MELODA 0.202 Methodology for assessing released data of opendata sources
The aim of MELODA (MEthodology for reLeasing Open DAta) is to provide a tool that will accelerate the release of information to society, mainly from the public sector but also from the private sphere.
Its use is focused on the maximum use of released information including commercial uses, mixing with private sources, etc. So that legal issues about information are considered as well as technical and accessibility issues.
This methodology is aimed at those public and private entities that are releasing data and want to maximize the use of data published under a free reuse scheme.
We release new versions of this methodology in http://gobernamos.com check it out.
To be operational MELODA must obtain a figure by assessing the available information of a data source (the same information that any user could reach). This requirement restricts the number of dimensions of analysis.
In this version MELODA analyses three dimensions:
Accessibility to the information
For each dimension to be analyzed 5 stages of maturity are considered.
In this five stages other considerations (i.e. Restriction of malicious use of informaTion, misuse, requirements to include the last update’s date, etc are not included).
Attrirbution to the original source is always considered as a must.
Data sources in this stage:
Either will reserve the copyright of data, thus restricting unauthorized use
Either those entities require of an non-online authorisation to use the information (i.e. A form that has to be manually answered fits this category).Stage 2. Private use only
Data sources in this stage will allow the use of the data without approval processes but only for private uses. (non-commercial)
Data sources in this stage will allow reuse of data but they do not allow commercial uses of the information reuse.
(i.e. For a blog, for a non-profit organisation)
Data sources in this stage will allow reuse of data, including the commercial reuse.
(i.e. For any company in order to create new visualization of data)
Data sources in this stage will only ask re-users the attribution of the data.
I.e. releasing with CC BY.
Data sources in this stage are release on proprietary standards. Other open formats but not suitable for reutilization will be considered closed as well. The definition of open standard can be found in national level legislation.
Eg xls, pdf, doc, shp, etc.
Data sources in this stage are published on open standards but as individual files.
i.e. eg, csv, txt, odb, odt, ods, etc.
Data sources in this stage includes those which release information as open standards in individual files but with available explanatory information about the contents of the files.
i.e. csv, odb, odt, ods, etc with additional information about size, data type, range of registers of the file.
Data sources in this stage includes those which release information accessible item by item through some technical mechanism (API, individual URI, etc). Additional information about the content of the data source is not available.
i.e. rdf without additional instructions
Data sources in this stage includes those which release information accessible on individual basis through some open technical mechanism (open API, individual URI, etc). Additional information about the content of the data source is available.
I.e. rdf with additional documentation
Access to information requires a non-automatic approval process for access to data information or to register data in a manual form.
Access to information via the web, but requires user interaction to select the data source.
Access to information via the web, but allows each of the datasets to be accessed individually, or through a shortened URL, or by specific parameters in the query call.
Access to information via the web, but allows each of the datasets to be accessed individually, or through a shortened URL, or by specific parameters in the query call and includes the date of last data update.
Access to information provides access to specific data of the dataset, either by calling a documented API or through a query language of data sources