Visualisation of the information resources for cell biology

Intelligent multimodal interfaces can facilitate scientists in utilising available information resources. Combining scientific visualisations with interactive and intelligent tools can help create a “habitable” information space. Development of such tools remains largely iterative. We discuss an ongoing implementation of intelligent interactive visualisation of information resources in cell biology

Transforming semi-structured life science diagrams into meaningful domain ontologies with DiDOn

AbstractBio-ontology development is a resource-consuming task despite the many open source ontologies available for reuse. Various strategies and tools for bottom-up ontology development have been proposed from a computing angle, yet the most obvious one from a domain expert perspective is unexplored: the abundant diagrams in the sciences. To speed up and simplify bio-ontology development, we propose a detailed, micro-level, procedure, DiDOn, to formalise such semi-structured biological diagrams availing also of a foundational ontology for more precise and interoperable subject domain semantics. The approach is illustrated using Pathway Studio as case study

LoLa: a modular ontology of logics, languages and translations

The Distributed Ontology Language (DOL), currently being standardised within the OntoIOp (Ontology Integration and Interoperability) activity of ISO/TC 37/SC 3, aims at providing a unified framework for (i) ontologies formalised in heterogeneous logics, (ii) modular ontologies, (iii) links between ontologies, and (iv) annotation of ontologies.\ud \ud This paper focuses on the LoLa ontology, which formally describes DOL's vocabulary for logics, ontology languages (and their serialisations), as well as logic translations. Interestingly, to adequately formalise the logical relationships between these notions, LoLa itself needs to be axiomatised heterogeneously---a task for which we choose DOL. Namely, we use the logic RDF for ABox assertions, OWL for basic axiomatisations of various modules concerning logics, languages, and translations, FOL for capturing certain closure rules that are not expressible in OWL (For the sake of tool availability it is still helpful not to map everything to FOL.), and circumscription for minimising the extension of concepts describing default translations

Assimilating knowledge from neuroimages in schizophrenia diagnostics

The aim of this article is to propose an integrated framework for classifying and describing patterns of disorders from medical images using a combination of image registration, linear discriminant analysis and region-based ontologies. In a first stage of this endeavour we are going to study and evaluate multivariate statistical methodologies to identify the most discriminating hyperplane separating two populations contained in the input data. This step has, as its major goal, the analysis of all the data simultaneously rather than feature by feature. The second stage of this work includes the development of an ontology whose aim is the assimilation and exploration of the knowledge contained in the results of the previous statistical methods. Automated knowledge discovery from images is the key motivation for the methods to be investigated in this research. We argue that such investigation provides a suitable framework for characterising the high complexity of MR images in schizophrenia

Spatial Data Harmonisation in Regional Context in Accordance with INSPIRE Implementing Rules

Spatial data seamless exchange and interoperable usage has become a necessity in efficient data management and competitive positioning in the European Union. Conceptual and technical framework for the spatial data and services interoperability is specified within the EU INSPIRE Directive. The Directive provides flexible and modular structure, giving the opportunity for customisation of the data specifications and usage. From the data publisher level to the European spatial data infrastructure, this opened the question of disharmony of the spatial data structure and sharing. Arisen challenges in data harmonisation process are thus subject of interest for different formalisation approaches. This study approaches the spatial data harmonisation process focusing on the area of Western Balkans, the region of Europe with countries that have similar interest for implementation of the INSPIRE Directive. With the main aim to propose the improvement to regional data harmonisation process, the study is focused on geology as the spatial theme. The study (1) analyses the INSPIRE data harmonisation process, (2) assesses critical factors of the process in the region and (3) tests the implementation of the INSPIRE data model harmonised in accordance with user needs. Results of the analysis present the structure and formalisation concepts of the INSPIRE data model, its extensibility, means for securing interoperability and standardised approach in defining data model elements. Critical factors of the harmonisation process are assessed through semi-structured questionnaire answered by competent representatives of the Western Balkans countries. The results show that, on a regional level, spatial data managers have made progress towards compliance and are familiar with the Directive. However, they lack a coordinated approach and implementation guidance. Aside from the low capacities, due to the current state of the data structures, harmonisation is a highly complex process and a goal that is difficult to reach. The outcomes of the INSPIRE defined harmonisation process and user needs are implemented on a practical example, a INSPIRE Theme Geology dataset from a Western Balkans region stakeholder. The user needs and data model structure characteristics of the regional geology dataset were integrated in the formal description of the source and transformed to target INSPIRE data model. The concept required structuring the source model to meet both INSPIRE and local requirements. The study general aim was reached by implementing the INSPIRE data harmonisation with fulfilling the main objectives – creating market-oriented, interoperable and accessible dataset, meeting national legal requirements towards the geological data management and increasing efficiency of data usage. Further application of the developed approach is seen as the implementation methodology for other INSPIRE themes and other geographical regions.Spatial data seamless usage and exchange has become a necessity in management of natural resources, environmental risk assessment, infrastructural planning and various other industrial domains. Framework for spatial data seamless usage is specified within the EU INSPIRE Directive on the continent-wide level. The Directive enables customisation of the data specifications and usage. However, high-level specification raised the issue of disharmony of the spatial data structure and sharing on regional level. Challenges in data harmonisation process therefore became subject of interest for different research approaches. This study approaches the spatial data harmonisation process focusing on the area of Western Balkans, the region of Europe with countries that have similar interest for implementation of the INSPIRE Directive. With the main aim to propose the improvement to regional data harmonisation process, the study is focused on geology as the spatial theme. The study assesses the regional needs and, in that light, develops the example of geological spatial data harmonisation. The needs and the critical factors of the harmonisation process are assessed through a questionnaire answered by competent representatives of the Western Balkans countries. It was found that spatial data managers in the region have made progress towards compliance and are familiar with the Directive. However, they lack a coordinated approach and implementation guidance. Moreover, the current state of the datasets structure makes harmonisation a complex process and a goal that is difficult to reach. Geology dataset from a Western Balkans region stakeholder was used as a practical example for testing the harmonisation process in accordance with user needs and INSPIRE requirements. The result was harmonised INSPIRE conformant spatial dataset, with validated seamless sharing and usage possibilities of the spatial dataset on both local and EU-wide level. The study showed the possibility of applying the INSPIRE data harmonisation, with fulfilling the main objectives of (1) creating market-oriented, interoperable and accessible dataset, (2) meeting national legal requirements towards the geological data management and (3) increasing efficiency of data usage. Further application of the presented approach is seen as the implementation methodology for other spatial themes and different geographical regions

The Natural Capital Indicator Framework (NCIF): A framework of indicators for national natural capital reporting

It is now widely recognised that components of the environment play the role of economic assets, termed natural capital, that are a foundation of social and economic development. National governments monitor the state and trends of natural capital through a range of activities including natural capital accounting, national ecosystem assessments, ecosystem service valuation, and economic and environmental analyses. Indicators play an integral role in these activities as they facilitate the reporting of complex natural capital information. One factor that hinders the success of these activities and their comparability across countries is the absence of a coherent framework of indicators concerning natural capital (and its benefits) that can aid decision-making. Here we present an integrated Natural Capital Indicator Framework (NCIF) alongside example indicators, which provides an illustrative structure for countries to select and organise indicators to assess their use of and dependence on natural capital. The NCIF sits within a wider context of indicators related to natural, human, social and manufactured capital, and associated flows of benefits. The framework provides decision-makers with a structured approach to selecting natural capital indicators with which to make decisions about economic development that take into account national natural capital and associated flows of benefits.Comment: 26 pages, 3 figures, 1 table, 1 graphical abstrac

URBAN AGRICULTURE DIVERSITY IN BRITAIN: BUILDING RESILIENCE THROUGH INTERNATIONAL EXPERIENCES

N° ISBN - 978-2-7380-1284-5International audienceDiversity of urban agriculture (UA) in Britain could reduce food security impacts if a crisis occured in industrial food production systems. Industrial agriculture (IA) both causes and suffers from a lack of resilience: environmental, financial and structural. In Britain, the allotment system, previously an important form of UA, now grossly insufficient to replace the output of industrial agriculture, particularly in London. With these points identified, the relationship between diversity and resilience takes on a new clarity. Systems theory shows that diversity in any system is key to resilience. Some lessons can be learnt from international experiences of food crises ammeliorated by different forms of urban agriculture. Examples include : St. Petersburg's dachas, Milwaukee Growing Power farm and Havana permaculture. These examples are chosen to illustrate the potential to rediversify food production systems with urban agriculture. Finally, a discussion about applying aspects of these urban agriculture practices to London and other cities

Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science

The paper deals with the use of empirical data in social science agent-based models. Agent-based models are too often viewed just as highly abstract thought experiments conducted in artificial worlds, in which the purpose is to generate and not to test theoretical hypotheses in an empirical way. On the contrary, they should be viewed as models that need to be embedded into empirical data both to allow the calibration and the validation of their findings. As a consequence, the search for strategies to find and extract data from reality, and integrate agent-based models with other traditional empirical social science methods, such as qualitative, quantitative, experimental and participatory methods, becomes a fundamental step of the modelling process. The paper argues that the characteristics of the empirical target matter. According to characteristics of the target, ABMs can be differentiated into case-based models, typifications and theoretical abstractions. These differences pose different challenges for empirical data gathering, and imply the use of different validation strategies.Agent-Based Models, Empirical Calibration and Validation, Taxanomy of Models