INESC TEC
INESC TEC
INESC TEC
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Gestão da Informação e Sistemas de Informação

INESC TEC

About Area

The Information Management and Information Systems (IMIS) area conducts R&D activities focused on the design, implementation, and evaluation of advanced information systems. Core research fields include Information Retrieval, Human Information Interaction, Research Data Management, and Data Infrastructures. Our work addresses key scientific, technical, and social challenges in data representation, enhancing interoperability and fostering deeper understanding of complex data. Moreover, we enhance human information interaction through comprehensive user studies, interaction analysis, user-centered interface design, and advanced eye-tracking technologies, ensuring systems effectively meet user needs. IMIS actively promotes Open Data and Open Science principles, facilitating broad collaboration and transparent knowledge dissemination. Application sectors span Cultural Heritage, Health, Media, and the Public Sector, highlighting significant impact and opportunities for innovative partnerships.

Flagship Projects

EPISA

The National Archive of Torre do Tombo, TT in the sequel, is the backbone of the Portuguese institutional memory, managed by DGLAB, the public administration partner in EPISA. It holds the most relevant cultural heritage collection, largely digitized and accessed both by history researchers and by laypeople from all the Portuguese-speaking countries and beyond. The vast amounts of archival description metadata help them find and contextualize the documents they seek. Being at the forefront of the archival world, TT designed its online description system 20 years ago, according to the standards by the International Council of Archives (ICA). Metadata in TT is mainly composed by textual descriptions of the context and contents of the documents. Meanwhile, the archival assets evolved to encompass growing amounts of born-digital information and the interoperability requirements of cultural heritage repositories grew. A new generation of description tools is needed that includes libraries, archives and museums (LAM), and is more fine grained, more flexible and specially more machine-actionable. These are the characteristics of linked open data (LOD) in semantic networks and preliminary work in TT led to the choice of CIDOC Conceptual Reference Model (CRM)(ISO, 2014), a standard developed in the museums community. The conceptual model of CIDOC CRM is a graph where nodes are entities and edges are relations. The huge step represented by such a paradigm shift raises many issues, some of which this project is devoted to solve. The first problem is the effective migration between the ICA and the CIDOC CRM standard, requiring both the use of existing crosswalks and the inference of the new relations with semi-automated methods. The second problem is the support to description, with tools that automate part of the generation of the more complex CIDOC CRM metadata records. The third has to do with interfaces for both human users and machines, improving user access to archives and promoting interoperability with both archives and global semantic networks. The role of TT as a large archival institution (it integrates the headquarters in Lisbon and the majority of the district archives) and also as a regulator for the state, municipal and private archives, ensures the impact of the project results in case the paradigm shift becomes a rule. Furthermore, the extensive record of innovation of TT makes it a respected voice in the ongoing debate on the archival description evolution. Three main impacts are expectable from the project. The proposed change in cultural heritage metadata will give users a better knowledge of the repository and an improved tool for more precise and richer retrieval. The second impact is a stronger presence in the aggregators, mainly in Europeana, that already uses a similar description approach. The third impact is the potential to deal with metadata assets in different platforms, from Excel files to archival description systems, and thus contribute to the integration in the Digital Archive of the Public Administration of diverse administrative as well as research assets.

Entity and Property Inference for Semantic Archives

StopPropagHate

StopPropagHate uses artificial intelligence to help detect and reduce hate speech in online news media. It’s important for news organisations to instigate online discussion, but dealing with the immediacy of user feedback is not an easy task – especially when discussion turns offensive. Using StopPropagHate’s API supported by machine learning techniques, news organisations can automatically identify hate speech within comments, but also predict the likelihood of a news piece to generate such comments in the first place.

Automatic hate speech detection in online news media