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1,307 results for “libraries”
Mnemosine Digital Library Functionality
<p>Source: </p> <p><em><span><span> </span>Mnemosine </span></em><span>and <em>Clavy</em>: applications for the development of specific libraries for teaching and research. Office for the Transfer of Research Results (</span><span><a href="https://www.ucm.es/otri/complutransfer-mnemosine-y-clavy-aplicaciones-para-la-gestacion-de-bibliotecas-especificas-para-la-docencia-y-la-investigacion"><span>OTRI</span></a></span><span>) <a href="https://www.ucm.es/otri/complutransfer-mnemosine-y-clavy-aplicaciones-para-la-gestacion-de-bibliotecas-especificas-para-la-docencia-y-la-investigacion">https://www.ucm.es/otri/complutransfer-mnemosine-y-clavy-aplicaciones-para-la-gestacion-de-bibliotecas-especificas-para-la-docencia-y-la-investigacion</a></span></p>
RECETOX Exposome HR-[EI+]-MS library
<p>The RECETOX Mass Spectrum Reference Libraries is a collection of MS spectra collected from authentic compounds. Each library comprises the spectra in MSP format and an accompanying SDF database of compounds. The collection is shared under terms & conditions of <a href="https://creativecommons.org/licenses/by-nc/4.0/">CC-BY-NC</a>.</p> <p>The RECETOX Exposome HR-[EI+]-MS library is a collection of mostly anthropogenic compounds. Spectra were acquired at 70 eV on Thermo Fisher Q Exactive™ GC Orbitrap™ GC-MS/MS at 60000 resolving power.</p>
RECETOX Metabolome HR-[EI+]-MS library
<p>The RECETOX Mass Spectrum Reference Libraries is a collection of MS spectra collected from authentic compounds. Each library comprises the spectra in MSP format and an accompanying SDF database of compounds. The collection is shared under terms & conditions of <a href="https://creativecommons.org/licenses/by-nc/4.0/">CC-BY-NC</a>.<br> <br> The RECETOX Metabolome HR-[EI+]-MS library is a collection of mostly endogoenous compounds from MetaSci Human Metabolite Library. Analytes underwent methoximation/silylation prior to acquisition. Spectra were acquired at 70 eV on Thermo Fisher Q Exactive™ GC Orbitrap™ GC-MS/MS at 60000 resolving power.</p>
NIR/SWIR Spectral Library of Plastic-Substrate Mixtures
<p>NIR/SWIR spectra of substrate-plastic mixtures at varying concentrations</p> <p>Plastics include polyethylene (PE), polyethylene terephthalate (PET), polylactic acid (PLA), polypropylene (PP), polyvinyl chloride (PVC), and styrene-butadiene rubber (SBR)</p> <p>Substrates included 3 soils (Bu5, W6, TG), crushed cement (C), oak leaf powder (V), and water (DIW)</p> <p>Concentrations of 0% (pure substrate), 0.15%, 1.5%, 5%, 15%, 50%, and 100% (pure plastic)</p> <p>Datasets are in .csv format for reflectance spectra, absorbance spectra, absorbance 1st derivative, and absorbance 2nd derivative. Reflectance spectra are also included as .hdr and .sli for ease of importing into ENVI or other hyperspectral image processing software. Additionally, raw ASD spectra and the python script for processing are included for custom spectral processing or analyses.</p>
A Study of Undefined Behavior Across Foreign Function Boundaries in Rust Libraries
<p>Developers rely on the static safety guarantees of the Rust programming language to write secure and performant applications. However, Rust is frequently used to interoperate with other languages which allow design patterns that conflict with Rust’s evolving aliasing models. Miri is currently the only dynamic analysis tool that can validate applications against these models, but it does not support finding bugs in foreign functions, indicating that there may be a critical correctness gap across the Rust ecosystem. We conducted a large-scale evaluation of Rust libraries that call foreign functions to determine whether Miri’s dynamic analyses remain useful in this context. We used Miri and an LLVM interpreter to jointly execute applications that call foreign functions, where we found 46 instances of undefined or undesired behavior in 37 libraries. Three bugs were found in libraries that had more than 10,000 daily downloads on average during our observation period, and one was found in a library maintained by the Rust Project. Many of these bugs were violations of Rust’s aliasing models, but the latest Tree Borrows model was significantly more permissive than the earlier Stacked Borrows model. The Rust community must invest in new, production-ready tooling for multi-language applications to ensure that developers can detect these errors.</p>
MS2Query pre-trained datasets needed for library matching
<p>The models, embeddings, sqlite file with metadata and classifiers identifiers needed for running MS2Query (https://github.com/iomega/ms2query)</p>
Information literacy in the area of Library and Information Science. A bibliometric analysis in Latin America, from the Lens database (2001-2020).
<p>The results of scientific production on ALFIN (2001-2020) in the areas of Library and Information Science are shown. All BIC journals were identified from Latindex. Then it was verified whether these journals were contained in the following databases: Web of Science (Core Collection and Scielo Citation Index), Scopus, Lens and Dimensions. The Lens database was chosen for retrieving records on ALFIN and performing the bibliometric analysis, as it has the highest coverage of BIC journals in Latindex. The trend and growth of scientific production were evaluated according to authors and year of publication; the productivity of authors was analyzed using Lotka's Law and the dispersion of the literature according to Bradford's Law. The degree, index and coefficient of collaboration were determined and collaboration networks were identified according to authors. The results show that scientific production on ALFIN in Latin America, reached a peak between 2017 and 2018, presenting a decrease from 2019 onwards. It was also observed that the production, collaboration between authors and the number of journals is predominantly Brazilian.</p>
Citizen science at public libraries: Data on librarians and users perceptions of participating in a citizen science project in Catalunya, Spain
<p>As libraries struggle to keep pace with the changing societal landscape, emerging practices such as citizen science (CS) initiatives are being incorporated to reinforce the idea of public libraries as gathering, meeting, and collaboration spaces within the context of shared community and shared learning resources. However, there is little empirical evidence of whether the most open and participatory ways that CS puts forward can converge with and be nurtured by the essence of public libraries. Also, the roles of librarians and users in the ‘next generation public library’ have been under-developed. As the number of CS initiatives at public libraries grows, so does the need to collect evidence on the impact and the capacity of assimilation of CS practices. The data describes librarians and users' perceptions of participating in a citizen science project. Two hands-on activities for librarians of the Barcelona Network of Public Libraries were implemented. One was a training course for 30 librarians from 24 libraries which allowed them to envisage citizen science implementation in each library. The second activity consisted in the co-creation of a citizen social science project. 40 library users, 7 librarians from 3 different cities, and professional scientists, were involved. The data on librarians and users' perception was collected through participant observation, surveys, and a focus group to identify strengths and challenges of implementing citizen science at public libraries. The data covers librarians and users attitudes towards citizen science, their motivations to participate, their perceived ability to implement a citizen science project (as for librarians) or to contribute to science (as for library users), and the participants intention to keep engaged with citizen science, drawing on the Theory of Planned Behavior. Responses to closed-ended survey questions are analyzed at a descriptive level. The qualitative feedback from the focus group and the open-ended survey question on motivations is subjected to a thematic analysis. The data offers interesting insights to identify opportunities and challenges of implementing citizen science at public libraries, contributing to the debate over the public library's mission as local community hub.</p> <p>The dataset is formed by 5 tables:</p> <ol> <li>Librarians_pre.csv: data on librarians profiles, attitudes towards citizen science, expected impact of the project and self-efficacy collected at the beginning of the Citizen Science Lab.</li> <li>Librarians_post.csv: data on librarians profiles, attitudes towards citizen science, perceived impact of the project and self-efficacy collected at the end of the Citizen Science Lab.</li> <li>Users_first_phase.csv: data on users profiles, motivation, attitudes towards the library, confidence to perform scientific tasks and self-efficacy collected at the beginning of the Science and Citizen Action.</li> <li>Users_second_phase.csv: data on users profiles and motivation collected at the middle of the Science and Citizen Action.</li> <li>Users_last_phase.csv: data on users profiles, attitudes towards the library, confidence to perform scientific tasks and perceived impact of the project collected at the end of the Science and Citizen Action.</li> </ol> <p><strong>Citizen Science Lab Questionnaire (Librarians_pre)</strong></p> <table> <tbody> <tr> <td> <p><strong>Personal information</strong></p> </td> </tr> <tr> <td> <p>1. [rol_1] What is your role at the library?</p> </td> <td> <ul> <li>Director</li> <li>Library technician</li> <li>Support technician</li> <li>Service support</li> </ul> </td> </tr> <tr> <td> <p>2. [years_1] How long have you been working at the library?</p> </td> <td> <ul> <li>2 or less</li> <li>3 to 5 years</li> <li>6 to 10 years</li> <li>11 to 20 years</li> <li>more than 20 years</li> </ul> </td> </tr> <tr> <td> <p>3. [back_1] Do you have a scientific background?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p>4. [know_1] Have you already heard about citizen science?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p>5. [part_1] Have you already participated in a citizen science project?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p><strong>Attitudes towards users engagement</strong></p> </td> </tr> <tr> <td> <p>6. [att_lib_pre1] Do you believe that library users are able to participate in a citizen science project?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> <p>7. [att_lib_pre2] Do you believe that library users will commit to participating in a citizen science project?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> <p><strong>Expected impacts</strong></p> </td> </tr> <tr> <td> <p>8. [exp_lib_pre] To what extent do you believe that citizen science may bring positive impacts to your library?</p> <p> </p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> <p><strong>Self-efficacy</strong></p> </td> </tr> <tr> <td> <p>9. [se_lib_pre1] Right now, do you feel able to recommend any citizen science project to library users?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p>10. [se_lib_pre2] Right now, do you feel able to implement yourself and lead a citizen science project?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> </tbody> </table> <p><strong>Citizen Science Lab Questionnaire (Librarians_post)</strong></p> <table> <tbody> <tr> <td> <p><strong>Personal information</strong></p> </td> </tr> <tr> <td> <p>1. [years_2] How long have you been working at the library?</p> </td> <td> <ul> <li>2 or less</li> <li>3 to 5 years</li> <li>6 to 10 years</li> <li>11 to 20 years</li> <li>more than 20 years</li> </ul> </td> </tr> <tr> <td> <p>2. [back_2] Do you have a scientific background?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p>3. [sat_1] To what extent does the project meet your initial expectations?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> <p><strong>Attitudes towards users engagement</strong></p> </td> </tr> <tr> <td> <p>4. [att_lib_post1] Do you believe that library users will commit to participating in a citizen science project?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> <p>5. [att_lib_post2] What are/could be the potential barriers to users engagement in citizen science?</p> </td> <td> <p>[open]</p> </td> </tr> <tr> <td> <p><strong>Perceived impact</strong></p> </td> </tr> <tr> <td> <p>6. [imp_lib] What do you believe that citizen science may bring to public libraries and users?</p> <p>1 [Not at all] …… 5 [Totally]</p> <p> </p> </td> <td> <p>a. Knowledge of the scientific process</p> <p>b. New connections among participants </p> <p>c. Fun</p> <p>d. New knowledge of the local environment</p> <p>e. Scientific evidence on a common concern</p> <p>f. Social cohesion</p> <p>g. Positive attitudes towards science</p> <p>h. Willingness to learn</p> <p>i. Critical thinking and self-efficacy</p> </td> </tr> <tr> <td> <p><strong>Self-efficacy</strong></p> </td> </tr> <tr> <td> <p>8. [se_lib_post1] Right now, do you feel able to recommend any citizen science project to library users?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p>9. [se_lib_post2] Right now, do you feel able to implement yourself and lead a citizen science project?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> <p><strong>Intention to keep engaged</strong></p> </td> </tr> <tr> <td> <p>10. [eng_lib] To what extent are you motivated to keep engaged with citizen science?</p> <p> </p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> </tbody> </table> <p> </p> <p><strong>Science and Citizens Action Focus group guide (Librarians)</strong></p> <p><strong>Opening questions</strong></p> <p><strong>1.</strong> To start with…. Are you satisfied with the project?</p> <p><strong>Probe</strong><strong>:</strong> Yes, no, why? Was it fun/interesting/challenging/enriching….</p> <p><strong>2.</strong> Do you feel you have learned something new?</p> <p><strong>Probe</strong><strong>:</strong> About your library’s environment, users, science and citizen science... Is there anything special that you will take with you after the project?</p> <p><strong>Reflections on the cocreation process</strong></p> <p><strong>3.</strong> At what time during the project have you felt most comfortable?</p> <p><strong>Probe:</strong> For example, has it been easier to lead the activity and/or involve and retain the community? Did you find it entertaining?</p> <p><strong>4.</strong> At what time during the project have you felt less at ease?</p> <p><strong>Probe</strong><strong>:</strong> What was challenging during the cocreation process?</p> <p><strong>5.</strong> To what extent do you feel more capable of implementing and leading a citizen science project in your library right now?</p> <p><strong>Probe: </strong>For example, in the case of both more crowdsourcing and of cocreated projects that actively involve the community</p> <p><strong>Reflections on the perceived impact</strong></p> <p><strong>6. </strong>To what extent does the project meet your initial expectations?</p> <p><strong>Probe</strong><strong>:</strong> in line with what you discussed at the beginning of the project, you expected it to promote participation, new connections among participants, improve the library perceptions and stimulate the participants’ critical thinking...Do you think that citizen science may meet these expectations?</p> <p><strong>Reflections on citizen science at public libraries</strong></p> <p><strong>7.</strong> To what extent can citizen science (in its most ‘extreme’ form of participation) be imagined as an activity within the library that promotes more active user participation?</p> <p><strong>Probe</strong><strong>:</strong> Through for example cocreation, experimentation, and hands-on learning activities...</p> <p><strong>8. </strong>Do you think that the activity has brought new knowledge? What new knowledge has the activity brought from your perspective?</p> <p><strong>Probe</strong><strong>:</strong> Knowledge of the scientific process, knowledge of the community or new users...</p> <p>9. What could be the opportunities and barriers of introducing citizen science at public libraries? And the barriers?</p> <p><strong>Probe:</strong> Like for example improving the perception of the library, actively involving certain users...What could be the ‘return’ for the community? What impact can citizen science projects have on making the environment more dynamic from libraries?</p> <p><strong>10. </strong>More generally, what could be the ‘added value’ of the introduction of citizen science within the library’s range of activities?</p> <p><strong>Probe:</strong> Is it a fun activity that promotes socialization, for example? Or that allows to generate new knowledge? Or that highlights the library’s social value? Or, also, that may offer new uses and new roles to the library? Can it foster a sense of community with the library as a connector? What other impacts can be generated in your environment?</p> <p><strong>Closing</strong></p> <p><strong>11.</strong> Do you see yourselves the next year, implementing a citizen science project as part of the library’s range of activities? And adopting an existing one?</p> <p><strong>Probe: </strong>Are you motivated to get more involved with citizen science projects? What kind of projects? What level of user involvement do you expect? What barriers do you see to users’ involvement? What benefits and opportunities do you think you can bring to the library?</p> <p><strong>12.</strong> We have now reached the end of the discussion. Anyone want to add anything else?</p> <p><strong>Science and Citizens Action Questionnaire (Users_first_phase)</strong></p> <table> <tbody> <tr> <td> <p><strong>Personal information</strong></p> </td> </tr> <tr> <td> <p>1. [gen_1] Are you..?</p> </td> <td> <ul> <li>Woman</li> <li>Man</li> <li>NA</li> </ul> </td> </tr> <tr> <td> <p>2. [years_3] How old are you?</p> </td> <td> <ul> <li>18-25</li> <li>26-35</li> <li>36-45</li> <li>46-55</li> <li>56-65</li> <li>66+</li> </ul> </td> </tr> <tr> <td> <p>3. [rol_2] What is your role at the library?</p> </td> <td> <ul> <li>Library user not associated with local associations</li> <li>Library technician</li> <li>Member of a local association</li> <li>Representative of public administrations</li> <li>Representative of the private sector</li> <li>Others:</li> </ul> </td> </tr> <tr> <td> <p>4. [back_3] Do you have a scientific background?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p>5. [part_2] Have you already participated in a citizen science project?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p><strong>Motivations to participate</strong></p> </td> </tr> <tr> <td> <p>6. [mot_us] What did motivate you to participate in the project?</p> </td> <td> <p>[open]</p> </td> </tr> <tr> <td> <p><strong>Attitudes towards the library</strong></p> </td> </tr> <tr> <td> <p>7. [att_us_pre1] To what extent do you believe that your library is responsive to the community needs?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> <p>8. [att_us_pre2] To what extent to you believe your library is able to face local challenges based on users' active participation?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> <p><strong>Confidence to perform scientific tasks</strong></p> </td> </tr> <tr> <td> <p>9. [conf_us_pre] To what extent do you feel able to contribute to perform the following scientific tasks:</p> <p>1 [Not at all] …… 4 [Totally]</p> </td> <td> <p>a. Formulate the research question</p> <p>b. Data collection</p> <p>c. Analysis and interpretation of the results</p> <p>d. Propose concrete actions based on scientific evidence</p> </td> </tr> <tr> <td> <p><strong>Self-efficacy</strong></p> </td> </tr> <tr> <td> <p>10. [se_us_pre] To what extent do you feel able to positively contribute to the library and your community?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> </tbody> </table> <p><strong>Science and Citizens Action Questionnaire (Users_second_phase)</strong></p> <table> <tbody> <tr> <td> <p><strong>Personal information</strong></p> </td> </tr> <tr> <td> <p>1. [gen_3] Are you..?</p> </td> <td> <ul> <li>Woman</li> <li>Man</li> <li>NA</li> </ul> </td> </tr> <tr> <td> <p>2. [years_5] How old are you?</p> </td> <td> <ul> <li>18-25</li> <li>26-35</li> <li>36-45</li> <li>46-55</li> <li>56-65</li> <li>66+</li> </ul> </td> </tr> <tr> <td> <p>3. [rol_4] What is your role at the library?</p> </td> <td> <ul> <li>Library user or technician not associated with local associations</li> <li>Member of a local association</li> <li>Representative of public administrations</li> <li>Representative of the private sector</li> <li>Others:</li> </ul> </td> </tr> <tr> <td> <p>3. [back_5] Do you have a scientific background?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p>4. [mot_us2] To what extent are you motivated to carry out the experiment?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> </tbody> </table> <p><strong>Science and Citizens Action Questionnaire (Users_last_phase)</strong></p> <table> <tbody> <tr> <td> <p><strong>Personal information</strong></p> </td> </tr> <tr> <td> <p>1. [gen_2] Are you..?</p> </td> <td> <ul> <li>Woman</li> <li>Man</li> <li>NA</li> </ul> </td> </tr> <tr> <td> <p>2. [years_4] How old are you?</p> </td> <td> <ul> <li>18-25</li> <li>26-35</li> <li>36-45</li> <li>46-55</li> <li>56-65</li> <li>66+</li> </ul> </td> </tr> <tr> <td> <p>3. [rol_3] What is your role at the library?</p> </td> <td> <ul> <li>Library user or technician not associated with local associations</li> <li>Member of a local association</li> <li>Representative of public administrations</li> <li>Representative of the private sector</li> <li>Others:</li> </ul> </td> </tr> <tr> <td> <p>3. [back_4] Do you have a scientific background?</p> </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> <p>4. [part_3] To how many cocreation sessions have you participated?</p> </td> <td> <ul> <li>None</li> <li>1</li> <li>2</li> <li>3</li> </ul> </td> </tr> <tr> <td> <p>5. [sat_2] To what extent are you satisfied with the experiment?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> <p><strong>Attitudes towards the library</strong></p> </td> </tr> <tr> <td> <p>6. [att_us_post] To what extent do you believe that the project has positively changed your perception of the library?</p> </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> <p><strong>Confidence to perform scientific tasks</strong></p> </td> </tr> <tr> <td> <p>7. [conf_us_post] To what extent do you feel able to contribute to perform the following scientific tasks:</p> <p>1 [Not at all] …… 5 [Totally]</p> </td> <td> <p>a. Formulate the research question</p> <p>b. Data collection</p> <p>c. Analysis and interpretation of the results</p> <p>d. Propose concrete actions based on scientific evidence</p> </td> </tr> <tr> <td> <p><strong>Perceived impact</strong></p> </td> </tr> <tr> <td> <p>8. [imp_us] What do you believe that citizen science may bring to public libraries and users?</p> <p>1 [Not at all] …… 5 [Totally]</p> <p> </p> </td> <td> <p>a. Knowledge of the scientific process</p> <p>b. New connections among participants </p> <p>c. Fun</p> <p>d. New knowledge of the local environment</p> <p>e. Scientific evidence on a common concern</p> <p>f. Social cohesion</p> <p>g. Positive attitudes towards science</p> <p>h. Willingness to learn</p> <p>i. Critical thinking and self-efficacy</p> </td> </tr> </tbody> </table> <p> </p>
Library of price and performance data of domestic and commercial technologies for low-carbon energy systems
<p>This library consists of extensive price and performance data of commercially available technologies for low-carbon energy systems on the UK market, including domestic and commercial applications. All information is obtained from published manufacturer datasheets and pricelists. The library contains useful information for energy-system and technology modellers in their efforts to capture the techno-economic characteristics of different technology options, minimise uncertainties and suggest reliable system- and technology-design strategies.</p> <p>The data analysis shows how technology characteristics vary with component choice, technology size and to capture the spread of values found between different suppliers, which can be used to determine uncertainty bounds on key performance indicators. Fitting techniques can be used to determine relationships arising from the collected data, infer values for which data are not available and quantify the related variability in technology characteristics.</p> <p>This work was conducted by members of the <a href="https://www.imperial.ac.uk/clean-energy-processes/">Clean Energy Processes (CEP) Laboratory</a> and is part of Project 2 of the <a href="https://www.imperial.ac.uk/energy-futures-lab/idles/">Integrated Development of Low-Carbon Energy Systems (IDLES)</a> project. IDLES brings together researchers across Imperial College London and partner organisations and companies to provide the evidence needed to facilitate a cost-effective and secure transition to a low-carbon future. The overarching aim of Project 2 is: (i) to characterise current and new/future technologies in terms of cost and performance to provide evidence for whole-energy system modelling; and (ii) to extend the capabilities of whole-energy-system models so that they can, apart from optimising energy network infrastructures, provide information to manufacturers about the optimal choice of materials, components and the design of key technologies.</p> <p>The library will be updated regularly as more data regarding existing and new technologies are collected.</p>
ePharmaLib: A Versatile Library of e-Pharmacophores to Address Small-Molecule (Poly-)Pharmacology
<p><em><strong>The peer-reviewed publication for this dataset has now been published in Journal of Chemical Information and Modeling, and can be accessed here: <a href="https://doi.org/10.3390/epidemiologia2030024">https://doi.org/10.1021/acs.jcim.1c00135</a>. Please cite this when using the dataset.</strong></em></p> <p><em>Reverse pharmacophore screening (parallel screening) is an efficient and cost-effective computational method used to study the polypharmacology of drugs. To this end, we created ePharmaLib: a collection of 15,148 energetically optimized, structure-based pharmacophores (e-pharmacophores) , with 3 to 8 features constituting 12.6%, 17.9%, 20.9%, 17.1%, 10.6% and 20.9%, respectively. The pharmacophores were generated from the 3D macromolecular structures of druggable proteins in complex with diverse ligands, retrieved from the sc-PDB database (<a href="http://bioinfo-pharma.u-strasbg.fr/scPDB/">http://bioinfo-pharma.u-strasbg.fr/scPDB/</a>). ePharmaLib can either be used with the Schrödinger’s PHASE program (<a href="https://www.schrodinger.com/products/phase">https://schrodinger.com/products/phase</a>) or PHARAO, also known as Align-it (<a href="https://silicos-it.be.s3-website-eu-west-1.amazonaws.com/software/align-it/1.0.4/align-it.html">https://silicos-it.be.s3-website-eu-west-1.amazonaws.com/software/align-it/1.0.4/align-it.html</a>). Designed for drug discovery research, this ready-to-use library could dramatically expedite drug discovery by revealing novel molecular interactions of drugs in an efficient and cost-effective manner.</em></p>
MetaPro: a web-based metabolomics application for MS data batch inspection and library curation
<p>MetaPro is a metabolomics web analysis platform built on the Aird data format with high performance and high compression. This platform includes a series of necessary functions for metabolomics analysis such as quality control, retention time(RT) alignment, target analysis, untarget analysis, manual integration, batch inspection, MS2 library establishment, and report export, providing efficient data analysis, management and visualization capabilities</p>
Datasample - Social Media Analytics and Metrics of Facebook Performance of Libraries, Archives and Museums
<p>The current dataset describes Facebook pages performance for 220 Libraries, Archives and Museums from all over the world. The performance is measured through 9 different social media metrics. That is, number of posts, link-posts, picture-posts, video-posts, total reactions, comments and shares, number of reactions, comments per post and reactions per post. The data harvesting process has been conducted through the use of FanPageKarma API. The gathered metrics and their values depict the performance for each Facebook page in a time-period of 30 days.</p>
InpactorDB: A Plant classified lineage-level LTR retrotransposon reference library for free-alignment methods based on Machine Learning
<p>LTR retrotransposons are mobile elements that make up the major part of most plant genomes. Their identification and annotation via bioinformatics approaches represent a major challenge in the era of massive plant genome sequencing. In addition to their involvement in the variation in genome size, these elements are also associated in the function and structure of different chromosomal regions and in the alteration of the function of coding regions, among others. Several plant retrotransposon sequence databases of LTR retrotransposons are available with public access such as PGSB, RepetDB or restricted access such as Repbase. Although they are useful for approaches to identify LTR-RTs in new genomes by similarity, the elements of these databases are not classified down to the lineage/family level. with great depth. </p> <p>Here, we present InpactorDB a semi-curated dataset composed of 130,511 elements from 195 plant genomes (belonging to 108 plant species), classified down to the lineage level. This data set has been used to train two deep neural networks (one fully connected and one convolutional) for fast classification of elements. Used in lineage-level classification approaches, we obtain a score above 98% of F1-score, precision and recall. </p> <p>In order to classify elements of the ‘LTR_STRUC’ and ‘EDTA’ datasets, we used the methodology proposed by Inpactor, which uses homology-based strategy with known coding domains belonging to LTR-RTs. We utilized the RexDB domain library as reference. LTR-RTs were classified into superfamilies, Gypsy (RLG) or Copia (RLC) and sub-classified into lineages according to the similarities of five different amino acid reference domains (GAG, AP, RT, RNAseH, and INT domains). In addition, we applied filters to remove keep only intact elements:</p> <p>1) to remove predicted elements with domains from two different superfamilies (i.e. Gypsy and Copia),</p> <p>2) or elements with domains belonging to two or more different lineages,</p> <p>3) to remove elements with lengths different than those reported by Gypsy Database (GyDB) with a tolerance of 20%,</p> <p>4) to delete incomplete elements which has less than three identified domains, and</p> <p>5) to remove elements with insertions of TE class II (reported in Repbase). </p> <p>The final non-redundant version of InpactorDB consists of 67,305 LTR retrotransposons. Both redundant and non-redundant versions of InpactorDB are available in Fasta format in which sequences have identifiers with the following general Identification code:</p> <p>>Superfamily-Lineage-plant_family-specie-source-length-ID,</p> <p>Where Superfamily can is either RLC (for Copia) or RLG (for Gypsy), Lineage/family follows following the RexDB nomenclature, source (can be Repbase, RepetDB, PGSB, LTR_STRUC or EDTA datasets), length, and ID, is a unique number which identify each element inside the InpactorDB.</p>
Interview data on history-oriented theologians' recommendations for visualizations in libraries
<p>Results of an interview study with the target group "history-oriented theologians" on their recommendations for visualizations in libraries. Recommendations were retrieved with the method SHIRA (Structured Hierarchical Interviewing for Requirement Analysis)[1]. This allows generating concrete qualities and implementation suggestions out of abstract qualities.</p> <p>Feel free to contact me if you have any questions!</p> <p> </p> <p> [1] M. Hassenzahl, R. Wessler, and K.-C. Hamborg. Exploring and understanding product qualities that users desire. Conference on Human-Computer Interaction IHM-HCI’2001, 2, 2001.</p>
Interview data on experts' recommendations for visualizations in libraries
<p>Results of an interview study with twelve experts on their project processes and their recommendations for visualizations in libraries. Recommendations were retrieved with the method SHIRA (Structured Hierarchical Interviewing for Requirement Analysis)[1]. This allows generating concrete qualities and implementation suggestions out of abstract qualities.</p> <p>The file contains two pages: On the first, a meta-model was constructed out of all identified steps during library visualization projects. On the second, all SHIRA suggestions were gathered and analyzed.</p> <p>Feel free to contact me if you have any questions!</p> <p> </p> <p> [1] M. Hassenzahl, R. Wessler, and K.-C. Hamborg. Exploring and understanding product qualities that users desire. Conference on Human-Computer Interaction IHM-HCI’2001, 2, 2001.</p>
Research Artefact: An Empirical Study of React-Library Related Issues via Stack Overflow
<p>This research artifact accompanies the paper titled "An Empirical Study of React-Library Related Issues via Stack Overflow." It is a comprehensive repository that includes the collected dataset containing 447,542 React-related Stack Overflow question posts, as well as 384 representative samples obtained randomly. The primary objective of this artifact is to facilitate the replication of our dataset for researchers and allow them to utilize it for further investigations and research purposes.</p>
DGL Data Library
<p><em>Please find an up-to-date version of this document at <a href="https://github.com/DigitalGeographyLab/data-library">https://github.com/DigitalGeographyLab/data-library</a></em></p> <p> </p> <p><strong>Digital Geography Lab Data Library</strong></p> <p>Over the years, the Digital Geography Lab (DGL) has collected data from a variety of open data sources, that now reside in the group’s common database. These data collection efforts have been carried out by different members of the DGL and different contributors, at different points in time, and with different focus and coverage. This is especially true for data from social media, data from other online platforms, and volunteered geographic information.</p> <p>This document is an effort in honouring everybody who contributed to the DGL data library, and to keep record of which datasets have once been used in DGL research and publications. It also should serve as a document to cite when referring to data that are re-used in a new study. For these purposes, please use the following citation:</p> <blockquote> <p>DGL data contributors, 2022: <em>Digital Geography Lab Data Library</em>. DOI:10.5281/zenodo.6425396</p> </blockquote> <p> </p> <pre><code>@misc{dgl_data_contributors_digital_2022, title = {Digital Geography Lab Data Library}, author = {{DGL data contributors}}, date = {2022}, doi = {10.5281/zenodo.6425396} }</code></pre> <p><br> </p> <p><strong>Data contributors</strong></p> <p>- Tuuli Toivonen<br> - Henrikki Tenkanen<br> - Olle Järv<br> - Vuokko Heikinheimo<br> - Maria Salonen<br> - Tuomo Hiippala<br> - Elias Willberg<br> - Claudia Bergroth<br> - Tuomas Väisänen<br> - Jeison Londoño Espinosa<br> - Age Poom<br> - Joel Jalkanen<br> - Kerli Müürisepp<br> - Oleksandr Karasov<br> - Christoph Fink<br> - Enrico Di Minin<br> - Anna Hausmann<br> - Matthew Zook<br> - Håvard Aagesen<br> - Samuli Massinen<br> - Tatu Leppämäki<br> - Marisofia Nurmi<br> - Sonja Koivisto<br> - Aleksi Toikka<br> - Bryan Vallejo<br> - Laura Centore<br> - Ainokaisa Tarnanen<br> - Jaani Lahtinen<br> - Perttu Saarsalmi<br> - Timo Jaakkola<br> - Juha Järvi</p> <p><strong>Data sources</strong></p> <p>The Digital Geography Lab Data Library contains data compiled from the following sources:</p> <p>- Twitter<br> - flickr<br> - Instagram<br> - OpenStreetMap<br> - Wikipedia<br> - Helsinki Region Infoshare</p> <p>Note that some of the data has been purged to meet legal and ethical requirements, and that other data sets have been preserved in an anonymised form.</p>
Peptide Mass Fingerprint Library of Monoclonal Murine anti-SARS-CoV-2 Antibodies
<p>The dataset contains fingerprints of monoclonal antibodies that can be used to identify the antibodies by using the open-source software ABID 2.0 <a href="https://bam.de/ABID">https://bam.de/ABID</a><br> More information can be found in the publication where this data was used to rapidly distinguish between 35 monoclonal murine Anti-SARS-CoV-2 antibodies: <a href="https://doi.org/10.3390/antib11020027">https://doi.org/10.3390/antib11020027 </a></p>
ProtNAff: Protein-bound Nucleic Acid filters and fragment libraries
<p>This archive contains data obtained by running the <strong>ProtNAff</strong> pipeline (<a href="https://github.com/isaureCdB/ProtNAff">https://github.com/isaureCdB/ProtNAff</a>) and used to perform the analyses described in the original ProtNAff paper. The input list of PDB IDs was obtained in October 2021 by searching all PDB structures that contain protein chains and RNA chains but no DNA, and where the resolution is less than 3 A or where the method is NMR. The ribosomes are removed from this database due to their size.</p> <p>The files provided are:</p> <p>- structures.json : the database containing <strong>metadata and parsing data for all the protein-RNA structures</strong> from the input list</p> <p>- fragments_clust.json : the list and description of all the trinucleotide fragments extracted from those structures</p> <p>- trinucl_clust1A_allatom: the <strong>all-atom coordinates of the trinucleotide fragment library</strong> , i.e. the centers of 1A clusters such that each initial fragment has a RMSD of less than 1A from at least one of those centers.</p> <p>- trinucl_clust1A_ATTRACT: the coordinates of the trinucleotide fragment library , but reduced into ATTRACT <strong>coarse-grained representation</strong> (Setny and Zacharias, NAR 2011).</p>
Chenopodium Oxford Nanopore libraries
<p>Oxford Nanopore libraries of four diploid Chenopodium species (2n=2x=18), <em>C. acuminatum</em>, <em>C. iljinii</em>, <em>C. pamiricum</em> and <em>C. suecicum. </em>The 50,000 longest ON reads in each library. </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.