Digital Asset Management Systems » History » Version 1
Steve Welburn, 2012-08-08 02:32 PM
1 | 1 | Steve Welburn | h1. Digital Assets Management (DAM) Software |
---|---|---|---|
2 | 1 | Steve Welburn | |
3 | 1 | Steve Welburn | Digital Assets Management (DAM) Software |
4 | 1 | Steve Welburn | |
5 | 1 | Steve Welburn | NOTE: Apparently Queen Mary has an institutional repository (although only for papers at the moment), called "QMRO":https://qmro.qmul.ac.uk/jspui/ (Queen Mary Research Online). It is built on "DSpace":http://www.dspace.org/ . In DSpace, one can create "Communities", which can be for example a Department (e.g. C4DM). It might be a possible option, but it will probably require some customisation of the DSpace installation to accommodate the kind of data produced at C4DM. |
6 | 1 | Steve Welburn | |
7 | 1 | Steve Welburn | Requirements: OpenSource, free, extensible, widely used and actively maintained, versioning |
8 | 1 | Steve Welburn | Plus: easy to integrate with Soundsoftware |
9 | 1 | Steve Welburn | |
10 | 1 | Steve Welburn | http://www.opensourcedigitalassetmanagement.org/ |
11 | 1 | Steve Welburn | http://www.rsp.ac.uk/ |
12 | 1 | Steve Welburn | |
13 | 1 | Steve Welburn | # "Fedora Commons":http://fedora-commons.org/ |
14 | 1 | Steve Welburn | #* Pros: Store all types of content and its metadata, Multiple, customer driven front-ends (e.g. Drupal), Provide RDF search (SPARQL), Access data via Web APIs (REST/SOAP), Many storage options (database and file systems), Versioning support |
15 | 1 | Steve Welburn | #* Cons: relatively complex implementation and deployment process when compared with other alternatives, Java |
16 | 1 | Steve Welburn | #* Examples: "Ensemble":http://ensemble.ljmu.ac.uk/wp/ , https://wiki.duraspace.org/display/FCCommReg/Fedora+Commons+Registry |
17 | 1 | Steve Welburn | # "DSpace":http://www.dspace.org/ |
18 | 1 | Steve Welburn | #* Pros: developed by HP/MIT, Supports Communities, highly configurable and includes a flexible workflow for applying metadata to assets that will suit complex metadata, used in other projects (DRYAD, Edinburgh DataShare) |
19 | 1 | Steve Welburn | #* Cons: no versioning support (planed for the next major release), complex implementation, no support for Drupal front-end |
20 | 1 | Steve Welburn | #* Examples: "QMRO aka Queen Mary Research Online":https://qmro.qmul.ac.uk/jspui/ , DRYAD":http://datadryad.org/about , Edinburgh "DataShare":http://www.ed.ac.uk/schools-departments/information-services/services/research-support/data-library/data-repository/service-background , http://www.dspace.org/whos-using-dspace |
21 | 1 | Steve Welburn | # "NotreDAM":http://www.notre-dam.org/ |
22 | 1 | Steve Welburn | #* Pros: easier to set up than Fedora and Dspace, supports many formats and metadata |
23 | 1 | Steve Welburn | #* Cons: seems not very advanced in the development, versioning planed for next releases |
24 | 1 | Steve Welburn | #* Examples: ? |
25 | 1 | Steve Welburn | # "ResourceSpace":http://www.resourcespace.org/ |
26 | 1 | Steve Welburn | #* Pros: powerful, extensible, PHP based, widely used |
27 | 1 | Steve Welburn | #* Cons: not sure if supports versioning, more media-oriented |
28 | 1 | Steve Welburn | #* Examples: ? |
29 | 1 | Steve Welburn | # "Mercurial LargeFilesextension":http://mercurial.selenic.com/wiki/LargefilesExtension |
30 | 1 | Steve Welburn | #* Pros: already part of Mercurial, can be easily integrated with sound software.co.uk |
31 | 1 | Steve Welburn | #* Cons: not a specific DAM, does not support metadata, searches etc. explicitly |
32 | 1 | Steve Welburn | #* Examples: soundsoftware? |
33 | 1 | Steve Welburn | # "Artifactory":http://www.jfrog.com/products.php |
34 | 1 | Steve Welburn | #* Pros: Easy to set up |
35 | 1 | Steve Welburn | #* Cons: Not a DAM, just a repository |
36 | 1 | Steve Welburn | #* Examples: ? |
37 | 1 | Steve Welburn | # "EPrints":http://www.eprints.org/ |
38 | 1 | Steve Welburn | #* Pros: apparently easy to set up and manage, integrated front-end interface, extensible (Perl), used by more than 200 organisations, long development (since 2001), University of Southampton |
39 | 1 | Steve Welburn | #* Cons: very strong focus on scientific publications, although it can be used for research data |
40 | 1 | Steve Welburn | #* Examples: "Essex-RDR":http://www.data-archive.ac.uk/about/projects/essex-rdr , http://www.eprints.org/exemplar.php |
41 | 1 | Steve Welburn | # "Zentity":http://research.microsoft.com/en-us/projects/zentity/ |
42 | 1 | Steve Welburn | #* Pros: strong support (Microsoft), seems to be flexible, supports open standards |
43 | 1 | Steve Welburn | #* Cons: .NET, Powershell, not many users |
44 | 1 | Steve Welburn | #* Examples: "Homecoming Scotland":http://homecoming09archive.qmu.ac.uk/ |
45 | 1 | Steve Welburn | # "DataVerse":http://www.thedata.org |
46 | 1 | Steve Welburn | #* Pros: made specifically for managing datasets, linking them to publications, and sharing them; developed by Harvard University, supports conversion to open formats, versioning, persistent URI, different levels of access to data, can link to other dataverse networks, integrates with "OpenScholar":http://openscholar.harvard.edu/ for website creation (based on Drupal) |
47 | 1 | Steve Welburn | #* Cons: ? |
48 | 1 | Steve Welburn | #* Examples: "IQSS Harvard University":http://dvn.iq.harvard.edu/dvn/ |
49 | 1 | Steve Welburn | |
50 | 1 | Steve Welburn | Other options to make datasets available online: |
51 | 1 | Steve Welburn | * "Public Data Sets on Amazon AWS":http://aws.amazon.com/publicdatasets/ :Public Data Sets on AWS provides a centralized repository of public data sets that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge for the community, and like all AWS services, users pay only for the compute and storage they use for their own applications. The "Million Song Dataset":http://labrosa.ee.columbia.edu/millionsong/ can be found here. |
52 | 1 | Steve Welburn | * "Infochimps":http://www.infochimps.com/ : offers datasets (free and payed) and API to access datasets for applications. The Million Song Dataset is also available here hosted on AWS) |
53 | 1 | Steve Welburn | * "UCI Machine Learning Repository":http://archive.ics.uci.edu/ml/index.html : a repository for datasets from the University of California Irvine. Again, the Million Song Dataset (divided into subsets) will be soon available here. |
54 | 1 | Steve Welburn | * MARL (Music and Audio Research Lab at NYU) uses "git":http://git-scm.com/ to distribute their new chord transcription ground truth datasets. |