Abstract
In this article, we present solutions to visualize and interact with linked data in historical archives considering three different scenarios: search, individual record view, and creation of relationships. The created solutions were designed using nonfunctional mockups and were based on the CIDOC-CRM model, a model created and applied in the museums community liable to be extended to other cultural heritage institutions, being our solutions an application of this model to archives. A sample of 20 archival professionals was selected to evaluate the elements included in the proposed solutions. The evaluation sessions consisted in structured interviews supported by an introductory video and a survey. The think-aloud protocol was applied during the sessions. We conducted both a quantitative and qualitative analysis to the collected answers. From this analysis, we conclude that the majority of the participants showed great receptivity to the solutions presented and recognized many benefits in the application of linked data. Our contributions also include an exploratory study of some existing linked data systems, giving particular attention to their visualization and interaction modes.

Abstract
In this paper we describe the EPISA Platform, a technical infrastructure designed and developed to support archival records management and access using linked data technologies. The EPISA Platform follows a client-server paradigm, with a central component, the EPISA Server, responsible for storage, reasoning, authorization, and search; and a frontend component, the EPISA ArchClient, responsible for user interaction. The EPISA Server uses Apache Jena Fuseki for storage and reasoning, and Apache Solr for search. The EPISA ArchClient is a web application implemented using PHP Laravel and standard web technologies. The platform follows a modular architecture, based on Docker containers. We describe the technical details of the platform and the main user interaction workflows, highlighting the abstractions developed to integrate linked data in the archival management process. The EPISA Platform has been successfully used to support research and development of linked data use in the archival domain in the context of the EPISA project. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

Abstract
In this work, we targeted the search engine of a sports-related website that presented an opportunity for search result quality improvement. We reframed the engine as a Federated Search instance, where each collection represented a searchable entity type within the system, using Apache Solr for querying each resource and a Python Flask server to merge results. We extend previous work on individual search term weighing, making use of past search terms as a relevance indicator for user selected documents. To incorporate term weights we define four strategies combining two binary variables: integration with default relevance (linear scaling or linear combination) and search term frequency (raw value or log-smoothed). To evaluate our solution, we extracted two query sets from search logs: one with frequently submitted queries, and another with ambiguous result access patterns. We used click-through information as a relevance proxy and tried to mitigate its limitations by evaluating under distinct IR metrics, including MRR, MAP and NDCG. Moreover, we also measured Spearman rank correlation coefficients to test similarities between produced rankings and reference orderings according to user access patterns. Results show consistency across all metrics in both sets. Previous search terms were key to obtaining a higher effectiveness, with runs that used pure search term frequency performing best. Compared to the baseline, our best strategies were able to maintain quality on frequent queries and improve retrieval effectiveness on ambiguous queries, with up to six percentage points better performance on most metrics.

Abstract
News articles typically include reporting events to inform on what happened. These reporting events are not part of the story being told but are nonetheless a relevant part of the news and can pose a challenge to the computational processing of news narratives. They compose a reporting narrative, which is the present study's focus. This paper aims to demonstrate through selected use cases how a comprehensive annotation scheme with suitable tags and links can properly represent the reporting events and the way they relate to the events that make the story. In addition, we put forward a proposal for their visual representation that enables a systematic and detailed analysis of the importance of reporting events in the news structure. Finally, we describe some lexico-grammatical features of reporting events, which can contribute to their automatic detection. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Abstract
Visual representations have the potential to improve information understanding. We explore this idea in the development of NewsLine, an open-source web-based prototype that focuses on narrative visualizations of news content. Having structured data as input, the prototype produces a storyline which showcases the narrative's events and participants, allowing the user to interact with the visualization in a number of ways. We built an information hub around the storyline to allow for multiple levels of exploration, specifically the main visualization, the event information module, and the sidebar. The visualization depicts the sequence of events that make up a news story, as well as the interactions between the involved parties in each event. The event information module presents additional information on a particular event. The sidebar is the “control center” of the visualization, unlocking a number of interactions and configurations. The prototype was evaluated with a user study with journalists and also with an online survey which gathered feedback from 178 potential end users. From these, 106 participants (60.6%) provided a rating of four or above (one to five scale) when asked to quantify their interest in using the application. Moreover, participants were asked to rank the importance of the visualization elements used. The results highlight that two elements stand out as the most important, the events and the entities. Overall, the participants generally found the application to be useful, but in need of some work in order for it to be made available to a broader public. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Abstract