Multi sensor data fusion allows large scale deployments for environmental monitoring applications especially in the areas like homes, other buildings and infrastructures and industries. In such areas early fire detection is of great importance as the consequences of a fire are catastrophic. This project predicts the possibility of catching fire using a multi-sensor scheme of data fusion to enhance the performance of the early fire detection process by detecting the concentration of inflammable gases in the atmosphere (...) and by measuring the atmospheric temperature. (shrink)

The overall goal of the approach developed in this paper is to estimate the likelihood of a given kinetic kill scenario between hostile spacebased adversaries using the mathematical framework of Complex Conceptual Spaces Single Observation. Conceptual spaces are a cognitive model that provide a method for systematically and automatically mimicking human decision making. For accurate decisions to be made, the fusion of both hard and soft data into a single decision framework is required. This presents several challenges to (...) this data fusion framework. The first is the challenge involved in handling multiple complex terminologies, which is addressed by drawing on a set of Space Domain Ontologies. Another challenge is the complex combinatorics involved when considering all possible feature combinations. This can be mitigated by using integer linear programming optimization that is outlined by the Complex Conceptual Spaces Single Observation mathematical model framework. A third challenge is the complicated physics that is involved in a spacecraft collision that must be addressed to obtain a better understanding of threat assessment. Overcoming these various challenges allows for a quantitative ranking for the potential of a kinetic kill collision across multiple spacecraft pairs. In addition to overcoming these challenges this paper will break down threat assessment into four domains and identify a ranking of threat both for each individual domain and for the four domains combined. Simulation results are shown to verify the developed concepts. (shrink)

This paper describes an AFOSR-supported basic research program that focuses on developing a new framework for combining hard with soft data in order to improve space situational awareness. The goal is to provide, in an automatic and near real-time fashion, a ranking of possible threats to blue assets (assets trying to be protected) from red assets (assets with hostile intentions). The approach is based on Conceptual Spaces models, which combine features from traditional associative and symbolic cognitive models. While Conceptual (...) Spaces are revolutionary, they lack an underlying mathematical framework. Several such frameworks have attempted to represent Conceptual Spaces, but by far the most robust is the model developed by Holender. His model utilizes integer linear programming in order to obtain an overall similarity value between observations and concepts that support the formation of hypotheses. This paper will describe a method for building Conceptual Spaces models for threats that utilizes ontologies as a means to provide a clear semantic foundation for this inferencing process; in particular threat ontologies and space domain ontologies are developed and employed in this approach. A space situational awareness use-case is presented involving a kinetic kill scenario and results are shown to assess the performance of this fusion-based inferencing framework. (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)

This paper explores a case example of qualitative research that applied productive hermeneutics and the central concept, fusion of horizons. Interpretation of meaning is a fusing of the researchers’ and subjects’ perspectives and serves to expand understanding. The purpose is to illustrate an exemplar of qualitative research without establishing a rigid recipe of methodology. The illustration is based on in-depth observational and textual data from an applied anthropological study conducted in western Alaska with Yup’ik hunters and fishers and (...) government agency employees as they worked towards collaborative management. The metaphor of the hermeneutical circle is showcased to help the reader understand the philosophical underpinnings and the analytical processes used to realize a meaningful interpretation. A series of organizing systems for the interpretation is described, culminating in a final organizing system to communicate a fully realized understanding of collaborative management at the time. (shrink)

This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents (...) some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well. (shrink)

Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are not only data-laden, but data are also model-laden or model filtered. In this paper I elaborate and defend the second, more controversial, component of the symbiosis view. In particular, I construct a preliminary taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. These include (...) class='Hi'>data conversion, data correction, data interpolation, data scaling, data fusion, data assimilation, and synthetic data. Each is defined and briefly illustrated with an example from the geosciences. I argue that model-filtered data are typically more accurate and reliable than the so-called raw data, and hence beneficially serve the epistemic aims of science. By illuminating the methods by which raw data are turned into scientifically useful data sets, this taxonomy provides a foundation for developing a more adequate philosophy of data. (shrink)

The question of when human life begins is critical in debates related to life issues. While there are a variety of proposals as to how an organism should be defined, many biologists and ethicists, particularly Catholics, have approached this issue by arguing that fertilization defines the beginning of a new organism. Examining the processes of fission and fusion, which take place before gastrulation, provides strong evidence for when human life beings and therefore how it should be defined. Among the (...) four dominant theories, regulative fission and fusion are the best explanations in terms of being the most consistent with the biological data. This explanation of twinning provides compelling evidence that fertilization is not a necessary condition for human generation, although it may be a sufficient condition. While fertilization generates the vast majority of human beings, additional human beings may rarely be generated during fission events. (shrink)

The article summarizes the software tool on astrophysical analysis with multi-wavelength space telescope data. It recaps the evidence analysis conducted on the Kerr-Newman black hole (KNBH). It was written prior to the article Research on the Kerr-Newman Black Hole in M82 Confirms Black Hole and White Hole Juxtapose not soon after the experiment. The conducted analysis suggested Hawking radiation is caused by the movement of ergosurfaces of the BH and serves as the primal evidence for black hole and white (...) hole juxtapose. A later data exploration was conducted with the radiation trails in the multi-wavelength data. The evidences produced corroborates with Yale professor Priyamvada Natarajan's black hole seeds theory. It implies that the electromagnetic dynamic of fusion and fission temperature determines the pressure of surface tension on the macro particles, and the mass density of the BH is determined by the electromagnetic tension between the outer ergosurface and inner ergosurface. The ring singularity of the BH and the Penrose-Hawking singularity of the BH determine the spin and gravitational singularity of the BH. Inside the ergosurfaces, the BH singularities' backward inflow causes the vicinity's rate on feeding the BH. It makes the active galactic nuclei (AGN) a semi-closed system. The density pressure is released on threshold. During the mass exchange observed by energy momentum upon the AGN's open, the macroparticle composition of the BH changes with the galactic event. This causes the expansion rate of the galaxy and contraction rate of the BH. AGN types and their relative motions determine the expansion rate of the cosmic universe in a generalized quantitative thinking. The article concludes that BH spin is caused by the asymmetric motions of AGN in the BH system. A set of the nuclear resonance caused by BH and white hole (WH) oscillation is processed with the same set of data. (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)

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)

Fixing the problem won’t be easy, but humans’ sharpened focus on an emerging philosophy of data might give us some clue about where we will be heading for.

This paper provides a method for characterizing space events using the framework of conceptual spaces. We focus specifically on estimating and ranking the likelihood of collisions between space objects. The objective is to design an approach for anticipatory decision support for space operators who can take preventive actions on the basis of assessments of relative risk. To make this possible our approach draws on the fusion of both hard and soft data within a single decision support framework. Contextual (...) data is also taken into account, for example data about space weather effects, by drawing on the Space Domain Ontologies, a large system of ontologies designed to support all aspects of space situational awareness. The framework is coupled with a mathematical programming scheme that frames a mathematically optimal approach for decision support, providing a quantitative basis for ranking potential for collision across multiple satellite pairs. The goal is to provide the broadest possible information foundation for critical assessments of collision likelihood. (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)

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)

Ontologies formally represent reality in a way that limits ambiguity and facilitates automated reasoning and data fusion, but is often daunting to the non-technical user. Thus, many researchers have endeavored to hide the formal syntax and semantics of ontologies behind the constructs of Controlled Natural Languages (CNLs), which retain the formal properties of ontologies while simultaneously presenting that information in a comprehensible natural language format. In this paper, we build upon previous work in this field by evaluating prospects (...) of implementing International Technology Alliance Controlled English (ITACE) as a middleware for ontology editing. We also discuss at length a prototype of a natural language conversational interface application designed to facilitate ontology editing via the formulation of CNL constructs. (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)

Humans and artificial intelligences (AI) will increasingly participate digitally and physically in conflicts yet there is a lack of trusted communications across agents and platforms. For example, humans in disasters and conflict already use messaging and social media to share information, however, international humanitarian relief organisations treat this information as unverifiable and untrustworthy. AI may reduce the ‘fog-of-war’ and improve outcomes, however current AI implementations are often brittle, have a narrow scope of application and wide ethical risks. Meanwhile, human error (...) causes significant civilian harms even by combatants committed to complying with international humanitarian law. AI offers an opportunity to help reduce the tragedy of war and better deliver humanitarian aid to those who need it. However, to be successful, these systems must be trusted by humans and their information systems, overcoming flawed information flows in conflict and disaster zones that continue to be marked by intermittent communications, poor situation awareness, mistrust and human errors. In this paper, we consider the integration of a communications protocol (the ‘Whiteflag protocol’), distributed ledger technology, and information fusion with artificial intelligence (AI), to improve conflict communications called “Protected Assurance Understanding Situation & Entities” PAUSE. Such a trusted human-AI communication network could provide accountable information exchange regarding protected entities, critical infrastructure; humanitarian signals and status updates for humans and machines in conflicts. Trust-based information fusion provides resource-efficient use of diverse data sources to increase the reliability of reports. AI can be used to catch human mistakes and complement human decision making, while human judgment can direct and override AI recommendations. We examine several case studies for the integration of these technologies into a trusted human-AI network for humanitarian benefit including mapping a conflict zone with civilians and combatants in real time, preparation to avoid incidents and using the network to manage misinformation. (shrink)

Iris Marion Young’s classic paper on the phenomenology of pregnancy chronicles the alienating tendencies of technology-ridden maternal care, as the mother’s subjective knowledge of the pregnancy gets overridden by the objective knowledge provided by medical personnel and technological apparatuses. Following Fredrik Svenaeus, the authors argue that maternal care is not necessarily alienating by looking specifically at the proper attention paid by sonographers in maternal care when performing ultrasound examinations. Using Martin Heidegger’s philosophy as a theoretical lens, the authors argue that (...) sonographers who cultivate technical mastery, build patient rapport, explain the process and significance of the ultrasound, and understand the patient’s world are able to provide excellent patient care. The authors utilize Hans-Georg Gadamer’s hermeneutics to show how sonographers can frame the ultrasound in a way that acknowledges both the subjective knowledge of the mother and the objective data obtained by the sonographer through the use of technology. Ultimately, the authors argue that the common practice of framing the ultrasound as the chance to “meet the baby” is inappropriate, as it exacerbates the tendency to regard objective knowledge as the only legitimate knowledge in medical contexts. They recommend a more balanced approach that elicits a fusion of horizons between the patient’s subjective knowledge and the objective data that is obtained by the sonographer via the ultrasound, thus respecting and bolstering patient autonomy. (shrink)

Recent discoveries of semantic compositionality in Japanese tits have enlivened the discussions on the presence of this phenomenon in wild animal communication. Data on semantic compositionality in wild apes are lacking, even though language experiments with captive apes have demonstrated they are capable of semantic compositionality. In this paper, I revisit the study by Boesch (Hum. Evol. 6:81–89, 1991) who investigated drumming sequences by an alpha male in a chimpanzee (_Pan troglodytes_) community in the Taï National Park, Côte d’Ivoire. (...) A reanalysis of the data reveals that the alpha male produced semantically compositional combined messages of travel direction change and resting period initiation. Unlike the Japanese tits, the elements of the compositional expression were not simply juxtaposed but displayed structural reduction, while one of the two elements in the expression coded the meanings of both elements. These processes show relative resemblance to blending and fusion in human languages. Also unlike the tits, the elements of the compositional expression did not have a fixed order, although there was a fixed distribution of drumming events across the trees used for drumming. Because the elements of the expression appear to carry verb-like meanings, the compositional expression also resembles simple verb-verb constructions and short paratactic combinations of two clauses found across languages. In conclusion, the reanalysis suggests that semantic compositionality and phenomena resembling paratactic combinations of two clauses might have been present in the communication of the last common ancestor of chimpanzees and humans, not necessarily in the vocal modality. (shrink)

(Introduction) The question of heterogeneity does not appear at first glance to be a genuinely phenomenological problem and not even a problem in general. It seems to go without saying that there is “coupling” (Paarung), association, fusion, synthesis or in general any form connection between different data of consciousness, all as it seems obvious (at least from Husserl) that there must be objectities so that we can talk about knowledge and truth. After Kant we got so used to (...) synthetic formations that we hardly think of their possibilities in principle and the problems that these are called upon to resolve. Phenomenology does nothing else but describing the synthetic process, starting with its most elementary (pre-reflective) levels, aiming thus to completely elucidate the constitution of the objectity and, by that, the functioning and the rights of reason. Now, such elucidation does not only involve an approach aimed at the how, but also, the why of this process. In other words, our attention and our theoretical interest must be directed not only towards the course of the constitutive synthesis, but also on what motivates her intrinsically. Questions like "why should he be there in general an objectity? " or "is it principally possible to associate in one form or another data belonging to to the same class or to different classes? ”, questions which are de jure and which therefore refer rather to the legality of the constitution than its more or less contingent functioning, cannot in any way be excluded from the scope of the phenomenological questioning. As much as the epistemological ideal of phenomenological description required above all that it avoid any form of abstraction and idealization, this class of questions is, if not excluded, at least left in shadow. (shrink)

The article deals with the problem of cognition in the framework of the biogenetic structuralist neurophenomenology of Charles Laughlin. The aim of the article is to study the possibilities of applying the biogenetic structuralist theory as a theoretical and methodological basis for the study of consciousness in Laughlin’s theory. A feature of biogenetic structuralism is the interdisciplinary fusion of anthropology, psychology, and neuroscience. The methodology of biogenetic structuralism allows exploring universal structures of consciousness, which are caused by the genetically (...) predisposed organization of the human nervous system. Universal structures of consciousness include structures that mediate human language, knowledge of time and space. It is shown that the problem of cognition is realized in neurognostic models, which are compared with the operational environment. Neurognostic models include both the real nature of man as an organism and the external environment of the organism. Laughlin introduces the concept of a cognitive environment to designate a set of neurognostic models that can potentially be captured by the area of consciousness. He relies on the idea of a cognitive environment, which is essentially intentional in its organization. The polar interaction between the prefrontal cortex and the sensory cortex of the human brain gives rise to the intentionality of consciousness. Laughlin explains the work of the human cerebral cortex neurognostically as omnipresent for human consciousness, and independent of the cultural background. The cerebral cortex is a field of neural activity that arises and dissolves in temporal sequences and coordinates with cognitive processes that connect meaning and form into a single structure in consciousness. The experience of consciousness suggests a sensitive sphere of the cerebral cortex ascertains the meaningful, phenomenal world. The biogenetic structuralist methodology allows to development of an idea of the intentional structure and uniqueness of consciousness. The biogenetic structuralist approach is heuristic for modern science because, firstly, this approach creates the maximum opportunity to include data obtained from naturalistic, ethnographic, anatomical, clinical, and experimental sources; secondly, biogenetic data have the widest empirical and phenomenological rationale; thirdly, biogenetic concepts are defined in the context of a holistic understanding of the phenomenon through the uniqueness of consciousness. (shrink)

I criticise a paper by Peter Forrest in which he argues that a principle of unrestricted countable fusion has paradoxical consequences. I argue that the paradoxical consequences that he exhibits may be due to his Whiteheadean assumptions about the nature of spacetime rather than to the principle of unrestricted countable fusion.

This paper raises some concerns about Paul Humphreys’ fusion emergence in general and about his core example of fusion emergence (i.e., covalent bonding) in particular. It argues that the extent to which covalent bonding undermines the idea that our world’s ontology is wholly compositional has been overstated.

Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate (...) the patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research. (shrink)

There are two main ways in which the notion of mereological fusion is usually defined in the current literature in mereology which have been labelled ‘Leśniewski fusion’ and ‘Goodman fusion’. It is well-known that, with Minimal Mereology as the background theory, every Leśniewski fusion also qualifies as a Goodman fusion. However, the converse does not hold unless stronger mereological principles are assumed. In this paper I will discuss how the gap between the two notions can (...) be filled, focussing in particular on two specific sets of principles that appear to be of particular philosophical interest. The first way to make the two notions equivalent can be used to shed some interesting light on the kind of intuition both notions seem to articulate. The second shows the importance of a little-known mereological principle which I will call ‘Mild Supplementation’. As I will show, the mereology obtained by adding Mild Supplementation to Minimal Mereology occupies an interesting position in the landscape of theories that are stronger than Minimal Mereology but weaker than what Achille Varzi and Roberto Casati have labelled ‘Extensional Mereology’. (shrink)

We face reality presented with the data of conscious experience and nothing else. The project of early modern philosophy was to build a complete theory of the world from this starting point, with no cheating. Crucial to this starting point is the data of conscious sensory experience – sense data. Attempts to avoid this project often argue that the very idea of sense data is confused. But the sense-data way of talking, the sense-data language, (...) can be freed from every blemish using ideas from contemporary metaontology. We can adopt a sense-data framework that vindicates the traditional claims of sense-data theories and leads to plausible theories of perception and color. We can, we should, and in a sense, we must. Yet when we do, we face the traditional problem of external world skepticism, head-on. The real challenge of skepticism is forced upon us; it cannot honestly be avoided using externalist tricks, burden of proof shifting, or other razzle dazzle. But the challenge can be met: we are rational to posit the external world as the best explanation of the many synchronic and diachronic patterns over our sense-data. This paper argues for all of these points and ends with a plea for analytic empiricism – a traditional sense-data version of empiricism that uses all of the tools of analytic philosophy while avoiding the more questionable doctrines of the Vienna Circle (phenomenalism, verificationism). Analytic empiricism is our last best hope for completing the great philosophical project of early modern philosophy. (shrink)

Nowadays, protecting trust in social sciences also means engaging in open community dialogue, which helps to safeguard robustness and improve efficiency of research methods. The combination of open data, open review and open dialogue may sound simple but implementation in the real world will not be straightforward. However, in view of Begley and Ellis’s (2012) statement that, “the scientific process demands the highest standards of quality, ethics and rigour,” they are worth implementing. More importantly, they are feasible to work (...) on and likely will help to restore plausibility to social sciences research. Therefore, I feel it likely that the triplet of open data, open review and open dialogue will gradually emerge to become policy requirements regardless of the research funding source. (shrink)

Digital data help data scientists and epidemiologists track and predict outbreaks of disease. Mobile phone GPS data, social media data, or other forms of information updates such as the progress of epidemics are used by epidemiologists to recognize disease spread among specific groups of people. Targeting groups as potential carriers of a disease, rather than addressing individuals as patients, risks causing harm to groups. While there are rules and obligations at the level of the individual, we (...) have to reach a stage in the development of data analytics where groups are protected as entities. This chapter offers a deeper examination of harms to the groups. (shrink)

Data subject rights provide data controllers with obligations that can help with transparency, giving data subjects some control over their personal data. To date, a growing number of researchers have used these data subject rights as a methodology for data collection in research studies. No one, however, has gathered and analysed different academic research studies that use data subject rights as a methodology for data collection. To this end, we conducted a systematic (...) literature review that searched, compiled, and analysed 32 academic studies that use data subject rights as a data collection method. We find that the right of access is the most commonly-used data subject right by researchers, most studies are interested in measuring data subject rights compliance, and that a variety of difficulties exist in conducting research studies with data subject rights. We conclude that researchers should explore other data subject rights for alternative purposes, ease the process of exercising data subject rights, and improve the scalability of these studies. (shrink)

To obtain effective fusion results of multi source evidences with different importance, an evidence fusion method with importance discounting factors based on neutrosopic probability analysis in DSmT framework is proposed. First, the reasonable evidence sources are selected out based on the statistical analysis of the pignistic probability functions of single focal elements. Secondly, the neutrosophic probability analysis is conducted based on the similarities of the pignistic probability functions from the prior evidence knowledge of the reasonable evidence sources. Thirdly, (...) the importance discounting factors of the reasonable evidence sources are obtained based on the neutrosophic probability analysis and the reliability discounting factors of the real-time evidences are calculated based on probabilistic-based distances. Fourthly, the real-time evidences are discounted by the importance discounting factors and then the evidences with the mass assignments of neutrosophic empty sets are discounted by the reliability discounting factors. Finally, DSmT+PCR5 of importance discounted evidences is applied. Experimental examples show that the decision results based on the proposed fusion method are different from the results based on the existed fusion methods. Simulation experiments of recognition fusion are performed and the superiority of proposed method is testified well by the simulation results. (shrink)

We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides (...) insight into the common but little-discussed practices of iteratively reusing and repurposing data, which result in many datasets’ having a phylogeny—an origin and complex evolutionary history—that is relevant to their evaluation and future use. We relate these insights to the open-data and data-rescue movements, and highlight several future avenues of research that build on the PR view of data. (shrink)

While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what (...) are experimental artifacts and what is the most productive way of dealing with them? In this paper, I approach these questions by exploring the ways in which experimenters in psychology simultaneously exploit and suppress the reactivity of their subject matter in order to produce experimental data that speak to the question or subject matter at hand. Highlighting the artificiality of experimental data, I raise the question of what distinguishes a genuine experimental result from an experimental artifact. My analysis construes experimental results as the outcomes of inferences from the data that take material background assumptions as auxiliary premises. Artifacts occur when one or more of these background assumptions are false, such that the data do not reliably serve the purposes they were generated for. I conclude by laying out the ways in which my analysis of data quality is relevant to, and informed by, recent debates about the replicability of experimental results. (shrink)

Between 2006 and 2011, humanity accumulated 1,600 EB of data. As a result of this growth, there is now more data produced than available storage. This article explores the problem of “Big Data,” arguing for an epistemological approach as a possible solution to this ever-increasing challenge.

The potential to collect brain data more directly, with higher resolution, and in greater amounts has heightened worries about mental and brain privacy. In order to manage the risks to individuals posed by these privacy challenges, some have suggested codifying new privacy rights, including a right to “mental privacy.” In this paper, we consider these arguments and conclude that while neurotechnologies do raise significant privacy concerns, such concerns are—at least for now—no different from those raised by other well-understood (...) class='Hi'>data collection technologies, such as gene sequencing tools and online surveillance. To better understand the privacy stakes of brain data, we suggest the use of a conceptual framework from information ethics, Helen Nissenbaum’s “contextual integrity” theory. To illustrate the importance of context, we examine neurotechnologies and the information flows they produce in three familiar contexts—healthcare and medical research, criminal justice, and consumer marketing. We argue that by emphasizing what is distinct about brain privacy issues, rather than what they share with other data privacy concerns, risks weakening broader efforts to enact more robust privacy law and policy. (shrink)

Culture as a dynamic system of meaningful relations can naturally accommodate a hermeneutic analysis. In this essay, the notion of Gadamer’s hermeneutics as involving interpretable meaning throughout experiential reality permits a natural concordance with an understanding of culture as meaningful. The Gadamerian idea that prejudices inform the horizons that make our experiences intelligible is applied to the view that culture is both a self-enclosed structure that is given by one’s horizon and one that continuously points past this horizon in genuine (...) dialogue. Nevertheless, in seeing culture as a coherent system that transcends itself, we are consequently faced with a dilemma regarding the evolution of one’s cultural horizons: whether past horizons can survive the creation of novel ones through dialogue. However, this may be resolved through Gadamer’s understanding of the functions of sameness and difference within horizonal evolution, and how these functions feature in the distinction between a shared ontological ground and the horizons through which the ground is interpreted. Ultimately, we showcase how it is noncontradictory to suppose that culture is both self- and other-referential. (shrink)

Dr Miranda Anderson is an Honorary Fellow in History, Classics and Archaeology at the University of Edinburgh and an Associate Lecturer at the Open University. She has held several prestigious fellowships and was principal investigator of an AHRC-funded project, titled ‘The Art of Distributed Cognition’, which involved collaboration with the Talbot Rice Gallery. Her work has investigated the relations between cognition and culture, particularly literary works, challenging the boundaries between disciplines and engaging with numerous contemporary science, technology and society (STS) (...) questions. In this perspective article, she evokes the ‘fission-fusion’ concept on which she has been working for some years now – a concept that contributes to debates surrounding the issue of identity by drawing on the arts, humanities, social sciences, and natural sciences. (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)

This essay illustrates the main aspects of the discussion between Brentano and Stumpf about «tonal fusion». In his Tonpsychologie, Stumpf essentially moved from a Brentanian standpoint. Yet, he did not adopt Brentano’s subsequently developed new theory of «sensible qualities», so that a polemic eventually arouse between them. Far from representing a marginal issue, the episode is relevant to our understanding of their relationship. The discussion as to the mechanism of tonal fusion reveals a general divergence between Brentano and (...) Stumpf concerning the idea of human sensibility as a whole and of the method of psychology. (shrink)

A growing awareness of the lack of reproducibility has undermined society’s trust and esteem in social sciences. In some cases, well-known results have been fabricated or the underlying data have turned out to have weak technical foundations.

The first few years of the 21st century were characterised by a progressive loss of privacy. Two phenomena converged to give rise to the data economy: the realisation that data trails from users interacting with technology could be used to develop personalised advertising, and a concern for security that led authorities to use such personal data for the purposes of intelligence and policing. In contrast to the early days of the data economy and internet surveillance, the (...) last few years have witnessed a rising concern for privacy. As bad data practices have come to light, citizens are starting to understand the real cost of using online digital technologies. Two events stamped 2018 as a landmark year for privacy: the Cambridge Analytica scandal, and the implementation of the European Union’s General Data Protection Regulation (GDPR). The former showed the extent to which personal data has been shared without data subjects’ knowledge and consent and many times for unacceptable purposes, such as swaying elections. The latter inaugurated the beginning of robust data protection regulation in the digital age. Getting privacy right is one of the biggest challenges of this new decade of the 21st century. The past year has shown that there is still much work to be done on privacy to tame the darkest aspects of the data economy. As data scandals continue to emerge, questions abound as to how to interpret and enforce regulation, how to design new and better laws, how to complement regulation with better ethics, and how to find technical solutions to data problems. The aim of the research project Data, Privacy, and the Individual is to contribute to a better understanding of the ethics of privacy and of differential privacy. The outcomes of the project are seven research papers on privacy, a survey, and this final report, which summarises each research paper, and goes on to offer a set of reflections and recommendations to implement best practices regarding privacy. (shrink)

Data mining possess a significant threat to ethics, privacy, and legality, especially when we consider the fact that data mining makes it difficult for an individual or consumer (in the case of a company) to control accessibility and usage of his data. Individuals should be able to control how his/ her data in the data warehouse is being access and utilize while at the same time providing enabling environment which enforces legality, privacy and ethicality on (...) data scientists, or data engineer during data mining process. This paper review issues of legality, privacy, and ethicality in data mining, review processes of Data mining, and also proposes solution to current ethical and privacy issue in data mining. It introduces a new method which enforces data mining without infringing on the privacy of individual or consumer whose data are being used. The sole aim of this paper is to propose a new method of mining data which restricts scientists within the constraints of legality, privacy, and ethicality. (shrink)

By moving beyond the overly emphasized image of a “fusion of horizons” and focusing on Gadamer’s concept of “play,” this paper aims to rehabilitate the dynamic and multi-vocal character of understanding as Gadamer conceives it, and to argue that “difference” is the life-blood of understanding against the recurring charge that Gadamer’s hermeneutics is fundamentally antagonistic to otherness.

We simulate trial data to test speculative claims about research methods, such as the impact of publication bias.

In this essay, we advocate that the issue of health data ethics should no longer be considered on the level of individual scientists or research labs, but rather as a problem involving all stakeholders, from publishers, funders, ethical committees to governments, for the sake of research integrity.

The theory of knowledge in early twentieth-century Anglo American philosophy was oriented toward phenomenally described cognition. There was a healthy respect for the mind-body problem, which meant that phenomena in both the mental and physical domains were taken seriously. Bertrand Russell's developing position on sense-data and momentary particulars drew upon, and ultimately became like, the neutral monism of Ernst Mach and William James. Due to a more recent behaviorist and physicalist inspired "fear of the mental", this development has been (...) down-played in historical work on early analytic philosophy. Such neglect assumes that the "linguistic turn" is a proper and permanent effect of twentieth-century philosophy, an assumption that distorts early analytic historiography, and begs a substantive philosophical question about thought and cognition. (shrink)

Biodiversity science is in a pivotal period when diverse groups of actors—including researchers, businesses, national governments, and Indigenous Peoples—are negotiating wide-ranging norms for governing and managing biodiversity data in digital repositories. These repositories, often called biodiversity data portals, are a type of organization for which governance can address or perpetuate the colonial history of biodiversity science and current inequities. Researchers and Indigenous Peoples are developing and implementing new strategies to examine and change assumptions about which agents should count (...) as salient participants in scientific projects, especially in projects that build and manage large digital data portals. Two notable efforts are the FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective benefit, Authority, Responsibility, Ethics) Principles for scientific data management and governance. To characterize how these principles influence the governance of biodiversity data portals, we develop an account of fit-for-use data that makes explicit its social as well as technical conditions in relation to agents and purposes. The FAIR Principles, already widely adopted by biodiversity researchers, prioritize machine agents and efficient computation, while the CARE Principles prioritize Indigenous Peoples and their data sovereignty. Both illustrate the potency of an emerging general strategy by which groups of actors craft and implement governance principles for data fitness-of-use to change assumptions about who are salient participants in data science. (shrink)