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7 results for “intellectual property”
ALL-READY Questionnare on potential drivers and barriers to the adoption of innovation management, open science, and Intellectual Property Rights (IPR) among the members of the Pilot Network
<p><strong>Background & Summary</strong>: </p><p>The ALL-READY project unites a diverse consortium of Research Infrastructures (RI) and Living Labs, instrumental in developing new methodologies and technologies in agroecology. The project focuses on effective management of innovation, adherence to open science principles, and strategic application of Intellectual Property Rights (IPR). Task 6.4 of the project, which concentrates on Innovation and IPR Management, seeks to understand the dynamics influencing the adoption of these practices among its members. Recognizing the need for end-to-end data management, the project emphasizes standardized data collection and management while adhering to FAIR principles.</p><p><strong>Methods</strong>: </p><p>The questionnaire was developed by LifeWatch ERIC to capture data reflecting current practices and perceptions in agroecology. It included 26 questions divided into four sections, focusing on existing practices, potential drivers, and barriers in innovation management, open science, and IPR. The survey was disseminated via an online platform to the ALLREADY Pilot Network, ensuring a representative sample from diverse organizations. The data collection process was closely monitored, and the responses were analyzed using a mixed-methods approach to extract meaningful insights.</p><p><strong>Data Records of the ALLREADY Project Questionnaire</strong>: </p><p>The dataset, collected through an online survey platform, underwent a meticulous process of data preparation, download, formatting, and anonymization. It consists of one text file containing metadata (Readme.txt) and a single CSV file encompassing all questionnaire responses. The dataset provides a comprehensive view of innovation management, open science adoption, and IPR handling within the agroecology sector, particularly among the network of RIs and Living Labs involved in the project.</p><p><strong>Technical Validation of the ALLREADY Project Questionnaire</strong>: </p><p>Several critical steps were taken to ensure the accuracy, reliability, and overall quality of the data collected. This included development and testing of the questionnaire, rigorous monitoring of the data collection process, and thorough checks for data quality and completeness. The representativeness of the sample was analyzed specifically with respect to the Pilot Network rather than the broader population involved in agroecology. Strategies were employed to counter survey fatigue and maintain respondent engagement.</p><p><strong>Usage Notes for the ALLREADY Project Questionnaire</strong>: </p><p>The dataset's proper usage is vital for ensuring the validity and reproducibility of research. Researchers are advised to consider the nature of the data, the representativeness of the dataset, and its generalizability. The dataset allows for comprehensive analysis and integration of different sections, and analysts have the flexibility to handle open and write-in responses according to their research needs. Additional information to facilitate analysis is provided in a separate documentation file.</p><p> </p>
Text-fig. 1. Geographic position of the beaver-bearing sites discussed in this paper. Red triangles – records of Castor, blue dots – records of Trogontherium. Bilz II – Bilzingsleben II, Ehr – Weimar-Ehringsdorf, Mosb 2 – Mosbach 2, Taub – Weimar-Taubach, Teg – Tegelen. (This map was created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri). in Mortality Profiles Of Castor And Trogontherium (Mammalia: Rodentia, Castoridae), With Notes On The Site Formation Of The Mid-Pleistocene Hominin Locality Bilzingsleben Ii (Thuringia, Central Germany)
Text-fig. 1. Geographic position of the beaver-bearing sites discussed in this paper. Red triangles – records of Castor, blue dots – records of Trogontherium. Bilz II – Bilzingsleben II, Ehr – Weimar-Ehringsdorf, Mosb 2 – Mosbach 2, Taub – Weimar-Taubach, Teg – Tegelen. (This map was created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri).
CMAD: A Dataset of Conflicting Marks from the Brazilian Intellectual Property Office
<p>CMAD, an acronym for Conflicting Marks Archive Dataset, is a dataset that has been meticulously organized into pairs of marks (Number of pairs=18,355) involved in conflicts of copyright infringement between word, figurative and mixed marks. Marks sought registration with the National Institute of Industrial Property (INPI) in Brazil, and had their applications denied after analysis by intellectual property specialists.</p>
Research Data Quality Assurance – an intellectual property perspective
<p>The presentation summarizes the intellectual property issues, regarding the second Demonstrator in the FAIR Data Spaces project, Research Data Quality Assurance. It will especially outline the specific copyright law paragraphs, which may be and are important for this demonstrator and the participants in the project.</p>
Data e-commerce AND intellectual property
<p>Data e-commerce AND intellectual property</p>
Gambar Data e-commerce AND intellectual property
<p>Gambar Data e-commerce AND intellectual property</p>
CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models
<p>This repository contains prompts generated by CodeIPPrompt, a platform used to assess potential intellectual property infringement risks associated with the output of code language models. The source code of the platform can be found at our GitHub repository: <a href="https://github.com/zh1yu4nyu/CodeIPPrompt">https://github.com/zh1yu4nyu/CodeIPPrompt</a>. Detailed information regarding the datasets, as well as usage instructions, can be found in the README.md file.</p> <p>The paper has been accepted by International Conference on Machine Learning (ICML) 2023. If you find this work helpful, please cite us as follows:</p> <pre><code class="language-markdown">@inproceedings{yu2023codeipprompt, title={CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models}, author={Yu, Zhiyuan and Wu, Yuhao and Zhang, Ning and Wang, Chenguang and Vorobeychik, Yevgeniy and Xiao, Chaowei}, booktitle={International Conference on Machine Learning}, year={2023}, organization={PMLR} }</code></pre>
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
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DANDI Archive for NWB datasets
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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.