<![CDATA[数据管理平台选型]]>https://dataverse.org/
The Project
The Dataverse Project is an open source web application to share, preserve, cite, explore, and analyze research data. It facilitates making data available to others, and allows you to replicate others' work more easily. Researchers, journals, data authors, publishers, data distributors, and affiliated institutions all receive academic credit and web visibility.

A Dataverse repository is the software installation, which then hosts multiple virtual archives called Dataverse collections. Each Dataverse collection contains datasets, and each dataset contains descriptive metadata and data files (including documentation and code that accompany the data). As an organizing method, Dataverse collections may also contain other Dataverse collections.

The central insight behind the Dataverse Project is to automate much of the job of the professional archivist, and to provide services for and to distribute credit to the data creator. Before the Dataverse Project, researchers were forced to choose between receiving credit for their data, by controlling distribution themselves but without long term preservation guarantees, or having long term preservation guarantees, by sending it to a professional archive but without receiving much credit. The Dataverse Project breaks this bad choice: we put a Dataverse collection (a virtual archive) on your website that has your website's look, feel, branding, and URL, along with an academic citation for the data that gives you full credit and web visibility. Yet, that page of your website is served up by a Dataverse repository, with institutional backing, and long term preservation guarantees. See Gary King. 2007. “An Introduction to the Dataverse Network as an Infrastructure for Data Sharing.” Sociological Methods and Research, 36, Pp. 173–199. Please use this paper to cite the Dataverse Project.

2085fa1b-86cd-4aa1-9a5e-e2e079a7237e-image.png

]]>http://an.forum.genostack.com/topic/834/数据管理平台选型RSS for NodeSat, 13 Jun 2026 09:37:44 GMTSat, 25 Mar 2023 03:47:18 GMT60<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 05:05:21 GMT]]>https://omeka.org/s/docs/user-manual/modules/datarepositoryconnector/

]]>http://an.forum.genostack.com/post/2009http://an.forum.genostack.com/post/2009Sat, 25 Mar 2023 05:05:21 GMT<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 05:06:01 GMT]]>http://ircdl2022.dei.unipd.it/downloads/papers/IRCDL_2022_paper_9.pdf
DALIA: an Open Data repository for the open digital data of the
Bologna CNR Research Area Library

https://ceur-ws.org/Vol-2447/paper1.pdf
Analysis of current RDM applications for the interdisciplinary publication of research data

]]>http://an.forum.genostack.com/post/2008http://an.forum.genostack.com/post/2008Sat, 25 Mar 2023 05:06:01 GMT<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 04:58:35 GMT]]>https://github.com/DSpace/DSpace
(Official) The DSpace digital asset management system that powers your Institutional Repository
wiki.lyrasis.org/display/DSDOC7x/

]]>http://an.forum.genostack.com/post/2007http://an.forum.genostack.com/post/2007Sat, 25 Mar 2023 04:58:35 GMT<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 04:58:18 GMT]]>https://medium.com/analytics-vidhya/comprehensive-study-of-open-data-platforms-a63d702ef0d5
Comprehensive Study of Open Data Platforms
da5c8e5a-bc6d-4117-8b1e-7d1fc6ca9e80-image.png

]]>http://an.forum.genostack.com/post/2006http://an.forum.genostack.com/post/2006Sat, 25 Mar 2023 04:58:18 GMT<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 05:37:17 GMT]]>https://ckan.org/8015976d-38c3-41a6-974f-15afc2b62d9a-image.png
The world’s leading open source data management system.
CKAN is an open-source DMS (data management system) for powering data hubs and data portals. CKAN makes it easy to publish, share and use data. It powers hundreds of data portals worldwide.

https://github.com/CINERGI/jupyter-ckan
https://www.pythonsherpa.com/tutorials/2/
重点看看

]]>http://an.forum.genostack.com/post/2005http://an.forum.genostack.com/post/2005Sat, 25 Mar 2023 05:37:17 GMT<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 04:20:39 GMT]]>https://aaltodoc.aalto.fi/bitstream/handle/123456789/19414/master_Nurmela_Miro_2016.pdf?sequence=1&isAllowed=y
Aalto Data Repository
Research data management, sharing and
publishing in the world of data intensive science

]]>http://an.forum.genostack.com/post/2004http://an.forum.genostack.com/post/2004Sat, 25 Mar 2023 04:20:39 GMT<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 04:07:53 GMT]]>9d3fd2fc-b3cc-4078-921d-0c0ae682f474-image.png
Corporate Linked Data - short: COLID - is a technical solution for corporate environments that provides a metadata repository for corporate assets based upon semantic models. COLID assigns URIs as persistent and global unique identifiers to any resource. The incorporated network proxy ensures that these URIs are resolvable and can be used to directly access those assets. By following the Linked Data principles consequently, the data model of COLID uses RDF and provides the content through a SPARQL endpoint to consumers. This model was developed based on learnings from open standards like dcat and prov-o. Being both a management system for resolvable identifier and an asset catalog, COLID is the core service to realize Linked Data in corporate environments and therefore an essential cornerstone for FAIR data.

10d908f2-682e-4e03-8fbf-03ede5dea7c1-image.png

]]>http://an.forum.genostack.com/post/2003http://an.forum.genostack.com/post/2003Sat, 25 Mar 2023 04:07:53 GMT<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 04:04:55 GMT]]>https://github.com/thehyve/fairspace
Fairspace provides a secure environment for managing research data.
Fairspace
Fairspace is a secure place for managing research data. Research teams have their own workspaces in which they can manage research data collections. Researchers can upload directories and files to data collections. Data access is organised on data collection level. Collections can be shared with other teams or individual researchers. Also, collections can be published for all researchers in the organisation.

Collections and files can be annotated with descriptive metadata. The metadata is stored using the Resource Description Framework (RDF) in an Apache Jena database. For the metadata, a data model can be configured that suits the data management needs of the organisation. The data model is specified using the Shapes Constraint Language (SHACL), see the section on Data model and view configuration. Descriptive metadata entities (e.g., subjects, projects, samples) should be added to the database by a careful process, ensuring that duplicates and inconsistencies are avoided and that all entities have proper unique identifiers. The application provides overviews of the available metadata entities. In the collection browser, researchers can link their collections and files to these entities or add textual descriptions and key words.

]]>http://an.forum.genostack.com/post/2002http://an.forum.genostack.com/post/2002Sat, 25 Mar 2023 04:04:55 GMT<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 04:02:44 GMT]]>https://irods.org/
b0b17c06-6303-4f06-8315-f954c94cd6c8-image.png
https://github.com/irods/irods
0333b1fd-9636-4959-9416-2356e803b000-image.png

]]>http://an.forum.genostack.com/post/2001http://an.forum.genostack.com/post/2001Sat, 25 Mar 2023 04:02:44 GMT<![CDATA[Reply to 数据管理平台选型 on Sat, 25 Mar 2023 03:59:32 GMT]]>https://gen3.org/
9b82c117-1e69-4160-bbe9-f7ac26fbcf57-image.png
Gen3 is a data platform for building data commons and data ecosystems.
The Gen3 platform consists of open-source software services that support the emergence of healthy data ecosystems by enabling the interoperation and creation of cloud-based data resources, including data commons and analysis workspaces. Gen3 aims to accelerate and democratize the process of scientific discovery by making it easy to manage, analyze, harmonize, and share large and complex datasets in the cloud.
f2bceb35-1fee-49fc-965c-9d13b062f9a4-image.png

]]>http://an.forum.genostack.com/post/2000http://an.forum.genostack.com/post/2000Sat, 25 Mar 2023 03:59:32 GMT