientific research. Study Design and Methodology: the study is grounded on the premise that open infrastructures are crucial for ensuring transparency, reproducibility, and fostering trust in scientific research. The research methodology involved the use of secondary data sources, namely the OpenCitations Meta database, the ERIH PLUS bibliographic index, and the DOAJ index. A custom research software was developed in Python to facilitate the processing and analysis of the data. Findings: the results reveal that 78.1% of SSH journals listed in the European Reference Index for the Humanities (ERIH-PLUS) are included in the OpenCitations Meta database. The discipline of Psychology has the highest number of publications. The United States and the United Kingdom are the leading contributors in terms of the number of publications. However, the study also uncovers that only 38% of the SSH journals in the OpenCitations Meta database are OA. Originality: this research adds to the existing body of knowledge by providing insights into the representation of SSH in open bibliographic databases and the role of open access in this domain. The study highlights the necessity for advocating OA practices within SSH and the significance of open data for bibliometric studies. It further encourages additional research into the impact of OA on various facets of citation patterns and the factors leading to disparity across disciplinary representation. Related resources: Ghasempouri S., Ghiotto M., & Giacomini S. (2023). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - RESEARCH ARTICLE. <a href="https://doi.org/10.5281/zenodo.8263908">https://doi.org/10.5281/zenodo.8263908</a> Ghasempouri, S., Ghiotto, M., Giacomini, S., (2023).  Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - DATA MANAGEMENT PLAN (Version 4). Zenodo. <a href="https://doi.org/10.5281/zenodo.8174644">https://doi.org/10.5281/zenodo.8174644</a> Ghasempouri, S., Ghiotto, M., Giacomini, S. (2023e). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - PROTOCOL. V.5. (<a href="https://dx.doi.org/10.17504/protocols.io.5jyl8jo1rg2w/v5">https://dx.doi.org/10.17504/protocols.io.5jyl8jo1rg2w/v5</a>)

opencc-by-4.0Aug 2023View details →

A Shortlist of Diamond Open Access Journals for the Faculty of Science at Utrecht University

Context The following shortlist of diamond open-access journals was compiled to increase awareness of alternative scholarly publication models among the six departments of the <a href="https://www.uu.nl/en/organisation/faculty-of-science">Faculty of Science at Utrecht University</a>. The list is relevant to the six disciplines at the Faculty of Science: Biology, Chemistry, Mathematics, Information and Computing Sciences, Physics, and Pharmaceutical Sciences. For this purpose, a "diamond journal" is defined as a journal indexed in the <a href="https://www.doaj.org/">Directory of Open Access Journals (DOAJ)</a> that does not charge an article processing charge (APC).   Contents and Results The Excel file titled “Diamond_journals_faculty_of_science_UU” contains the list of selected diamond journals based on the following criteria: they allow submissions in English, have a plagiarism screening policy, possess an electronic ISSN number, and accept submissions in Biology, Chemistry, Mathematics, Information and Computing Sciences, Physics, and Pharmaceutical Sciences. In this shortlist, 355 journals meet the criteria. Out of these 355 journals, only 29 have received a DOAJ seal, 150 journals are indexed in <a href="https://www.scopus.com/">Scopus</a>, and 94 journals are indexed in <a href="https://mjl.clarivate.com/home">Web of Science</a>. A detailed description of the methods employed to obtain this shortlist can be found in the Word file titled "Methods_and_Results". The raw CSV data has been included under the name "Raw_DOAJ_journal_metadata_2023_07_25".   Limitations The compilers of this shortlist are aware that some current diamond journals could change their status to non-diamond by charging article processing fees at a later stage. Since the journal record is not always updated by the publishers, we strongly recommend the users double-check the latest open access status directly on the journal's homepage (journal URLs are provided in the Excel file). The same applies for Scopus and WOS indexations.

opencc-by-4.0Sep 2023View details →

Watkins natural accessions yellow rust disease resistant scores

The file contains the phenotypic information from field trails conducted in Kenya at the Kenya Agriculture and Livestock Research Organisation (KALRO) and the Ethiopian Institute of Agricultural Research (EIAR).  Data are separated into the three rusts (yellow rust (Yr), stem rust (Sr) and leaf rust (Lr)), although data is not complete at all locations. When possible both seedling and adult plant data is provided. Adult scores include several observation across the growing season. For scoring rust severity, the modified Cobb scale (Peterson et al. 1948) was used to determine the percentage of tissue infected (0-100%) with rust and infection response (S, MS, MR and R, corresponding to susceptible, moderately susceptible, moderately resistant and resistant).  Accession codes relate to Watkins landraces and their country of origin and accession names are indicated. Locations, dates and disease scores are indicated. Missing data is indicated as "-".  For more detailed passport data and access to germplasm visit the John Innes Centre Germplasm Resources Unit (<a href="https://www.seedstor.ac.uk/search-browseaccessions.php?idCollection=39">SeedStor</a>). Additional germplasm resources and populations developed from the Watkins accessions can be found here: <a href="https://wisplandracepillar.jic.ac.uk/">https://wisplandracepillar.jic.ac.uk/</a>

opencc-by-4.0Sep 2023View details →

ACCESS-OM2 1° resolution global repeat decade full forcing interannual simulation data for 1972-2018

This data set contains the full forcing interannual simulation output from the global ocean-sea ice model ACCESS-OM2 in the 1° horizontal configuration over the period 1972-2018. This simulation was branched off from the repeat decade forcing spin-up and alongside the control simulation (see light blue and black lines in Fig. 1c in the publication linked below). The control simulation output can be found here: https://zenodo.org/record/8339578 The output here as well as in the control simulation is saved in sets of ten years (output200, output201, ...) in the ocean/ and ice/ folders as netcdf files. The last output folder contains the data for 2012-2018 with the last four years of this output folder (output204) are again the 1972-1975 period and should be omitted from any analysis. For more information on the spin-up and the model configuration, see the Methods section and Fig. 1 in Huguenin, M.F., Holmes, R.M. & England, M.H. Drivers and distribution of global ocean heat uptake over the last half century. Nat Commun 13, 4921 (2022). https://doi.org/10.1038/s41467-022-32540-51

opencc-zeroOct 2023View details →

NWO and ZonMw Open Access Monitor 2022 - dataset

This is the dataset underlying the report "NWO and ZonMw Open Access Monitor 2022". Openly accessible metadata was used to research if and how publications from research funded by NWO and ZonMw were open access in 2022. 93% of the articles that were detected have been made available open access using one of the available routes (NWO: 93,1%; ZonMw: 92,5%). This is a slight increase compared to 2021 (90%) and 2020 (85%). At least 64% of the included NWO and ZonMw publications of 2022 (3.688 out of 5.763) has been published via Gold, Hybrid, under a transformative agreement, or Green OA, with a CC-BY license and is therefore fully Plan S compliant.

opencc-by-4.0Jan 2020View details →

Data for Research Assessment in the Transition to Open Science. 2019 EUA Open Science and Access Survey Results

This database refers to the data collected by the European University Association (EUA) for its Open Science and Access Survey 2019, which gathered responses from universities and higher education institutions across Europe. The full report published by the association is available at <a href="https://eua.eu/resources/publications/888:research-assessment-in-the-transition-to-open-science.html">https://eua.eu/resources/publications/888:research-assessment-in-the-transition-to-open-science.html</a>. The data included in this database refers only to those universities and higher education institutions that accepted their data to be available in open access (n=174). All information that could lead to the identification of individual universities and higher education institutions was removed from the database (cf. cells highlighted in red). The following files are available: <ul> <li>2019 EUA Open Science and Access Survey</li> <li>Database in the following formats: .xlsx (Microsoft Excel)</li> <li>Survey Codebook: includes information on all the variables and their coding.</li> </ul>

opencc-by-4.0Mar 2019View details →

GenBank accession numbers of the four marker genes and associated voucher specimens/tissues that were used in this study. For more details see Guo et al. (2014). Sequences of species in bold are unpublished and were provided by P. Guo as personal communication in Rediscovery of Andrea's keelback, Hebius andreae (Ziegler & Le, 2006): First country record for Laos and phylogenetic placement

GenBank accession numbers of the four marker genes and associated voucher specimens/tissues that were used in this study. For more details see Guo et al. (2014). Sequences of species in bold are unpublished and were provided by P. Guo as personal communication

Data_supplemental Figure 3_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ

Data of supplemental figure 3 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ Dataset (doi:10.1194/jlr.M092908) contains the original figure as PNG-format (10.1194_jlr.M092908_Fig. S3). Corresponding raw data obtained from liquid scintillation analysis provided as three files in CSV format (31003A-179400_DATE_SK_KB_27Oxysterol_11_6_1-3). All further experiment related information and subsequent data analysis provided as meta-data-file (31003A-179400_DATE_SK_KB_27Oxysterol_11_6_M) as TXT format

Data_Figure 8_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ

Data of figure 8 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ Dataset (doi:10.1194/jlr.M092908) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 8). Corresponding raw data obtained from luminescence measurement analysis (Spectra Max L, Molecular devices, Serial Nr. LU01049) provided as eight files in CSV format (31003A-179400_DATE_SI_KB_27Oxysterol_18_1-2_1-4). All further experiment related information and subsequent data analysis provided as two meta-data-files (31003A-179400_DATE_SI_KB_27Oxysterol_18_1-2_M) as TXT format.

Data_Figure 6_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ

Data of figure 6 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ Dataset (doi:10.1194/jlr.M092908) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 6). Corresponding raw data obtained from docking calculation analysis and calculations provided as four files in TXT format (31003A 179400_DATE_KB_27Oxysterol_19_1-4_1). All further experiment related information and subsequent data analysis provided as four meta-data-files (31003A-179400_DATE_KB_27Oxysterol_19_1-4_M) as TXT format.

Data_Figure 5_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ

Data of figure 5 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ Dataset (doi:10.1194/jlr.M092908) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 5). Corresponding raw data obtained from liquid scintillation analysis provided as seven files in CSV format (31003A-179400_DATE_SK_KB_27Oxysterol_11_4-5_1-4). All further experiment related information and subsequent data analysis provided as two meta-data-file: (31003A-179400_DATE_SK_KB_27Oxysterol_11_4-5_M_1,) as TXT format.

Data_Figure 1_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ

Data of figure 1 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ Dataset (doi:10.1194/jlr.M092908) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 1). Corresponding raw data obtained from LC-MS/MS analysis provided three files in CSV format (31003A-179400_DATE_KB_27Oxysterol_4_1_1-3). All further experiment related information and subsequent data analysis provided as two meta-data-files as TXT format and PDF format.

opencc-by-3.0Feb 2017View details →

Appendix. List of the 28S and 16S rRNA sequences recovered from GenBank. 28S = 28S rRNA GenBank accession number; 16S = 16S rRNA GenBank accession number. in Genetic and morphological evidence for cryptic species in Macrobrachium australe and resurrection of M. ustulatum (Crustacea, Palaemonidae)

Appendix. List of the 28S and 16S rRNA sequences recovered from GenBank. 28S = 28S rRNA GenBank accession number; 16S = 16S rRNA GenBank accession number.

opencc-by-4.0Jul 2020View details →

Austrian Science Fund (FWF) Open Access Compliance Monitoring 2019

I. Executive summary The Austrian Science Fund (FWF), which is Austria's main funding organisation for basic research, encourages and helps all project leaders and project staff members to make their peer-reviewed research results freely available on the Internet. Any exceptions must be clearly indicated and justified. For projects that started after 1 January 2015, open access has been compulsory for all peer-reviewed publications. All principal investigators in FWF-funded projects are obliged to submit a final report within three months of completing their projects. In 2019 all in all 565 final reports were submitted to the FWF, 44 out of them couldn't report publications by now. The publications and other data mentioned in those reports are archived and analysed by the FWF. This report examines the state of compliance with open access requirements on the basis of final project reports submitted in the year 2019. Main findings: -A total of 9.353 publications were listed in the final project reports submitted in 2019. -Of those publications, 7.326 were conclusively identified as peer-reviewed. -Regarding compliance with the FWF's Open Access Policy, the analysis shows that 89% of the peer-reviewed publications that are listed in the submitted final reports of FWF projects in 2019 are openly accessible (2015: 83%, 2016:   92%, 2017: 90%, 2018: 92%). -The most frequently chosen option is hybrid open access (40%). The share of old open access is 19%, the share of green open access 22% and other open access 8%. -The majority of peer-reviewed publications submitted are journal articles (91%), 91% of which are openly accessible. -The lowest rate of compliance with the FWF's Open Access Policy can be found in editions, contributions to edited volumes and monographs (42%). -Although open access is not compulsory for non peer-reviewed publications, 43% of  those publications are freely available through the internet. -The absolute number of publications listed in final reports in 2019 includes 565 publications that are mentioned several times in different projects; however, those repetitions do not ultimately affect the relative share of open access publications (89%). II. Bias Half of the publications were entered in the FWF’s database manually and with utmost care when the final project reports were received. Nevertheless, it is not possible to rule out minor errors entirely. The other half has been submitted to the FWF via a research documentation system (provided by ©Researchfish) in which FWF-funded researchers are able to enter and update their research data on an ongoing basis. The last check of the open access status was performed in January 2020. In some cases, the embargo period may have already expired, and publications labelled other open access in the FWF’s database may now be accessible through green open access. Whenever the status "peer-reviewed" could not be clearly identified according to FWF guidelines, the publications were classified as non peer-reviewed. Openly available non peer-reviewed publications were entered as 'openly available'.

opencc-by-4.0Sep 2020View details →

Genbank accession numbers of sequences used in the phylogenetic analysis

Phylogenetic analysis: Sequences were assembled using Lasergene v15 (DNASTAR, Inc. Madison, USA), and combined with sequences obtained from Genebank

opencc-by-4.0Nov 2020View details →

Corresponding spreadsheet to the Paper 'An intersectional approach to analyse gender productivity and open access: a bibliometric analysis of the Italian National Research Council' submitted to the Scientometric journal by Roberta Ruggieri, Fabrizio Pecoraro and Daniela Luzi from National Research Council, Italy.

Gender equality and Open Access (OA) are priorities within the European Research Area (ERA) and cross-cutting issues in European research program H2020. Gender and openness are also key elements of Responsible Research and Innovation (RRI). However, despite the common underlying targets of fostering an inclusive, transparent and sustainable research environment, both issues are analysed as independent, unrelated topics. This paper represents a first exploration of the inter-linkages between gender and OA analysing the scientific production of researchers of the Italian National Research Council under a gender perspective integrated with the different OA publications modes. A bibliometric analysis was carried out for articles published in the period 2016-2018 and retrieved from the Web of Science. Results are presented constantly analysing CNR scientific production in relation to gender, disciplinary fields and OA publication modes. These variables are also used when analysing articles that receive financial support.  Our results indicate that gender disparities in scientific production still persist in particularly in STEM disciplines (Science, Technology, Engineering and Mathematics), while in medical and agricultural sciences the gender gap is the closest to parity. A positive dynamic toward OA publishing and women scientific production is shown when open disciplines with well-established practices are related to articles supported by funds. A slightly higher women propensity toward OA is shown when considering Gold OA,OA or authorships with women in the first and last article by-line position. Moreover, the prevalence of Italian funded articles with women’s contributions published in Gold OA journals seems to confirm this tendency, especially if considering the week enforcement of the Italian OA policies.