Databases

Immunology researchers are beginning to explore the possibilities of reproducibility, reuse and secondary analyses of immunology data. Open-access datasets are being applied in the validation of the methods used in the original studies, leveraging studies for meta-analysis, or generating new hypotheses. To promote these goals, the ImmPort data repository was created for the broader research community to explore the wide spectrum of clinical and basic research data and associated findings. The ImmPort ecosystem consists of four components–Private Data, Shared Data, Data (...) Analysis, and Resources—for data archiving, dissemination, analyses, and reuse. To date, more than 300 studies have been made freely available through the Shared Data portal (immport.org/immportopen), which allows research data to be repurposed to accelerate the translation of new insights into discoveries. (shrink)

Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal knowledge is necessary for (...) the project, both as a source for handling complexity and as an output for meeting the project’s goals. Consequently, I argue that data-driven claims about causality are fundamentally flawed and causal knowledge should be considered a necessary aspect of Big Data science. In addition, I present the consequences of this result on other data-driven claims, concerning the role of theoretical considerations. I argue that the importance of causal knowledge and other kinds of theoretical engagement in EXPOsOMICS undermine theory-free accounts and suggest alternative ways of framing science based on Big Data. (shrink)

Management of information is facilitated by unambiguously tracking portions of reality over time. To track the portions of reality, a referent tracking system is used. The referent tracking system is able to communicate with other tracking systems and/or tradition information systems. Errors in the referent tracking system are detected and corrected to maintain actual representations of the portions of reality.

Two large lexicological projects for the Center for the Greek Language, Thessaloniki, were to be published in print and on the WWW, which meant that two conversions were needed: a near-database file had to be converted to fully formatted file for printing and a fully formatted file had to be converted to a database for WWW access. As it turned out, both conversions could make use of existing clues that indicated the kinds of information contained in each particular piece of (...) text, thus separating fields from each other and ordering them into a tree-like structure. This indicates that both forms of the dictionaries, print and database, stem from the same cognitive need to categorize information into a kind of information before further understanding – be this for a human reader or for a machine. (shrink)

The orbital space environment is home to natural and artificial satellites, debris, and space weather phenomena. As the population of orbital objects grows so do the potential hazards to astronauts, space infrastructure and spaceflight capability. Orbital debris, in particular, is a universal concern. This and other hazards can be minimized by improving global space situational awareness (SSA). By sharing more data and increasing observational coverage of the space environment we stand to achieve that goal, thereby making spaceflight safer and expanding (...) our knowledge of near-Earth space. To facilitate data-sharing interoperability among distinct orbital debris and space object catalogs, and SSA information systems, I proposed ontology in (Rovetto, 2015) and (Rovetto and Kelso, 2016). I continue this effort toward formal representations and models of the overall domain that may serve to improve peaceful SSA and increase our scientific knowledge. This paper explains the project concept introduced in those publications, summarizing efforts to date as well as the research field of ontology development and engineering. I describe concepts for an ontological framework for the orbital space environment, near-Earth space environment and SSA domain. An ontological framework is conceived as a part of a potential international information system. The purpose of such a system is to consolidate, analyze and reason over various sources and types of orbital and SSA data toward the mutually beneficial goals of safer space navigation and scientific research. Recent internationals findings on the limitations of orbital data, in addition to existing publications on collaborative SSA, demonstrate both the overlap with this project and the need for data-sharing and integration. (shrink)

A short summary paper of my Orbital Space Domain Ontology project (purl.org/space-ontology), originally conceived in 2011. Since then I've sought (without success) opportunities to realize it (either as a PhD or other degree thesis; or in an employment position) toward my original passion of entering the space sector and gaining further space education. Since then persons in the relevant space disciplines have seen the potential in it, and unfortunately some have taken advantage of my ideas yet excluded me from work. (...) I continue to struggle to fight for my own ideas as I see others professionally and financially benefit at my expense. References and documentation are available upon request to confirm my early ideation and origination on this topic. Please contact me if you have opportunities. Thank you. (shrink)

This paper develops the ontology of space objects for theoretical and computational ontology applied to the space (astronautical/astronomical) domain. It follows “An ontological architecture for Orbital Debris Data” (Rovetto, 2015) and “Preliminaries of a Space Situational Awareness Ontology” (Rovetto, Kelso, 2016). Important considerations for developing a space object ontology, or more broadly, a space domain ontology are presented. The main category term ‘Space Object’ is analyzed from a philosophical perspective. The ontological commitments of legal definitions for artificial space objects are (...) also discussed. Space object taxonomies are offered and space object terms are defined. (shrink)

The orbital debris problem presents an opportunity for inter-agency and international cooperation toward the mutually beneficial goals of debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris and broader SSA domain, taking steps in the creation of an orbital debris ontology (ODO). The purpose of this ontological system is to (I) represent general orbital debris and SSA domain (...) knowledge, (II) structure, and standardize where needed, orbital data and terminology, and (III) foster semantic interoperability and data-sharing. In doing so I hope to (IV) contribute to solving the orbital debris problem, improving peaceful global SSA, and ensuring safe space travel for future generations. (shrink)

Space situational awareness (SSA) is vital for international safety and security, and for the future of space travel. The sharing of SSA data and information should improve the state of global SSA for planetary defense and spaceflight safety. I take steps toward a Space Situational Awareness (SSA) Ontology, and outline some central objectives, requirements and desiderata in the ontology development process for this domain. The purpose of this ontological system is to explore the potential for the ontology research topic to (...) (i) represent SSA general knowledge, data, and entities/objects, (ii) clearly express the meaning of SSA data, and (iii) foster SSA data-sharing. The overall goal and motivation is to (iv) improve our capacity for planetary defense, e.g., from near- or deep-space objects and phenomena, and (v) facilitate safer and peaceful space access, navigation and travel, by improving global SSA. This research is thereby intended only for peaceful space-domain applications and uses, with particular interests in orbital debris. There is little application of ontology to the space domain as compared with other disciplines and little if any ontological development of SSA and related domains. In this respect, this paper offers novel concepts. (shrink)

The central hypothesis of the collaboration between Language and Computing (L&C) and the Institute for Formal Ontology and Medical Information Science (IFOMIS) is that the methodology and conceptual rigor of a philosophically inspired formal ontology greatly benefits application ontologies. To this end r®, L&C’s ontology, which is designed to integrate and reason across various external databases simultaneously, has been submitted to the conceptual demands of IFOMIS’s Basic Formal Ontology (BFO). With this project we aim to move beyond the level of (...) controlled vocabularies to yield an ontology with the ability to support reasoning applications. Our general procedure has been the implementation of a meta-ontological definition space in which the definitions of all the concepts and relations in LinKBase® are standardized in a framework of first-order logic. In this paper we describe how this standardization has already led to an improvement in the LinKBase® structure that allows for a greater degree of internal coherence than ever before possible. We then show the use of this philosophical standardization for the purpose of mapping external databases to one another, using LinKBase® as translation hub, with a greater degree of success than possible hitherto. We demonstrate how this offers a genuine advance over other application ontologies that have not submitted themselves to the demands of philosophical scrutiny. LinKBase® is one of the world’s largest applications-oriented medical domain ontologies, and BFO is one of the world’s first philosophically driven reference ontologies. The collaboration of the two thus initiates a new phase in the quest to solve the so-called “Tower of Babel”. (shrink)

The discipline of ontology has enjoyed a checkered history since 1606, with a significant expansion in recent years. We focus here on those developments in the recent history of philosophy which are most relevant to the understanding of the increased acceptance of ontology, and especially of realist ontology, as a valuable method also outside the discipline of philosophy.

As available intelligence data and information expand in both quantity and variety, new techniques must be deployed for search and analytics. One technique involves the semantic enhancement of data through the creation of what are called ‘ontologies’ or ‘controlled vocabularies.’ When multiple different bodies of heterogeneous data are tagged by means of terms from common ontologies, then these data become linked together in ways which allow more effective retrieval and integration. We describe a simple case study to show how these (...) benefits are being achieved, and we describe our strategy for developing a suite of ontologies to serve the needs of the war-fighter in the ever more complex battlespace environments of the future. (shrink)

The world of ontology development is full of mysteries. Recently, ISO Standard 15926 (“Lifecycle Integration of Process Plant Data Including Oil and Gas Production Facilities”), a data model initially designed to support the integration and handover of large engineering artefacts, has been proposed by its principal custodian for general use as an upper level ontology. As we shall discover, ISO 15926 is, when examined in light of this proposal, marked by a series of quite astonishing defects, which may however provide (...) general lessons for the developers of ontologies in the future. (shrink)

The Health Level 7 Reference Information Model (HL7 RIM) is lauded by its authors as ‘the foundation of healthcare interoperability’. Yet even after some 10 years of development work, the RIM is still subject to a variety of logical and ontological flaws which have placed severe obstacles in the way of those who are called upon to develop implementations. We offer evidence that these obstacles are insurmountable and that the time has come to abandon an unworkable paradigm.

Criticism of big data has focused on showing that more is not necessarily better, in the sense that data may lose their value when taken out of context and aggregated together. The next step is to incorporate an awareness of pitfalls for aggregation into the design of data infrastructure and institutions. A common strategy minimizes aggregation errors by increasing the precision of our conventions for identifying and classifying data. As a counterpoint, we argue that there are pragmatic trade-offs between precision (...) and ambiguity that are key to designing effective solutions for generating big data about biodiversity. We focus on the importance of theory-dependence as a source of ambiguity in taxonomic nomenclature and hence a persistent challenge for implementing a single, long-term solution to storing and accessing meaningful sets of biological specimens. We argue that ambiguity does have a positive role to play in scientific progress as a tool for efficiently symbolizing multiple aspects of taxa and mediating between conflicting hypotheses about their nature. Pursuing a deeper understanding of the trade-offs and synthesis of precision and ambiguity as virtues of scientific language and communication systems then offers a productive next step for realizing sound, big biodiversity data services. (shrink)

Throughout the biological and biomedical sciences there is a growing need for, prescriptive ‘minimum information’ (MI) checklists specifying the key information to include when reporting experimental results are beginning to find favor with experimentalists, analysts, publishers and funders alike. Such checklists aim to ensure that methods, data, analyses and results are described to a level sufficient to support the unambiguous interpretation, sophisticated search, reanalysis and experimental corroboration and reuse of data sets, facilitating the extraction of maximum value from data sets (...) them. However, such ‘minimum information’ MI checklists are usually developed independently by groups working within representatives of particular biologically- or technologically-delineated domains. Consequently, an overview of the full range of checklists can be difficult to establish without intensive searching, and even tracking thetheir individual evolution of single checklists may be a non-trivial exercise. Checklists are also inevitably partially redundant when measured one against another, and where they overlap is far from straightforward. Furthermore, conflicts in scope and arbitrary decisions on wording and sub-structuring make integration difficult. This presents inhibit their use in combination. Overall, these issues present significant difficulties for the users of checklists, especially those in areas such as systems biology, who routinely combine information from multiple biological domains and technology platforms. To address all of the above, we present MIBBI (Minimum Information for Biological and Biomedical Investigations); a web-based communal resource for such checklists, designed to act as a ‘one-stop shop’ for those exploring the range of extant checklist projects, and to foster collaborative, integrative development and ultimately promote gradual integration of checklists. (shrink)

We describe a prototype ontology-driven information system (ODIS) that exploits what we call Portion of Reality (POR) representations. The system takes both sensor data and natural language text as inputs and composes on this basis logically structured POR assertions. The goal of our prototype is to represent both natural language and sensor data within a single framework that is able to support both axiomatic reasoning and computation. In addition, the framework should be capable of discovering and representing new kinds of (...) situations and thematic roles, (e.g., roles such as agent, patient and instrument), based on new compositions of existing representations. We applied our prototype in an intelligence analysis use case to test the hypothesis that a framework of this sort can produce usefully structured information from combined natural language and sensor data inputs. We further tested our hypothesis by adding an enhanced US Air Force ontology framework to our ODIS in order to (1) process a collection of sensor data, intel reports, and mission plans; (2) build composite POR representations from these data; and (3) machine analyze the fused results to infer mission threats. (shrink)