Selecting and submitting the good examples

The network of collaborating experts is based on competent organisations and indiviudals, also displayed on the Partners page. Professionals participate in the collection and submission of good innovation examples, who regularly work in the field, close to the practice of production and processing in agriculture, in daily contact with practitioners both in the private and public sector, academia, research and extension.


The main types of innovations managed in the system:

  1. technical
  2. social
  3. organisational
  4. process 
  5. product

Related papers by network members:

The criteria for agricultural innovations for smallholders and family farms in the FAO-REU region / 2018 / Andrew Fieldsend

The criteria for collection, validation and management of data about agricultural innovations for smallholders and family farms in the FAO-REU region / 2018 / Laszlo Gabor Papocsi

Interoperability and open data

The SHIP template describing innovation examples combines different metadata stuctures, including the the use of standards such as Dublic Core or FAO's AGROVOC, as well as most of FAO's  good practice template and other structures. This makes it possible to achieve a certain level of interoperability with other platforms, by publishing the entries in Open Data format, so that the other systems can more easily access and reuse our content. 

Technical information is under preparation how to access the data.

We also plan to integrate our services with other open data providers who have relevant content about innovation for smallholders and family farmers.  

WeAreNet is a member of the GODAN partnership network.

Data validation

The control of input data compliance with expected content, structure and quality is maintained during the SHIP input precess.
Data validation contains several consecutive steps to provide data cleaning to ensure data quality.

  1. Data content. The descriptive part of the innovation example or the proposed innovative solution is evaluated, according to the technical guideline which covers the main points of criteria. 
  2. Data structure. Once the data input has passed validation and evaluation of the content, the next step is to check the structural correctness by format validation of each input field, the permitted syntax, value limits, length, (min,/max), and other constrains. The structural validation of the input form ensures the compliance with standard schemas – such as for instance the Dublin Core or controlled vocabularies for subject keywords such as AGROVOC.


Short guide for innovation data input

  1. In order to access the innovation input form, registration of user account is required on the platform.
  2. Input form can only be accessed after login.
  3. Explanation about short summary of expected content for each input field is provided in tooltip by clicking on the question mark and opening a bubble textbox besides the name of the field. 
  4. Mandatory fields are indicated with asterisk (*). The input form cannot be submitted until all mandatory fields are filled out. After submit without all mandatory fields filled out, the missing parts are highlighted with pink borderline.
  5. Submitted form can be re-opened for further edits, changes or corrections by the owner of the entry, i.e. the logged in user who first created it. All of the fields can be modified, inlcuding multiple ones and attachments.
  6. The entry will be published for visitors and other users after data validation and approval by the content superviser.
  7. If needed, it is possible to extend some of the SHIP category lists, for example the Main category list. For further information contact the system admin at
  8. Published entry can be accesed online, exporting the full data sheet in PDF format, and in Open Data format.