Supporting Human Memory by Reconstructing Personal Episodic Narratives from Digital Traces

Numerous applications capture in digital form aspects of people’s lives. The resulting data, which we call Personal Digital Traces - PDTs, can be used to help reconstruct people’s episodic memories and connect to their past personal events. This may have several applications, from helping the recall of patients with neurodegenerative diseases to gathering clues from multiple sources to identify recent contacts and places visited – a critical new application for the recent health crisis. This paper takes steps towards integrating, connecting and summarizing the heterogeneous collection of data into episodic narratives using scripts – prototypical plans for everyday activities. Specifically, we propose a matching algorithm that groups PDTs from many different sources into script instances (episodes), and we provide a technique for ranking the likelihood of candidate episodes. We report on the results of a study based on the personal data of real users, which gives evidence that our episode reconstruction 1) integrates well PDTs from different sources into coherent episodes, and 2) augments users’ memory of their past actions

Public data homogenization for AI model development in breast cancer

Abstract Background Developing trustworthy artificial intelligence (AI) models for clinical applications requires access to clinical and imaging data cohorts. Reusing of publicly available datasets has the potential to fill this gap. Specifically in the domain of breast cancer, a large archive of publicly accessible medical images along with the corresponding clinical data is available at The Cancer Imaging Archive (TCIA). However, existing datasets cannot be directly used as they are heterogeneous and cannot be effectively filtered for selecting specific image types required to develop AI models. This work focuses on the development of a homogenized dataset in the domain of breast cancer including clinical and imaging data. Methods Five datasets were acquired from the TCIA and were harmonized. For the clinical data harmonization, a common data model was developed and a repeatable, documented “extract-transform-load” process was defined and executed for their homogenization. Further, Digital Imaging and COmmunications in Medicine (DICOM) information was extracted from magnetic resonance imaging (MRI) data and made accessible and searchable. Results The resulting harmonized dataset includes information about 2,035 subjects with breast cancer. Further, a platform named RV-Cherry-Picker enables search over both the clinical and diagnostic imaging datasets, providing unified access, facilitating the downloading of all study imaging that correspond to specific series’ characteristics (e.g., dynamic contrast-enhanced series), and reducing the burden of acquiring the appropriate set of images for the respective AI model scenario. Conclusions RV-Cherry-Picker provides access to the largest, publicly available, homogenized, imaging/clinical dataset for breast cancer to develop AI models on top. Relevance statement We present a solution for creating merged public datasets supporting AI model development, using as an example the breast cancer domain and magnetic resonance imaging images. Key points • The proposed platform allows unified access to the largest, homogenized public imaging dataset for breast cancer. • A methodology for the semantically enriched homogenization of public clinical data is presented. • The platform is able to make a detailed selection of breast MRI data for the development of AI models. Graphical Abstrac

Metadata management, interoperability and linked data publishing support for natural history museums

Summarization: Natural history museums (NHMs) form a rich source of knowledge about Earth’s biodiversity and natural history. However, an impressive abundance of high-quality scientific content available in NHMs around Europe remains largely unexploited due to a number of barriers, such as the lack of interconnection and interoperability between the management systems used by museums, the lack of centralized access through a European point of reference such as Europeana and the inadequacy of the current metadata and content organization. The Natural Europe project offers a coordinated solution at European level that aims to overcome those barriers. In this article, we present the architecture, deployment and evaluation of the Natural Europe infrastructure allowing the curators to publish, semantically describe and manage the museums’ cultural heritage objects, as well as disseminate them to Europeana.eu and BioCASE/GBIF. Additionally, we discuss the methodology followed for the transition of the infrastructure to the Semantic Web and the publishing of NHMs’ cultural heritage metadata as Linked Data, supporting the Europeana Data Model.Presented on: International Journal on Digital Librarie

From Syntactic to Semantic Interoperability Using a Hyperontology in the Oncology Domain

International audienceInteroperability is crucial to overcoming various challenges of data integration in the healthcare domain. While OMOP and FHIR data standards handle syntactic heterogeneity among heterogeneous data sources, ontologies support semantic interoperability to overcome the complexity and disparity of healthcare data. This study proposes an ontological approach in the context of the EUCAIM project to support semantic interoperability among distributed big data repositories that have applied heterogeneous cancer image data models using a semantically well-founded Hyperontology for the oncology domain

From Syntactic to Semantic Interoperability Using a Hyperontology in the Oncology Domain

International audienceInteroperability is crucial to overcoming various challenges of data integration in the healthcare domain. While OMOP and FHIR data standards handle syntactic heterogeneity among heterogeneous data sources, ontologies support semantic interoperability to overcome the complexity and disparity of healthcare data. This study proposes an ontological approach in the context of the EUCAIM project to support semantic interoperability among distributed big data repositories that have applied heterogeneous cancer image data models using a semantically well-founded Hyperontology for the oncology domain

Bringing environmental culture content into the Europeana.eu portal: The natural Europe digital libraries federation infrastructure

Summarization: The aim of the Natural Europe project [1] is to improve the availability and relevance of environmental culture content for education and life-long learning use, in a multilingual and multicultural context. Cultural heritage content related with natural history, natural sciences, and nature/ environment preservation, is collected from six Natural History Museums (NHMs) around Europe into a federation of European Natural History Digital Libraries that is directly connected with Europeana.eu. We present here the Natural History Digital Libraries Federation infrastructure along with the appropriate tools and services that (a) allow the participating NHMs to uniformly describe and semantically annotate their content according to international standards and specifications, (b) interconnect their digital libraries, and (c) expose metadata records for Natural History cultural heritage objects to Europeana.eu.Παρουσιάστηκε στο: 5th International Conference, MTSR 2011, Izmir, Turkey, October 12-14

Federating natural history museums in natural Europe

Summarization: An impressive abundance of high quality scientific content about Earth’s biodiversity and natural history available in Natural History Museums (NHMs) around Europe remains largely unexploited due to a number of barriers, such as: the lack of interconnection and interoperability between the management systems used by museums, the lack of centralized access through a European point of reference like Europeana, and the inadequacy of the current metadata and content organization. To cope with these problems, the Natural Europe project offers a coordinated solution at European level. Cultural heritage content is collected from six Natural History Museums around Europe into a federation of European Natural History Digital Libraries that is directly connected with Europeana.eu. This paper presents the Natural Europe Cultural Digital Libraries Federation infrastructure consisting of: (a) The Natural Europe Cultural Environment (NECE), i.e. the infrastructure and toolset deployed on each NHM allowing their curators to publish, semantically describe, manage and disseminate the Cultural Heritage Objects (CHOs) they contribute to the project, and (b) the Natural Europe Cultural Heritage Infrastructure (NECHI) interconnecting NHM digital libraries and further exposing their metadata records to Europeana.eu.Παρουσιάστηκε στο: 7th Metadata Semantics and Research Conference (MTSR) 201