OpenGovIntelligence convincingly proposes a holistic approach for modernization of Public Administration (PA) by exploiting Linked Open Statistical Data (LOSD) technologies.
The concept and approach are outlined down to a sufficiently detailed level, allowing to understand broadly how the actual process will work. The suggested methodology to gather a high quality data through active participation of the society and enterprises in data sharing and in the co-production of innovative data-driven public services is very efficient and appropriate. The objectives are clearly outlined and pertinent overall, and the expected impacts of the project are well addressed.
The proposed work plan is clearly presented. The project itself involves enhanced innovation capacity and integration of new knowledge and the output will generate new knowledge and should have impact in these areas.
The work contents and its structure (work packages) are described in a thoroughly detailed manner, including methodology aspects. The experience accumulated on the various processes involved, and the tools and models can be considered as very valuable. The proposed measures to exploit and disseminate the project results are effective.
The project provides clearly the plan for managing the data generated and collected during the project. The data management plan gives detailed interconnections and interdependencies of OGI Working Packages and Deliverables. It convincingly provides detail about the handling of research data during and after the project, what data will be collected, processed or generated, what methodology and standards will be applied, whether data will be shared/made open and how and how data will be curated and preserved.
The plan involves a good number of (twenty five) data sets from nine different CSA domains. It is very well that the most data sets will be openly provided to the public and half of the data sets will be published as linked data. DCAT and PROV vocabularies will be used to model metadata. It is important that data sets will be preserved after the end of the project on the pilot’s web sites, on web servers or other web-based solutions. Data sets come from thirteen different domains.

OpenGovIntelligence supports six pilot projects to create value from the linked open statistical data. The pilots are in different areas showing the potential applications and possibilities and all have embraced co-creation practices. The pilots connect services that have not been connected before. People are involved that were traditionally not included and insights are created to save public money. It is very good that the pilots provide insights for improving policy-making practices. The results of evaluation process of the six OpenGovIntelligence pilots are very well presented.
Regarding the evaluation methodology, users should accept and use the toolkit and the more users the more impact can be generated. The report on dissemination activities from Year 1 presents good acknowledgement of previously published material and of the work of others has been made. It summarises well the flow of information and deliverables at OGI project. It also includes a plan for future dissemination based on the dissemination activities of Y1.
Project partners engaged with interest groups around relevant themes across target audiences and relevant dissemination events within these groups are included in the dissemination.
The proposed dissemination of the project results is logical. The report on dissemination activities describes well the strategies to communicate with the targeted groups; the promotional materials, online and electronic activities (including social media) and events and networking as well as the plan for the following year’s dissemination.
The promotional materials are to assist in drawing attention to the project and to explaining to the target groups what plan to achieve. It is very good that the website includes a brief description of the vision of the project and links to the following social media sites: Twitter, GitHub, Slideshare and registration to the mailing list (for the newsletter).
It is well decided that public deliverables from the first 12 months are made available via the project website. As well, a mailing list has been set up to support the creation and distribution of newsletters since it provides analytics on how many people receive and read the newsletter. A Twitter account was created which allows to provide timely, up to date news regarding the project and provide and receive other messages regarding innovation in the field of open and linked data. The project has a Slideshare account and GitHub account, too. Besides, there is summary of social media activities and international conferences to present OpenGovIntelligence as well as webinars are planned.
It is an important part of the dissemination process to promote interoperability of data and tools, and involvement of the project in relevant standardisation initiatives.
A substantial dissemination has been carried out in Year 1 of the OpenGovIntelligence Project. Some aspects of the initial targets for Y1 including a MOOC, synergies with other projects and google analytics to track online presence accurately on the project webpage will take place in Y2.
It is very good that measurement criteria of planned dissemination and exploitation activities
and academic publications as well as indicative list of industrial and practice publications are presented.
The project’s pilots aiming at validation and proof of the usability and effectiveness of the LOSD Innovation Ecosystem are well described and show the innovation potential of the project. Thanks to the pilots will be developed services at both national and local level to tackle societal and Public Administration challenges in various problem areas.
It is very important that will be issued practical recommendations and tutorials for public authorities regarding various issues of opening-up and exploiting statistical data; and to provide training to public administrations, businesses and citizens on the use of services developed by the OpenGovIntelligence project. Therefore, the work carried out in the project helps advance the field further for practitioners.
Training of OpenGovIntelligence stakeholders i.e. public administrations, businesses and citizens in order to increase their capacity in using the services developed by the project is important part of the process. Workshops will be organized for this reason for each of the three key stakeholders of the OpenGovIntelligence project, namely public administrations, businesses and citizens. It is promising that OpenGovIntelligence aims at issuing and providing public authorities with a number of detailed practical recommendations and tutorials regarding political, institutional, technical, legal and social issues of opening-up and exploiting statistical data. It also includes a deliverable documenting recommendations and tutorials.
Research findings will be put into practice by integrating them into innovative products and services. It is a good approach to host the data management plan on the project website, and a part of it will be made publicly accessible through the project’s dissemination activities.
It is well reported on how any potential ethical issues in OpenGovIntelligence will be addressed by the partners involved in field work activities, and in data collection and management.

From a general standpoint, the project is well laid out in the overall context, and the relation to the general Work Plan is well described, but the "top level" objectives of the proposal need to be better described. As well, the outputs of the project could have been more clearly linked to the general top level objectives.
Most WPs are well defined, with a suitable breakdown into tasks, but milestones and risks could also be planned so as to facilitate an affective progress monitoring.
Evidence of excellence in overall impact assessments could be further elaborated.