Classificatory Theory in Data-Intensive Science: The Case of Open Biomedical Ontologies

publication-status: Publishedtypes: ArticleThis is the author's version of a paper that was subsequently published in International Studies in the Philosophy of Science. Please cite the published version by following the DOI link.Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and argue that they constitute an example of classificatory theory. This form of theorizing emerges from classification practices in conjunction with experimental know-how and expresses the knowledge underpinning the analysis and interpretation of data disseminated online.Economic and Social Research Council (ESRC)The British AcademyLeverhulme Trus

Factors shaping the evolution of electronic documentation systems

The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments

Estrategias para un modelo digital dirigido al conocimiento y gestión del Conjunto Arqueológico de Itálica Cuaderno de bitácora

This paper adopts the form of a log book of experiences, observations, interpretations, ideas and resources obtained as a result of using digital information models to address the needs of the institutions and managers of the Archaeological Site of Itálica (CAI, after the Spanish initials) between 2006 and 2021. The problems related to the knowledge and management of the site vary enormously both in scale and complexity. We discuss them here in chronological order to provide a vision of how digital geometric registration and information models have played an increasingly important role at this type of heritage site. The significance of the case study resides both in the importance of the remains, recognised since the 18th century, and in the difficulty of applying systematic processes to manage the site today.Esta aportación se plantea como cuaderno de bitácora de las experiencias, observaciones, lecturas, ideas y recursos resultado de aplicar modelos digitales de información a los requerimientos de las instituciones y gestores responsables del Conjunto Arqueológico de Itálica (CAI) entre los años 2006 y 2021. Reúne problemas de muy diversa escala y complejidad relacionados con el conocimiento y la gestión del yacimiento. Su lectura en orden cronológico ofrece una visión de la forma en que los modelos digitales de registro geométrico y de información han ido asumiendo un papel cada vez más relevante en este tipo de conjunto patrimonial. La trascendencia del caso de estudio se debe tanto a la importancia de los restos reconocidos desde el siglo XVIII, como por la complejidad en la aplicación en el presente de procesos sistemáticos de tutela

Strategies for a digital model to facilitate the knowledge and management of the Archaeological Site of Itálica: log book

[EN] This paper adopts the form of a log book of experiences, observations, interpretations, ideas and resources obtained as a result of using digital information models to address the needs of the institutions and managers of the Archaeological Site of Itálica (CAI, after the Spanish initials) between 2006 and 2021. The problems related to the knowledge and management of the site vary enormously both in scale and complexity. We discuss them here in chronological order to provide a vision of how digital geometric registration and information models have played an increasingly important role at this type of heritage site. The significance of the case study resides both in the importance of the remains, recognised since the 18th century, and in the difficulty of applying systematic processes to manage the site today.[ES] Esta aportación se plantea como cuaderno de bitácora de las experiencias, observaciones, lecturas, ideas y recursos resultado de aplicar modelos digitales de información a los requerimientos de las instituciones y gestores responsables del Conjunto Arqueológico de Itálica (CAI) entre los años 2006 y 2021. Reúne problemas de muy diversa escala y complejidad relacionados con el conocimiento y la gestión del yacimiento. Su lectura en orden cronológico ofrece una visión de la forma en que los modelos digitales de registro geométrico y de información han ido asumiendo un papel cada vez más relevante en este tipo de conjunto patrimonial. La trascendencia del caso de estudio se debe tanto a la importancia de los restos reconocidos desde el siglo XVIII, como por la complejidad en la aplicación en el presente de procesos sistemáticos de tutela.Pinto Puerto, F.; Guerrero Vega, JM.; Angulo Fornos, R.; Castellano Román, M. (2021). Estrategias para un modelo digital dirigido al conocimiento y gestión del Conjunto Arqueológico de Itálica Cuaderno de bitácora. EGE Revista de Expresión Gráfica en la Edificación. 0(15):61-83. https://doi.org/10.4995/ege.2021.16796OJS6183015Angulo Fornos, R. 2012. "Construcción de la base gráfica para un sistema de información y gestión del patrimonio arquitectónico: Casa de Hylas". Arqueología de la Arquitectura, no. 9, pp. 11-25. ISSN 1695-2731. https://doi.org/10.3989/arqarqt.2012.10005Becerra, J.M., Ladrón de Guevara, C. 2005. "MOSAICO, un Sistema de Información para la gestión de los Bienes Culturales". PH Boletín del Instituto Andaluz del Patrimonio Histórico, no. 52, pp. 24-25. ISSN 1136-1867. https://doi.org/10.33349/2005.52.1894Ceballos, Fernando de. 1886. La Itálica. Sevilla: Sociedad de Bibliófilos Andaluces.García Gutiérrez, A. (dir.) 1998. Tesauro de Patrimonio Histórico Andaluz. Sevilla: Consejería de Cultura. ISBN 84-8266-030-6.González-Pérez, C. 2018. Information Modelling for Archaeology and Anthropology: Software Engineering Principles for Cultural Heritage. Cham: Springer. ISBN 978-3-319-72651-9.Grande León, A. 2010. "La Génesis de un Museo del Guadalquivir del siglo XXI. Anastylosis virtual del valle del Guadalquivir en el siglo II d. C: La Baetica de Adriano". Virtual Archaeology Review, vol. 1, no. 1, pp. 27-37. ISSN 1989-9947. https://doi.org/10.4995/var.2010.4753.IAPH Instituto Andaluz de Patrimonio Histórico. 2021. Diagnóstico general de mosaicos y revestimientos pictóricos del CAI.Kagan, Richard L. 1986. Ciudades del Siglo de Oro: las vistas españolas de Anton Van den Wyngaerde. Madrid: El Viso. ISBN 978-84-86022-24-2.Martín Pradas, A. 2007. "El Tesauro de Patrimonio Histórico Andaluz como lenguaje integrador" In El Sistema de Información del Patrimonio Histórico de Andalucía (SIPHA). Sevilla: Consejería de Cultura de la Junta de Andalucía. pp. 50-61. ISBN 84-8266-637-1.Mesa Gisbert, A., Regot, J. Núñez, M.A., Buil, F. 2009. "Métodos y procesos para el Levantamiento de reconstrucción tridimensional gráfica de elementos del patrimonio cultural. La iglesia de Sant Sever de Barcelona". Revista EGA, no. 14, pp. 82-89. ISSN 1133-6137. https://doi.org/10.4995/ega.2009.10240Morales, Ambrosio de. 1577. Las Antigüedades de las ciudades de España que se nombran en esta Coronica... Alcalá de Henares: Imprenta de Juan Íñiguez de Lequerica.Navarro, P., Cabanes, J.L. 2009. "Edición avanzada de fotomodelos de edificios". Revista EGA, no. 14, pp. 68-73. ISSN 1133-6137. https://doi.org/10.4995/ega.2009.10238Pinto Puerto, F., Angulo Fornos, R., Castellano Román, M., Guerrero Vega, J.M., Pastor Gil, F. 2010. "Aplicación de los sistemas BIM a la gestión de conjuntos arqueológicos: Itálica". Libro de Actas I Congreso Nacional de Investigación Aplicada a la Gestión de Edificación. Alicante: Universidad de Alicante, p. 116-133. ISBN 978-84-693-3404-1. https://doi.org/10.33349/2011.77.3115Pinto Puerto, F., Angulo Fornos, R., Castellano Román, M., Guerrero Vega, J. M., Pastor Gil, F. 2011a. "Construcción de una base cartográfica activa para el Conjunto Arqueológico de Itálica". Revista PH, no. 77, pp. 116-119. https://doi.org/10.33349/2011.77.3115Pinto Puerto, F., Angulo Fornos, R., Guerrero Vega, J. 2011b. "Metodología y recursos empleados en la propuesta de anastilosis de la scaenae frons del teatro romano de Itálica". Itálica Revista de Arqueología Clásica de Andalucía, no.1, p. 77-83. ISSN: 2174-8667.Pinto Puerto, F., Guerrero Vega, J.M. 2012. "The Scaenae Frons of the Roman Theatre of Itálica: Notes on the Construction Process". In Nuts and Bolts of Culture, Technology and Society. Construction History. Paris: Picard. vol. 3, p. 21-29. ISBN 978-2-7084-0929.Rodríguez de Guzmán Sánchez, S. (dir.) 2011. Plan Director del Conjunto Arqueológico de Itálica: documento de avance. Sevilla: Junta de Andalucía. ISBN 978-84-9959-074-5.Rodríguez Gutiérrez, O., Rodríguez Medina, J., Pinto Puerto, F., Angulo Fornos, R. 2016. "Refuerzo de fustes de columna en la arquitectura monumental de Itálica (prov. Baetica). Aplicación de nuevas tecnologías para la reconstrucción de una práctica singular". Arqueología de la Arquitectura, no. 13, e048. ISSN 1695-2731. https://doi.org/10.3989/arq.arqt.2016.166Tejedor Cabrera, A., Linares Gómez del Pulgar, M., López Sánchez M. y Merino del Rio, R. (coord.) 2020. Innovación para la gestión integral del patrimonio. El Paisaje y el turismo. Sevilla: Universidad de Sevilla y Universidad Valladolid. ISBN 978-84-472-2970-3.Torres Luque, E., Morón Orta, M. E. Domínguez Ruiz, V., Martín Pastor, A., González Jiménez, J. M., Aguilar de los Santos, R. 2004. "Aplicación de los Sistemas de Información Geográfica (SIG) al estudio de los edificios patrimoniales..., Sevilla". Primeras jornadas sobre investigación en arquitectura y urbanismo. Sevilla: IUCC. p. 150-151. ISBN: 84-88988-21-4

Automated Reasoning and Robotics

A most important quality in robotics is the work done in the development of automated reasoning techniques. This model of reasoning works on the assistance of computer programs and just as it is in other fields, it has worked to aid in the answering of certain open questions. The aim of this survey is to study the applications of automated reasoning in the field of robotics and to evaluate its efficiency as a reasoning technique when applied. It is based generally on research into reasoning techniques applied to robotics and running an evaluation in contrast to automated reasoning to determine the rates of effectiveness between them. This process involves a basic understanding of how reasoning is implemented in relation to robotics, after which varying reasoning techniques and applications are discussed and compared in relation to automated reasoning and how automated reasoning would work to enhance results retrieved. The primary objective in this study is to identify the effectiveness of automated reasoning techniques to other techniques available and it begins with an introduction providing an overview of the concepts discussed before proceeding to examine the technicalities involved and which level of technicality is best

Sustainability Reporting Process Model using Business Intelligence

Sustainability including the reporting requirements is one of the most relevant topics for companies. In recent years, many software providers have launched new software tools targeting companies committed to implementing sustainability reporting. But it’s not only companies willing to use their Business Intelligence (BI) solution, there are also basic principles such as the single source of truth and tendencies to combine sustainability reporting with the financial reporting (Integrated Reporting) The IT integration of sustainability reporting has received limited attention by scientific research and can be facilitated using BI systems. This has to be done both to anticipate the economic demand for integrated reporting from an IT perspective as well as for ensuring the reporting of revisable data. Through the adaption of BI systems, necessary environmental and social changes can be addressed rather than merely displaying sustainability data from additional, detached systems or generic spreadsheet applications. This thesis presents research in the two domains sustainability reporting and Business Intelligence and provides a method to support companies willing to implement sustainability reporting with BI. SureBI presented within this thesis is developed to address experts from both sustainability and BI. At first BI is researched from a IT and project perspective and a novel BI reporting process is developed. Then, sustainability reporting is researched focusing on the reporting content and a sustainability reporting process is derived. Based on these two reporting processes SureBI is developed, a step-by-step process method, aiming to guide companies through the process of implementing sustainability reporting using their BI environment. Concluding, an evaluation and implementation assesses the suitability and correctness of the process model and exemplarily implements crucial IT tasks of the process. The novel combination of these two topics indicates challenges from both fields. In case of BI, users face problems regarding historically grown systems and lacking implementation strategies. In case of sustainability, the mostly voluntary manner of this reporting leads to an uncertainty as to which indicators have to be reported. The resulting SureBI addresses and highlights these challenges and provides methods for the addressing and prioritization of new stakeholders, the prioritization of the reporting content and describes possibilities to integrate the high amount of estimation figures using BI. Results prove that sustainability reporting could and should be implemented using existing BI solutions

Phenotyping in the era of genomics: MaTrics—a digital character matrix to document mammalian phenotypic traits

A new and uniquely structured matrix of mammalian phenotypes, MaTrics (Mammalian Traits for Comparative Genomics) in a digital form is presented. By focussing on mammalian species for which genome assemblies are available, MaTrics provides an interface between mammalogy and comparative genomics. MaTrics was developed within a project aimed to find genetic causes of phenotypic traits of mammals using Forward Genomics. This approach requires genomes and comprehensive and recorded information on homologous phenotypes that are coded as discrete categories in a matrix. MaTrics is an evolving online resource providing information on phenotypic traits in numeric code; traits are coded either as absent/present or with several states as multistate. The state record for each species is linked to at least one reference (e.g., literature, photographs, histological sections, CT scans, or museum specimens) and so MaTrics contributes to digitalization of museum collections. Currently, MaTrics covers 147 mammalian species and includes 231 characters related to structure, morphology, physiology, ecology, and ethology and available in a machine actionable NEXUS-format*. Filling MaTrics revealed substantial knowledge gaps, highlighting the need for phenotyping efforts. Studies based on selected data from MaTrics and using Forward Genomics identified associations between genes and certain phenotypes ranging from lifestyles (e.g., aquatic) to dietary specializations (e.g., herbivory, carnivory). These findings motivate the expansion of phenotyping in MaTrics by filling research gaps and by adding taxa and traits. Only databases like MaTrics will provide machine actionable information on phenotypic traits, an important limitation to genomics. MaTrics is available within the data repository Morph·D·Base (www.morphdbase.de)

Experimenting on the Enactment of Predictive AI: The Quest for a Future Proactive Healthcare Sector

Currently, a large number of AI projects are experimenting with the use of AI and big data for various purposes, especially in the public sector. In this article, we explore one such AI project. Specifically, we study a group of developers in Scandinavia and their efforts to enact predictive AI through the development of a clinical decision support system (CDSS) in pursuit of a future proactive healthcare sector. This yet-to-be system was envisioned to prevent unplanned hospitalizations by ‘turning’ what we term ‘potential patients’, i.e. the effective management of patient trajectories, in pursuit of a proactive healthcare sector. In the article, we investigate this particular project as an ‘experiment’ and conceptualize the developing CDSS as a ‘partially existing object’ with an uncertain ontological status. By studying the gradual enactment and emergence of the CDSS, we illuminate how this fuzzy data-driven object is performed and gradually attributed with solid reality: during its creation process, it advances from being a proactive device imagined to be used in primary healthcare to becoming a triage tool embedded in the prehospital emergency department. Along the way, the project developers are also transformed, learning what ‘moves’ and ‘actions’ to make, and, thereby, becoming skillful CDSS-operators. By using ‘experiment’ as our analytical lens, the article renders visible how persons, locations, and procedures have to be changed, revoked, and suspended in order for the AI project to succeed. Thus, the article contributes to showing how ‘social mangling’ is an essential precondition for predictive AI to succeed as a prolific solution to specific healthcare challenges, along with developers’ learning and transformation.&nbsp