Ilaria Corda

The use of ontologies enables semantically driven access to a variety of digital resources. In this paper, we illustrate how an ontology can be exploited to provide structured access to Web-based resources. We present a case study in history of science that illustrates how to conceptualise and reason about a historical domain by taking a systematic approach to modelling time

"Exploring connections between events is paramount to any historical and philosophical investigation. Historians will always be eager to draw connections between events, so that they can better establish the significance of certain happenings and measure their impact effectively. Seeking out information in historical and philosophical domains is complex, multifaceted and requires unveiling and exploring new associations and relationships between happenings. Although several event models and information systems for handling connections between events have been developed so far, there is a lack of formal approaches to build a framework for connecting historical events. Our work contributes to the field of Computing for Humanities, i.e. the field that bridges humanities disciplines and computational approaches. The aim of this research is to describe a formal approach for generating Semantic Trajectories, defined as logically constructed paths derived from an Event Ontology and semantically enriched by using a set of rules as well as connection templates definitions. Our approach employs Semantic Trajectories to help users discover key ideas and explore relevant connections, and it is illustrated in a case study from the History of Science domain. The thesis presents a framework for modelling events and representing temporal information. This was inspired by Davidson’s theory of events in which each event-forming predicate is enriched with an additional argument to be filled with a variable ranging over a number of specific dated occurrences (event-tokens). This results in a unified and systematic way to associate properties to historical events. Moreover, the temporal dimension between events, crucial element especially in historical domains, has been modelled following Allen’s interval relationships model, which allows comparing time points between events. We have also specified our temporal framework further in order to deal with time points of different granularity. Our formal framework has been implemented using Logic programming paradigms for the conceptual data modelling and reasoning apparatus. Furthermore, we have evaluated our generic approach in the application domain of Knowledge Discovery for supporting essay writing with the aim of helping students identify semantically connected historical events and entities, according to an essay title."

Knowledge-based Information Systems have been proven to pr ovide intelligent support in several domains. For instance, these system s can be valid tools to help people discover implicit relationships between entit ies and events. In particular, historical domains are complex and loosely structure d, and impose a number of additional challenges (e.g. dealing with temporal in formation). This paper describes a formal approach for generating Semantic Trajectories , logically connected knowledge units, which are derived from an event onto l gy and refined using inference and connection rules. Such Semantic Trajectories would help users discover key ideas and elicit significant connections accor ding to their information seeking goals (e.g. writing an essay). The approach is illus trated in a case study from the History of Science domain, and it also includes eval uation results.

Knowledge-based Information Systems have been proven to provide intelligent support in several domains. For instance, these systems can be valid tools to help people discover implicit relationships between entities and events. In particular, historical domains are complex and loosely structured, and impose a number of additional challenges (e.g. dealing with temporal information). This paper describes a formal approach for generating Semantic Trajectories, logically connected knowledge units, which are derived from an event ontology and refined using inference and connection rules. Such Semantic Trajectories would help users discover key ideas and elicit significant connections according to their information seeking goals (e.g. writing an essay). The approach is illustrated in a case study from the History of Science domain, and it also includes evaluation results.

Exploring connections between events is paramount to any historical and philosophical investigation. Historians will always be eager to draw connections between events, so that they can better establish the significance of certain happenings and measure their impact effectively. Seeking out information in historical and philosophical domains is complex, multifaceted and requires unveiling and exploring new associations and relationships between happenings. Although several event models and information systems for handling connections between events have been developed so far, there is a lack of formal approaches to build a framework for connecting historical events.
Our work contributes to the field of Computing for Humanities, i.e. the field that bridges humanities disciplines and computational approaches. The aim of this research is to describe a formal approach for generating Semantic Trajectories, defined as logically constructed paths derived from an Event Ontology and semantically enriched by using a set of rules as well as connection templates definitions.
Our approach employs Semantic Trajectories to help users discover key ideas and explore relevant connections, and it is illustrated in a case study from the History of Science domain.
The thesis presents a framework for modelling events and representing temporal information. This was inspired by Davidson’s theory of events in which each event-forming predicate is enriched with an additional argument to be filled with a variable ranging over a number of specific dated occurrences (event-tokens). This results in a unified and systematic way to associate properties to historical events. Moreover, the temporal dimension between events, crucial element especially in historical domains, has been modelled following Allen’s interval relationships model, which allows comparing time points between events. We have also specified our temporal framework further in order to deal with time points of different granularity.
Our formal framework has been implemented using Logic programming paradigms for the conceptual data modelling and reasoning apparatus. Furthermore, we have evaluated our generic approach in the application domain of Knowledge Discovery for supporting essay writing with the aim of helping students identify semantically connected historical events and entities, according to an essay title.

Exploring connections between events is paramount to any historical investigation. In the course of human occurrences, historians have been always interested in unveiling connections between events for the purpose of establishing the significance of certain happenings and measure their impact. The paper
describes a formal model for representing events and comparing temporal dimensions as the backbone for drawing connections and exploring relationships between happenings. The approach is illustrated in a case study from the Astronomical Revolution, a sub-domain of History of Science.

When browsing information resources people often face the
problem of identifying relevant connections between entities
and facts. In historical domains, tasks typically involve discovering
temporal and causal relations between events. The
aim of this research is to assist users’ navigation in historical
domains by generating Semantic Trajectories, which are derived
from an appropriate event ontology and causal model.
Our approach identifies semantic trajectories to help users
discover connections relevant to their information seeking
goals. The approach is illustrated in a case study from the
History of Science domain.

The use of ontologies enables semantically driven access to a variety of digital resources. In this paper, we illustrate how an ontology can be exploited to provide structured access to Web-based resources. We present a case study in history of science that illustrates how to conceptualise and reason about a historical domain by taking a systematic approach to modelling time and events, based on existing artificial intelligence theories. An initial Web-based application has been implemented for exemplifying how an ontology can assist users to examine a historical conceptual space and to explore temporal relationships between scientific events.

The use of ontologies enables semantically enriched access to a variety of digital resources. Historical domains impose a number of challenges to creating ontologies, e.g.
modeling temporal relations, handling subjectivity, and dealing with vagueness. This research develops a case study in the History of Science that illustrates how to conceptualise and reason about a historical domain, and suggests an approach to modeling time and temporal relations. Based on existing methodologies for ontology construction, a methodology for conceptualising (a part of) the History of Science domain has been derived taking into account that the author has acted as both a domain expert and a knowledge engineer. Following the methodology, main concepts and relations in the History of
Science have been identified. Special attention is paid at modeling temporal concepts and relations. A framework for conceptualising and reasoning about the History of Science
is presented, combining Davidson’s theory of events to represent temporal categories and Allen’s interval logic to reason about temporal relations.

Users access digital library content to fulfill task-specific
searches. In this position paper, we argue that semantically driven approaches are needed to offer personalised access to historical collections.
We consider a case study in the History of Science and illustrate how an ontology can be used to generate personalised, contextualised reference space in order to help users examine the context of scientific events.

In recent times the British Library has incorporated two new data sets into our Primo
results. In each case we had to decide whether to harvest the data into our main index
or build a deep search to an external index. This presentation describes why we
decided to harvest one set and build a deep search to the other. Using these two case
studies we'll discuss the pros and cons of each approach. Along the way we'll discuss
the difficulties that come with a large Primo index and the complications arising from
handling both sides of a Deep Search,

Exploring connections between events is paramount to any historical investigation. In the course of human occurrences, historians have been always interested in unveiling connections between events for the purpose of establishing the significance of certain happenings and measure their impact. The paper describes a formal model for representing events and comparing temporal dimensions as the backbone for drawing connections and exploring relationships between happenings. The approach is illustrated in a case study from the Astronomical Revolution, a sub-domain of History of Science.