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Found 323 result(s)
The Archaeological Map of the Czech Republic (AMCR) is a repository designed for information on archaeological investigations, sites and finds, operated by the Archaeological Institutes of the CAS in Prague and Brno. The archives of these institutions contain documentation of archaeological fieldwork on the territory of the Czech Republic from 1919 to the present day, and they continue to enrich their collections. The AMCR database and related documents form the largest collection of archaeological data concerning the Czech Republic and are therefore an important part of our cultural heritage. The AMCR digital archive contains various types of records - individual archaeological documents (texts, field photographs, aerial photographs, maps and plans, digital data), projects, fieldwork events, archaeological sites, records of individual finds and a library of 3D models. Data and descriptive information are continuously taken from the AMCR and presented in the the AMCR Digital Archive interface.
The DRH is a quantitative and qualitative encyclopedia of religious history. It consists of a variety of entry types including religious group and religious place. Scholars contribute entries on their area of expertise by answering questions in standardised polls. Answers are initially coded in the binary format Yes/No or categorically, with comment boxes for qualitative comments, references and links. Experts are able to answer both Yes and No to the same question, enabling nuanced answers for specific circumstances. Media, such as photos, can also be attached to either individual questions or whole entries. The DRH captures scholarly disagreement, through fine-grained records and multiple temporally and spatially overlapping entries. Users can visualise changes in answers to questions over time and the extent of scholarly consensus or disagreement.
The CancerData site is an effort of the Medical Informatics and Knowledge Engineering team (MIKE for short) of Maastro Clinic, Maastricht, The Netherlands. Our activities in the field of medical image analysis and data modelling are visible in a number of projects we are running. CancerData is offering several datasets. They are grouped in collections and can be public or private. You can search for public datasets in the NBIA (National Biomedical Imaging Archive) image archives without logging in.
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FDAT is a research data repository hosted by the University of Tübingen, designed to facilitate long-term archiving and publication of research data. Managed by the Information, Communication and Media Center (IKM), it primarily caters to the humanities and social sciences, while welcoming researchers from all scientific disciplines at the university. Committed to high-quality data management, FDAT emphasizes the importance of adhering to the FAIR Data Principles, promoting findability, accessibility, interoperability, and reusability of the research data it contains.
<<<!!!<<< This repository is no longer available. >>>!!!>>> NetPath is currently one of the largest open-source repository of human signaling pathways that is all set to become a community standard to meet the challenges in functional genomics and systems biology. Signaling networks are the key to deciphering many of the complex networks that govern the machinery inside the cell. Several signaling molecules play an important role in disease processes that are a direct result of their altered functioning and are now recognized as potential therapeutic targets. Understanding how to restore the proper functioning of these pathways that have become deregulated in disease, is needed for accelerating biomedical research. This resource is aimed at demystifying the biological pathways and highlights the key relationships and connections between them. Apart from this, pathways provide a way of reducing the dimensionality of high throughput data, by grouping thousands of genes, proteins and metabolites at functional level into just several hundreds of pathways for an experiment. Identifying the active pathways that differ between two conditions can have more explanatory power than just a simple list of differentially expressed genes and proteins.
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Created and managed by the Library, DataSpace@HKUST is the data repository and workspace service for HKUST research community. Faculty members and research postgraduate students can use the platform to store, share, organize, preserve and publish research data. It is built on Dataverse, an open source web application developed at Harvard’s Institute for Quantitative Social Science. Using Dataverse architecture, the repository hosts multiple "dataverses". Each dataverse contains datasets; while each dataset may contain multiple data files and the corresponding descriptive metadata.
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O Repositório Aleia é o repositório digital oficial do Ibict para arquivar, publicar, disseminar, preservar e compartilhar os dados digitais de pesquisa produzidos pela comunidade científica Ibict, com a missão de promover, apoiar e facilitar a adoção do acesso aberto aos dados de pesquisa, fomentar novas pesquisas e promover uma Ciência Aberta. Para efeito deste documento, a comunidade científica institucional é aquela constituída por seus servidores, pesquisadores visitantes, bolsistas e alunos do programa de pós-graduação.
Our knowledge of the many life-forms on Earth - of animals, plants, fungi, protists and bacteria - is scattered around the world in books, journals, databases, websites, specimen collections, and in the minds of people everywhere. Imagine what it would mean if this information could be gathered together and made available to everyone – anywhere – at a moment’s notice. This dream is becoming a reality through the Encyclopedia of Life.
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This data repository allows users to publish animal tracking datasets that have been uploaded to Movebank (https://www.movebank.org/ ). Published datasets have gone through a submission and review process, and are typically associated with a written study published in an academic journal. All animal tracking data in this repository are available to the public.
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The arctic data archive system (ADS) collects observation data and modeling products obtained by various Japanese research projects and gives researchers to access the results. By centrally managing a wide variety of Arctic observation data, we promote the use of data across multiple disciplines. Researchers use these integrated databases to clarify the mechanisms of environmental change in the atmosphere, ocean, land-surface and cryosphere. That ADS will be provide an opportunity of collaboration between modelers and field scientists, can be expected.
The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc).
The Tropospheric Ozone Assessment Report (TOAR) database of global surface observations is the world's most extensive collection of surface ozone measurements and includes also data on other air pollutants and on weather for some regions. Measurements from 1970 to 2019 (Version 1) have been collected in a relational database, and are made available via a graphical web interface, a REST service (https://toar-data.fz-juelich.de/api/v1) and as aggregated products on PANGAEA (https://doi.pangaea.de/10.1594/PANGAEA.876108). Measurements from 1970 to present (Version 2) are being collected in a relational database, and are made available via a REST service (https://toar-data.fz-juelich.de/api/v2).
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Data Publication Server Forschungszentrum Juelich is a web server for providing large data sets to the general public. It's main application is publishing data belonging to scientific publications.
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Research Data Finder is QUT’s discovery service for research data created or collected by QUT researchers. Designed to promote the visibility of QUT research datasets, Research Data Finder provides descriptions about shareable, reusable datasets available via open or mediated access.
EDINA delivers online services and tools to benefit students, teachers and researchers in UK Higher and Further Education and beyond.
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We developed a method, ChIP-sequencing (ChIP-seq), combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing to identify mammalian DNA sequences bound by transcription factors in vivo. We used ChIP-seq to map STAT1 targets in interferon-gamma (IFN-gamma)-stimulated and unstimulated human HeLa S3 cells, and compared the method's performance to ChIP-PCR and to ChIP-chip for four chromosomes.For both Chromatin- immunoprecipation Transcription Factors and Histone modifications. Sequence files and the associated probability files are also provided.
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The Life Science Database Archive maintains and stores the datasets generated by life scientists in Japan in a long-term and stable state as national public goods. The Archive makes it easier for many people to search datasets by metadata (description of datasets) in a unified format, and to access and download the datasets with clear terms of use. In addition, the Archive provides datasets in forms friendly to different types of users in public and private institutions, and thereby supports further contribution of each research to life science.
A data repository and social network so that researchers can interact and collaborate, also offers tutorials and datasets for data science learning. "data.world is designed for data and the people who work with data. From professional projects to open data, data.world helps you host and share your data, collaborate with your team, and capture context and conclusions as you work."
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The IDR makes datasets that have never previously been accessible publicly available, allowing the community to search, view, mine and even process and analyze large, complex, multidimensional life sciences image data. Sharing data promotes the validation of experimental methods and scientific conclusions, the comparison with new data obtained by the global scientific community, and enables data reuse by developers of new analysis and processing tools.
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The "Flora of Bavaria" initiative with its data portal (14 million occurrence data) and Wiki representation is primarily a citizen science project. Efforts to describe and monitor the flora of Bavaria have been ongoing for 100 years. The goal of these efforts is to record all vascular plants, including newcomers, and to document threatened or former local occurrences. Being geographically largest state of Germany with a broad range of habitats, Bavaria has a special responsibility for documenting and maintaining its plant diversity . About 85% of all German vascular plant species occur in Bavaria, and in addition it has about 50 endemic taxa, only known from Bavaria (most of them occur in the Alps). The Wiki is collaboration of volunteers and local and regional Bavarian botanical societies. Everybody is welcome to contribute, especially with photos or reports of local changes in the flora. The Flora of Bavaria project is providing access to a research data repository for occurrence data powered by the Diversity Workbench database framework.