Utilizing distributed web resources for enhanced knowledge representation

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Experiments using Semantic Web technologies to connect IUGONET, ESPAS and GFZ ISDC data portals

E-science on the Web plays an important role and offers the most advanced technology for the integration of data systems. It also makes available data for the research of more and more complex aspects of the system earth and beyond. The great number of e-science projects founded by the European Union (EU), university-driven Japanese efforts in the field of data services and institutional anchored developments for the enhancement of a sustainable data management in Germany are proof of the relevance and acceptance of e-science or cyberspace-based applications as a significant tool for successful scientific work. The collaboration activities related to near-earth space science data systems and first results in the field of information science between the EU-funded project ESPAS, the Japanese IUGONET project and the GFZ ISDC-based research and development activities are the focus of this paper. The main objective of the collaboration is the use of a Semantic Web approach for the mashup of the project related and so far inoperable data systems. Both the development and use of mapped and/or merged geo and space science controlled vocabularies and the connection of entities in ontology-based domain data model are addressed. The developed controlled vocabularies for the description of geo and space science data and related context information as well as the domain ontologies itself with their domain and cross-domain relationships will be published in Linked Open Data

Proceedings of the First International Workshop on Mashup Personal Learning Environments

Wild, F., Kalz, M., & Palmér, M. (Eds.) (2008). Proceedings of the First International Workshop on Mashup Personal Learning Environments (MUPPLE08). September, 17, 2008, Maastricht, The Netherlands: CEUR Workshop Proceedings, ISSN 1613-0073. Available at http://ceur-ws.org/Vol-388.The work on this publication has been sponsored by the TENCompetence Integrated Project (funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org]) and partly sponsored by the LTfLL project (funded by the European Commission's 7th Framework Programme, priority ISCT. Contract 212578 [http://www.ltfll-project.org

WarMemoirSampo : A Semantic Portal for War Veteran Interview Videos

Publisher Copyright: © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)This paper presents WarMemoirSampo, a portal that provides semantic search and navigation of video interviews with Finnish World War II veterans. The portal associates video fragments with contextual data extracted from the video transcriptions, enabling users to find suitable video segments via faceted search and highlighting relevant content in the video being watched. This is carried out by processing natural language texts in order to extract named entities, keywords and lemmas. The result is a Linked Data Knowledge Graph that underpins the portal. We describe the collaboration between Natural Language Processing and Semantic Web technologies used in order to produce these results.Peer reviewe

Modern Tools for Old Content - in Search of Named Entities in a Finnish OCRed Historical Newspaper Collection 1771-1910

Named entity recognition (NER), search, classification and tagging of names and name like frequent informational elements in texts, has become a standard information extraction procedure for textual data. NER has been applied to many types of texts and different types of entities: newspapers, fiction, historical records, persons, locations, chemical compounds, protein families, animals etc. In general a NER system’s performance is genre and domain dependent and also used entity categories vary [1]. The most general set of named entities is usually some version of three partite categorization of locations, persons and organizations. In this paper we report first trials and evaluation of NER with data out of a digitized Finnish historical newspaper collection Digi. Digi collection contains 1,960,921 pages of newspaper material from years 1771– 1910 both in Finnish and Swedish. We use only material of Finnish documents in our evaluation. The OCRed newspaper collection has lots of OCR errors; its estimated word level correctness is about 74–75 % [2]. Our principal NER tagger is a rule-based tagger of Finnish, FiNER, provided by the FIN-CLARIN consortium. We show also results of limited category semantic tagging with tools of the Semantic Computing Research Group (SeCo) of the Aalto University. FiNER is able to achieve up to 60.0 F-score with named entities in the evaluation data. Seco’s tools achieve 30.0–60.0 F-score with locations and persons. Performance of FiNER and SeCo’s tools with the data shows that at best about half of named entities can be recognized even in a quite erroneous OCRed textNamed entity recognition (NER), search, classification and tagging of names and name like frequent informational elements in texts, has become a standard information extraction procedure for textual data. NER has been applied to many types of texts and different types of entities: newspapers, fiction, historical records, persons, locations, chemical compounds, protein families, animals etc. In general a NER system’s performance is genre and domain dependent and also used entity categories vary [1]. The most general set of named entities is usually some version of three partite categorization of locations, persons and organizations. In this paper we report first trials and evaluation of NER with data out of a digitized Finnish historical newspaper collection Digi. Digi collection contains 1,960,921 pages of newspaper material from years 1771– 1910 both in Finnish and Swedish. We use only material of Finnish documents in our evaluation. The OCRed newspaper collection has lots of OCR errors; its estimated word level correctness is about 74–75 % [2]. Our principal NER tagger is a rule-based tagger of Finnish, FiNER, provided by the FIN-CLARIN consortium. We show also results of limited category semantic tagging with tools of the Semantic Computing Research Group (SeCo) of the Aalto University. FiNER is able to achieve up to 60.0 F-score with named entities in the evaluation data. Seco’s tools achieve 30.0–60.0 F-score with locations and persons. Performance of FiNER and SeCo’s tools with the data shows that at best about half of named entities can be recognized even in a quite erroneous OCRed text.Peer reviewe

Tagging Named Entities in 19th Century and Modern Finnish Newspaper Material with a Finnish Semantic Tagger

Named Entity Recognition (NER), search, classification and tagging of names and name like informational elements in texts, has become a standard information extraction procedure for textual data during the last two decades. NER has been applied to many types of texts and different types of entities: newspapers, fiction, historical records, persons, locations, chemical compounds, protein families, animals etc. In general a NER system’s performance is genre and domain dependent. Also used entity categories vary a lot (Nadeau and Sekine, 2007). The most general set of named entities is usually some version of three part categorization of locations, persons and corporations. In this paper we report evaluation results of NER with two different data: digitized Finnish historical newspaper collection Digi and modern Finnish technology news, Digitoday. Historical newspaper collection Digi contains 1,960,921 pages of newspaper material from years 1771–1910 both in Finnish and Swedish. We use only material of Finnish documents in our evaluation. The OCRed newspaper collection has lots of OCR errors; its estimated word level correctness is about 70–75%, and its NER evaluation collection consists of 75 931 words (Kettunen and Pääkkönen, 2016; Kettunen et al., 2016). Digitoday’s annotated collection consists of 240 articles in six different sections of the newspaper. Our new evaluated tool for NER tagging is non-conventional: it is a rule-based semantic tagger of Finnish, the FST (Löfberg et al., 2005), and its results are compared to those of a standard rule-based NE tagger, FiNER. The FST achieves up to 55–61 F-score with locations and F-score of 51–52 with persons with the historical newspaper data, and its performance is comparative to FiNER with locations. With the modern Finnish technology news of Digitoday FiNER achieves F-scores of up to 79 with locations at best. Person names show worst performance; their F-score varies from 33 to 66. The FST performs equally well as FiNER with Digitoday’s location names, but is worse with persons. With corporations, FST is at its worst, while FiNER performs reasonably well. Overall our results show that a general semantic tool like the FST is able to perform in a restricted semantic task of name recognition almost as well as a dedicated NE tagger. As NER is a popular task in information extraction and retrieval, our results show that NE tagging does not need to be only a task of dedicated NE taggers, but it can be performed equally well with more general multipurpose semantic tools.Peer reviewe

Actas del Taller de Trabajo Zoco’08 / JISBD Integración de Aplicaciones Web : XIII Jornadas de Ingeniería del Software y Bases de Datos Gijón, 7 al 10 de Octubre de 2008

Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-0260

The building and application of a semantic platform for an e-research society

This thesis reviews the area of e-Research (the use of electronic infrastructure to support research) and considers how the insight gained from the development of social networking sites in the early 21st century might assist researchers in using this infrastructure. In particular it examines the myExperiment project, a website for e-Research that allows users to upload, share and annotate work flows and associated files, using a social networking framework. This Virtual Organisation (VO) supports many of the attributes required to allow a community of users to come together to build an e-Research society. The main focus of the thesis is how the emerging society that is developing out of my-Experiment could use Semantic Web technologies to provide users with a significantly richer representation of their research and research processes to better support reproducible research. One of the initial major contributions was building an ontology for myExperiment. Through this it became possible to build an API for generating and delivering this richer representation and an interface for querying it. Having this richer representation it has been possible to follow Linked Data principles to link up with other projects that have this type of representation. Doing this has allowed additional data to be provided to the user and has begun to set in context the data produced by myExperiment. The way that the myExperiment project has gone about this task and consideration of how changes may affect existing users, is another major contribution of this thesis. Adding a semantic representation to an emergent e-Research society like myExperiment,has given it the potential to provide additional applications. In particular the capability to support Research Objects, an encapsulation of a scientist's research or research process to support reproducibility. The insight gained by adding a semantic representation to myExperiment, has allowed this thesis to contribute towards the design of the architecture for these Research Objects that use similar Semantic Web technologies. The myExperiment ontology has been designed such that it can be aligned with other ontologies. Scientific Discourse, the collaborative argumentation of different claims and hypotheses, with the support of evidence from experiments, to construct, confirm or disprove theories requires the capability to represent experiments carried out in silico. This thesis discusses how, as part of the HCLS Scientific Discourse subtask group, the myExperiment ontology has begun to be aligned with other scientific discourse ontologies to provide this capability. It also compares this alignment of ontologies with the architecture for Research Objects. This thesis has also examines how myExperiment's Linked Data and that of other projects can be used in the design of novel interfaces. As a theoretical exercise, it considers how this Linked Data might be used to support a Question-Answering system, that would allow users to query myExperiment's data in a more efficient and user-friendly way. It concludes by reviewing all the steps undertaken to provide a semantic platform for an emergent e-Research society to facilitate the sharing of research and its processes to support reproducible research. It assesses their contribution to enhancing the features provided by myExperiment, as well as e-Research as a whole. It considers how the contributions provided by this thesis could be extended to produce additional tools that will allow researchers to make greater use of the rich data that is now available, in a way that enhances their research process rather than significantly changing it or adding extra workload