Outreach
The work in the IntelComp project showed that the ability to leverage vast amounts of data from various sources (both new and conventional) and the potential to utilise cutting-edge Artificial Intelligence Models (including deep learning, Natural Language Processing, and Large Language Models) tailored for Science, Technology and Innovation policy, will equip policymakers with a versatile toolbox. This includes flexible, interactive visualisations and dashboards that provide valuable insights to inform decision-making.
This policy brief shows the first results of the IntelComp platform: the use cases of Energy, as a key element for mitigating climate change, and of science and technology in Artificial Intelligence. They indicate that IntelComp has successfully produced topic models and automatic classifiers to address the granularity challenge.
This document translates the conceptual framework of the IntelComp platform into concrete measurements and data sources. It also explains the services of the platform which are required for the calculation of the identified measurements.
This document provides a first look at the rationale and the potential of using Artificial Intelligence-based tools in Science, Technology and Innovation policy. In addition, this deliverable deals with the challenges these tools face.
This deliverable provides a framework of Science, Technology and Innovation policy for the IntelComp platform, which will be tested in three domains: artificial intelligence, climate change/blue economy and health/cancer.
This document describes the solutions implemented for the impact evaluation in the IntelComp platform, and some experimental work related to it. The deliverable is structured in two well differentiated parts: Part I describes the components of the Graph Analysis Toolbox that allow the calculation of impact indicators, and a case study concerning the identification of research results (publications) associated with a collection of project proposals (which is a key component for the impact evaluation of the projects). Part II focuses on the description of the procedures implemented for the inclusion of aggregate indicators in the STI Viewer, one of the end user tools of the IntelComp platform
The Graph Analysis toolbox is a number of software components for the computation, processing and analysis of graph collections.
Although the toolbox can be used generally for any type of data sources, it is specially oriented to the processing and analysis of large corpora of scientific documents.
The key modules of the toolbox are:
- Import data from files or SQL / Neo4J databases, for the generation or the enrichment of graphs.
- Generation and processing of graphs.
- Management and processing structured collections of graphs (named supergraphs)
The IntelComp time analysis and trend detection service focuses on the dynamic analysis of the scientific literature, tracking the evolution of disciplines and capturing the emergent research areas or new topics and quantifying their trends. To this end, we automatically expand the Field of Science Taxonomy exploited by the IntelComp classifiers (documented in Deliverable D3.4) to a more fine-grained level by adding three additional levels (Level 4-Level 6) and provide a dynamic mechanism that properly adjusts the lower levels of the hierarchy as new research topics emerge.
This service is a set of ready-to-use automatic classifiers and a collection of training scripts that can be executed to create classifiers for new taxonomies.
The classifiers have been trained on the following taxonomies: Fields of Science and Technology (FOS); Nomenclature of Economic Activities (NACE) Rev.2; International Patent Classification (IPC); and the Sustainable Development Goals (SDGs).
This document provides information about the python-based Topic Modeling toolbox, one of the main services in IntelComp, including a review of the techniques implemented, the description of the architecture of the software, and manuals for the users of the tool.
The system for subcorpus generation (domain classifier) is aimed at facilitating the classification of all documents from a given corpus according to a category that is specified by the user (an expert in the domain).
The Intelcomp NLP pipeline can be defined as a collection of tools that apply the requested transformations to unstructured textual data, which will be used by the Intelcomp services (document classification, subcorpus generation, topic modeling, etc.) as a preliminary step to process the datasets of interest.
The IntelComp tools are the software “products” of the IntelComp platform that directly target its end users. Through those, the output of metadata and text analysis performed by IntelComp’s “algorithmic” components reaches its audience. The products are three:
- STI Viewer: An analytics visualisation tool that offers Science, Technology and Innovation (STI) measurements.
- Evaluation Workbench: A tool designed for Public Administration officials to assist them in the assessment of grant proposals.
- STI Policy Participation Portal: A portal, empowered by the STI Viewer and survey tools, that allows policy stakeholders to provide structured and informed feedback on STI policy.
The IntelComp H2020 project adopts a living labs methodology and involves external public administrations and policy stakeholders (civil society organisations, academia, and industry organisations) to:
(i) co-design and co-create IntelComp tools and services.
(ii) validate the resulting platform through the co-creation of science, technology, and innovation policies in three different domains: R&D in artificial intelligence, climate change and cancer research, for specific use cases of the IntelComp tools and services.
This document captures the main results and activities of the IntelComp Artificial Intelligence Living Lab.
The IntelComp H2020 project adopts a living labs methodology and involves external public administrations and policy stakeholders (civil society organisations, academia, and industry organisations) to:
(i) co-design and co-create IntelComp tools and services.
(ii) validate the resulting platform through the co-creation of science, technology, and innovation policies in three different domains: artificial intelligence, climate change and cancer research, for specific use cases of the IntelComp tools and services.
This document constitutes the final report of IntelComp Living Lab Climate Change and aims to
introduce the framework of the Living Lab, record its activities, and present the results.
The IntelComp H2020 project adopts a living labs methodology and involves external public administrations and policy stakeholders (civil society organisations, academia, and industry organisations) to:
(i) co-design and co-create IntelComp tools and services.
(ii) validate the resulting platform through the co-creation of science, technology, and innovation policies in three different domains: artificial intelligence, climate change and cancer research, for specific use cases of the IntelComp tools and services.
This document presents the main results and activities of the IntelComp Health Living Lab, which focuses on cancer research.
This document is the final monitoring report on the execution of the Dissemination and Communication Plan of the IntelComp project. It describes the channels and materials developed to reach the main target groups of the Plan: Public Administration, Society, Industry and Academia. It also takes stock of the specific actions and events carried out during the project to accomplish the Plan’s objectives: raise awareness of the project; disseminate its results; and initiate the engagement and support of external actors to IntelComp.
This deliverable explains how ethical and legal issues have been managed along the project. It considers how the legal aspects of the data affect the interaction of IntelComp with content providers (commercial or public) and users. It also adresses the ethics requirements of the project, in particular, the involvement of human participants.
This document serves as the updated Data Management Plan (DMP) for the IntelComp project that has been created using the OpenAIRE ARGOS DMP service (argos.openaire.eu). It presents an in-depth overview of the project's data management practices, in compliance with the Horizon 2020 policy and FAIR guidelines. The DMP details the types of datasets collected, generated, and used, with a particular focus on the datasets created in the project (output datasets), and describes the management methods implemented in the IntelComp STI Data Space.