climate scientists have been engaged in a decades-long debate over the standing of satellite measurements of the temperature trends of the atmosphere above the surface of the earth. This is especially significant because skeptics of global warming and the greenhouse effect have utilized this debate to spread doubt about global climate models used to predict future states of climate. I use this case from an under-studied science to illustrate two distinct philosophical approaches to the relation among data, scientists, measurement, (...) models, and theory. I argue that distinguishing between 'direct' empiricist and 'complex' empiricist approaches helps us understand and analyze this important scientific episode. I also introduce a complex empiricist account of testing and evaluation, and contrast it with the basic Hypothetico-Deductive approach to the climate models used by the direct empiricists. This more developed complex empiricist apporach will serve philosophy of science well, as computational models become more wide-spread in the sciences. (shrink)

The history of climate research in the 20th century has been characterised by a crucial shift from a geography-oriented, two-dimensional approach towards a physics-based, three-dimensional concept of climate. In the 1930s, the introduction of new technology, such as radiosondes, enabled climatologists to investigate the high atmosphere, which had previously been out of reach. This “conquest of the third dimension” challenged the surface-oriented, geographical notion of climate patterns and opened up climatology to a three-dimensional approach, which deeply changed the character of (...) climate research. Two decades later, by drilling deep into polar glaciers and using the downward vertical dimension as an archive of the earth's history, ice core scientists began to reconstruct past climates layer by layer. The data retrieved in deep glacial layers contributed crucially to a temporal expansion of climate history far beyond human timescales. However, the inaccessibility of glaciers and the practical challenges of bringing fragile fragments of ice into transnational networks of scientific exchange meant that this vertical extension of climate knowledge production proceeded through a range of new scientific practices, and was shaped by new forms of international collaboration. Furthermore, this vertical approach to glaciers also asked for a new understanding of glacier volume. Drawing on archival and printed sources, I argue that ice core research represented a second discovery of the third dimension, this time downwards into the depth of the earth's surface, but again with decisive consequences for the research practice, for collaboration politics, and for understandings of climate, spatially as well as temporally. (shrink)

Early versions of satellite and radiosonde datasets suggested that the tropical surface had warmed more than the troposphere, while climate models consistently showed tropospheric amplification of surface warming in response to human-caused increases in greenhouse gases. We revisit such comparisons here using new observational estimates of surface and tropospheric temperature changes. We find that there is no longer a serious discrepancy between modeled and observed trends in the tropics. Our results contradict a recent claim that all simulated temperature trends (...) in the tropical troposphere are inconsistent with observations. This claim was based on the use of older radiosonde and satellite datasets and on two methodological errors: the neglect of observational trend uncertainties introduced by interannual climate variability and application of an inappropriate statistical “consistency test”.This emerging reconciliation of models and observations has two primary explanations. First, because of changes in the treatment of buoy and satellite information, new surface temperature datasets yield slightly reduced tropical warming relative to earlier versions. Second, recently developed satellite and radiosonde datasets now show larger warming of the tropical lower troposphere. In the case of a new satellite dataset from remote sensing systems, enhancedRSS warming is due to an improved procedure of adjusting for inter-satellite biases. When the RSS-derived tropospheric temperature trend is compared with four different observed estimates of surface temperature change, the surface warming is invariably amplified in the tropical troposphere, consistent with model results. Even if we use data from a second satellite dataset with smaller tropospheric warming than in remote sensing systems RSS, observed tropical lapse rates are not significantly different from those in all model simulations.Our results contradict a recent claim that all simulated temperature trends in the tropical troposphere and in tropical lapse rates are inconsistent with observations. This claim was based on the use of older radiosonde and satellite datasets and on two methodological errors: the neglect of observational trend uncertainties introduced by interannual climate variability and application of an inappropriate statistical “consistency test”. (shrink)

Philosophical Methodology offers an up-to-date assessment of different methods of doing philosophy, and develops a novel account of the structure and goals of inquiry, a fresh analysis of philosophical data, and a nuanced approach to philosophical theorizing. It allows philosophers and students of philosophy to better understand their topics, and shows how philosophy can continue to make progress in answering its central questions.

This chapter addresses two questions. First, if knowledge is accounted information, how are we supposed (to apply this analysis in order) to understand perceptual knowledge and knowledge by testimony? In the first part of the chapter, I articulate an answer in terms of a re-interpretation of perception and testimony as data providers rather than full-blown cases of knowledge. Second, if perception and testimony are correctly understood as data providers, how are we supposed (to apply this analysis in order) (...) to understand the semantic value of the data provided by such processes? In the second part of the chapter, I argue in favour of a constructionist hypothesis about how data may become meaningful for human cognitive agents through a process of repurposing of natural data/signals. The conclusion of the chapter is that human agents are natural-born data hackers. (shrink)

This paper examines one of the historical antecedents of Big Data, the social physics movement. Its origins are in the scientific revolution of the 17th century in Western Europe. But it is not named as such until the middle of the 19th century, and not formally institutionalized until another hundred years later when it is associated with work by George Zipf and John Stewart. Social physics is marked by the belief that large-scale statistical measurement of social variables reveals underlying (...) relational patterns that can be explained by theories and laws found in natural science, and physics in particular. This larger epistemological position is known as monism, the idea that there is only one set of principles that applies to the explanation of both natural and social worlds. Social physics entered geography through the work of the mid-20th-century geographer William Warntz, who developed his own spatial version called “macrogeography.” It involved the computation of large data sets, made ever easier with the contemporaneous development of the computer, joined with the gravitational potential model. Our argument is that Warntz's concerns with numeracy, large data sets, machine-based computing power, relatively simple mathematical formulas drawn from natural science, and an isomorphism between natural and social worlds became grounds on which Big Data later staked its claim to knowledge; it is a past that has not yet passed. (shrink)

A widespread need to explain the behavior and outcomes of AI-based systems has emerged, due to their ubiquitous presence. Thus, providing renewed momentum to the relatively new research area of eXplainable AI (XAI). Nowadays, the importance of XAI lies in the fact that the increasing control transference to this kind of system for decision making -or, at least, its use for assisting executive stakeholders- already affects many sensitive realms (as in Politics, Social Sciences, or Law). The decision-making power handover to (...) opaque AI systems makes mandatory explaining those, primarily in application scenarios where the stakeholders are unaware of both the high technology applied and the basic principles governing the technological solutions. The issue should not be reduced to a merely technical problem; the explainer would be compelled to transmit richer knowledge about the system (including its role within the informational ecosystem where he/she works). To achieve such an aim, the explainer could exploit, if necessary, practices from other scientific and humanistic areas. The first aim of the paper is to emphasize and justify the need for a multidisciplinary approach that is beneficiated from part of the scientific and philosophical corpus on Explaining, underscoring the particular nuances of the issue within the field of Data Science. The second objective is to develop some arguments justifying the authors’ bet by a more relevant role of ideas inspired by, on the one hand, formal techniques from Knowledge Representation and Reasoning, and on the other hand, the modeling of human reasoning when facing the explanation. This way, explaining modeling practices would seek a sound balance between the pure technical justification and the explainer-explainee agreement. (shrink)

In this paper, we present our research on data mining approaches with the existence of obstacles. Although there are a lot of algorithms designed to detect clusters with obstacles, few algorithms can detect clusters and outliers simultaneously and interactively. We here extend our original research [Shi, Zhang, Towards Exploring Interactive Relationship between Clusters and Outliers in Multi-Dimensional Data Analysis, 518–519: IEEE Computer Society, 2005] on iterative cluster and outlier detection to study the problem of detecting cluster and outliers (...) iteratively with the presence of obstacles. Clusters and outliers are concepts of the same importance, so it is necessary to treat clusters and outliers in the same way in data analysis. In this algorithm, clusters are detected and adjusted according to the intra-relationship within clusters and the inter-relationship between clusters and outliers, and vice versa. The adjustment and modification of the clusters and outliers are performed iteratively until a certain termination condition is reached. This data processing algorithm can be applied in many fields such as pattern recognition, data clustering and signal processing. (shrink)

Computerized medical personal registers are created for administrative purposes but are frequently used in research. It can be shown that this divergence of aims deeply affects the validity of the diagnosis in register research. The diagnostic process is embedded within the process of creating the data base. This process is guided by the aims for making diagnosis.Five different aims for making diagnosis in clinical practice have been analysed and eight suggestions for validity control are proposed on the basis of (...) the study. (shrink)

As people’s lives get better and better, more and more people choose to travel and with that comes the demand for more transportation. For now, traditional transportation hubs can temporarily meet people’s travel needs. If driven by big data concepts and methods, the various capabilities of high-speed rail transportation hubs will be sublimated, and the regional economy will be in line with the prosperity of this place. Proportionally, railway hubs are extremely attractive to the rapid growth of the regional (...) economy. This paper takes the high-speed railway hub construction model under big data as the research object and verifies the reliability of the research model and the development of economic regions based on the high-speed railway data in recent years as reference parameters. This article selects the panel data of railway transportation and regional economy in China’s provinces for 10 consecutive years from 2011 to 2020. Among them, seven indicators were selected for railway transportation: passenger volume, freight volume, passenger turnover, cargo turnover, number of railway employees, railway transportation industry fixed asset investment and construction scale, and per capita railway network density. In terms of regional economy, six indicators were selected: regional GDP, per capita GDP, per capita investment in fixed assets, per capita total retail sales of consumer goods, per capita investment in imports and exports, and the proportion of the added value of the tertiary industry in GDP. The experimental results prove that each sample is tested in pairs, the standard error level of the mean is 0.002, which is less than 0.05, and high-speed railway construction can finally achieve economic integration. By improving the development of high-speed railways, continuously shortening the distance between time and space, breaking regional trade barriers, and reducing the cost of commodity circulation, industrial interaction and coordinated development between different regions can be effectively promoted. (shrink)

Since the beginnings of the Semantic Web, ontologies have played key roles in the design and deployment of new semantic technologies. Yet over the years, the level of collaboration between the Sema...

ABSTRACTJust as accountability policies have led to increased levels of teacher data use, teachers have begun to increase the extent to which students track and analyse data about their own learnin...

Research question The secondary research use of treatment data has the potential to expand medical knowledge and improve patient care. Hospitals play an important role in systematic secondary research use: they generate large amounts of treatment data and are supposed to establish the necessary structures for their use in research. This raises the ethical question: do hospitals have a moral duty to support secondary research use of treatment data by establishing and operating the necessary resources and infrastructure? (...) Procedure Our aim is to outline a conceptual framework to discuss the question and to propose a first normative position. Building on insights from business and organizational ethics, we develop a conceptual framework in which we view hospitals as moral actors. Our normative-ethical analysis is based on a reconstructive stakeholder approach, in which we identify the following general duties of hospitals: orientation towards patient wellbeing; cost efficiency; enabling employees to act in accordance with professional ethical standards; supporting public health and research. We examine whether these general duties provide reasons for a specific duty of hospitals to support secondary research use of treatment data. We discuss potential objections to such a duty arising from other, potentially conflicting general duties of hospitals (e.g., data protection), from practice (e.g., costs/resources), or related discourses (data ownership). Conclusion Certain general duties (orientation towards patient wellbeing, cost efficiency, support of public health) justify a duty of hospitals to support secondary research use of treatment data. The duty to enable employees to act in accordance with professional ethical standards is only an indirect reason; the duty to support research applies solely to university hospitals. Potential objections apply to a certain extent but can be mitigated through targeted measures. (shrink)

Two meta-analyses of pharmacological research are presented, demonstrating that psychoactive drugs have consistent effects on EEG and sleep outside of their effects on REM sleep, and demonstrating that drugs other than those affecting sleep neurotransmitter systems and REM sleep can also alter reported nightmare occurrence. These data suggest that the neurobiology data terrain outside activation-synthesis may include sleep and dream electrophysiology, cognitive reports of dreaming, effects of alterations in consciousness on dreaming, immunology and host defense, and clinical therapies (...) for sleep disorders. (shrink)

The interaction of automated vehicles with vulnerable road users is one of the greatest challenges in the development of automated driving functions. In order to improve efficiency and ensure the safety of mixed traffic, ADF need to understand the intention of vulnerable road users, to adapt to their driving behavior, and to show its intention. However, this communication may occur in an implicit way, meaning they may communicate with vulnerable road users by using dynamic information, such as speed, distance, etc. (...) Therefore, investigating patterns of implicit communication of human drivers with vulnerable road users is relevant for developing ADF. The aim of this study is to identify the patterns of implicit communication of human drivers with vulnerable road users. For this purpose, the interaction between right-turning motorists and crossing cyclists was investigated at a traffic light controlled urban intersection. In the scenario, motorists and cyclists had a green signal at the same time, but cyclist had right-of-way. Using the Application Platform for Intelligent Mobility Research Intersection, trajectory and video data were recorded at an intersection in Braunschweig, Germany. Data had been recorded for 4 weeks. Based on the criticality metric post-encroachment time and quality of the recorded trajectory, 206 cases of interaction were selected for further analyses. According to the video annotation, when approaching the intersection, three common communication patterns were identified: no yield, motorists, who should yield to cyclists, crossed the intersection first while forcing right-of-way; active yield, motorists, who were in front of cyclists, gave the right-of-way; passive yield, motorists, who were behind cyclists, had to give the right-of-way. The analysis of the trajectory data revealed different patterns of changes in time advantage in these three categories. Additionally, the communication patterns were evaluated with regard to frequency of occurrence, efficiency, and safety. The findings of this study may provide knowledge for the implementation of a communication strategy for ADF, contributing to traffic efficiency as well as ensuring safety in the interaction with vulnerable road users. (shrink)

The ethical and social implications of data mining, algorithmic curation and automation in the context of social media have been of heightened concern for a range of researchers with interests in digital media in recent years, with particular concerns about privacy arising in the context of mobile and locative media. Despite their wide adoption and economic importance, mobile dating apps have received little scholarly attention from this perspective – but they are intense sites of data generation, algorithmic processing, (...) and cross-platform data-sharing; bound up with competing cultures of production, exploitation and use. In this paper, we describe the ways various forms of data are incorporated into, and emerge from, hook-up apps’ business logics, socio-technical arrangements, and cultures of use to produce multiple and intersecting data cultures. We propose a multi-layered research agenda for critical and empirical inquiry into this field, and suggest appropriate conceptual and methodological frameworks for exploring the social and political challenges of data cultures. (shrink)

Synthetic biology, as an engineering approach to biological systems, has the potential to disruptively innovate the development of vaccines, therapeutics, and diagnostics. Data accessibility and differences in data-usage capabilities are important factors in shaping this innovation landscape. In this paper, the data that underpin synthetic biology responses to the COVID-19 pandemic are analyzed as positional information goods—goods whose value depends on exclusivity. The positionality of biological data impacts the ability to guide innovations toward societally preferred goals. (...) From both an ethical and economic point of view, positionality can lead to suboptimal as well as beneficial situations. When aiming for responsible innovation (i.e. embedding societal deliberation in the innovation process), it is important to consider hurdles and facilitators in data access and use. Central governance and knowledge commons provide routes to mitigate the negative effects of data positionality. (shrink)

Before a general cognitive model for recurrent complex visual hallucinations (RCVH) is accepted, there must be more research into the neuropsychological and cognitive characteristics of the various disorders in which they occur. Currently available data are insufficient to distinguish whether the similar phenomenology of RCVH across different disorders is in fact produced by a single or by multiple cognitive mechanisms.

This study investigates the sampled-data admissibility problem for a singular system. The objective of this paper is to design a sampled-data controller to ensure the admissibility of a singular system and to construct an appropriate Lyapunov–Krasovskii functional to get less conservative results for the sampled-data singular system. To accomplish these objectives, the system is converted into a time-delay system by the input delay approach firstly, and both lower and upper bounds of the delay are considered. Secondly, by (...) introducing a suitable LKF, the admissibility criteria are obtained. Then, when estimating the derivative of the LKF, a relaxation variable is introduced by the method of reciprocally convex inequality, and it is proved that the conservatism is reduced. Finally, two numerical examples are given to prove that the designed sampled-data controller can ensure the states of the systems under the influence of external interference. (shrink)

BackgroundA growing number of studies show the potential of loyalty card data for use in health research. However, research into public perceptions of using this data is limited. This study aimed to investigate public attitudes towards donating loyalty card data for academic health research, and the safeguards the public would want to see implemented. The way in which participant attitudes varied according to whether loyalty card data would be used for either cancer or COVID-19 research was (...) also examined.MethodsParticipants were recruited via Prolific Academic to take part in semi-structured telephone interviews, with questions focused on data sharing related to either COVID-19 or ovarian/bowel cancer as the proposed health condition to be researched. Content analysis was used to identify sub-themes corresponding to the two a priori themes, attitudes and safeguards.ResultsParticipant attitudes were found to fall into two categories, either rational or emotional. Under rational, most participants were in favour of sharing loyalty card data. Support of health research was seen as an important reason to donate such data, with loyalty card logs being considered as already within the public domain. With increased understanding of research purpose, participants expressed higher willingness to donate data. Within the emotional category, participants shared fears about revealing location information and of third parties obtaining their data. With regards to safeguards, participants described the importance of anonymisation and the level of data detail; the control, convenience and choice they desired in sharing data; and the need for transparency and data security. The change in hypothetical purpose of the data sharing, from Covid-19 to cancer research, had no impact on participants’ decision to donate, although did affect their understanding of how loyalty card data could be used.ConclusionsBased on interviews with the public, this study contributes recommendations for those researchers and the wider policy community seeking to obtain loyalty card data for health research. Whilst participants were largely in favour of donating loyalty card data for academic health research, information, choice and appropriate safeguards are all exposed as prerequisites upon which decisions are made. (shrink)

Christiansen & Chater propose that language comprehenders must immediately compress perceptual data by “chunking” them into higher-level categories. Effective language understanding, however, requires maintaining perceptual information long enough to integrate it with downstream cues. Indeed, recent results suggest comprehenders do this. Although cognitive systems are undoubtedly limited, frameworks that do not take into account the tasks that these systems evolved to solve risk missing important insights.

The present study adopts both empirical and theoretical methods for the analysis of the acquisition of English sentence stress based on Optimality Theory, aiming to overcome mispronunciation of English sentence stress. Optimality Theory has a dramatic impact on most areas in linguistics besides phonology. The acoustic software Praat is chosen to collect and label data as the basis of the empirical method. Then, through analyzing the four major principles of distribution of sentence stress and based on the analysis of (...) Optimality Theory, the software Praat, and SPSS, the researcher can present the following findings: firstly, the constraint hierarchical ranking of nonnative speakers is DEP-IO >> NEW-IP >> ALIGN-IP-LEFT >> ALIGN-IP-RIGHT. Secondly, the native speakers also undergo the demotion of constraint hierarchical ranking: NEW-IP >> DEP-IO >> ALIGN-IP-RIGHT >> ALIGN-IP-LEFT. Thirdly, the constraint in each demotion of constraint hierarchical ranking during different stages is as follows: NEW-IP constraint moves from the undominated position to the dominated position in the hierarchy; ALIGN-IP-RIGHT and ALIGN-IP-LEFT constraints move from the dominated position to the lower position in the hierarchy. Through the specific analysis, the researcher draws a conclusion that the varied reasons affect the nonnative speakers to master the distribution of sentence stress due to their incorrect position in the demotion of constraint hierarchical ranking. (shrink)

In order to study the intelligent collection system of moving object trajectory data under cloud computing, information useful to passengers and taxi drivers is collected from massive trajectory data. This paper uses cloud computing technology, through clustering algorithm and density-based DBSCAN algorithm combined with Map Reduce programming model and design trajectory clustering algorithm. The results show that based on the 8-day data of 15,000 taxis in Shenzhen, the characteristic time period is determined. The passenger hot spot area (...) is obtained by clustering the passenger load points in each time period, which verifies the feasibility of the passenger load point recommendation application based on trajectory clustering. Therefore, in the absence of holidays, the number of passenger hotspots tends to be stable. It is reliable to perform cluster analysis. The recommended application has been demonstrated through experiments, and the implementation results show the rationality of the recommended application design and the feasibility of practice. (shrink)

If you are an anthropologist wanting to use digital methods or programming as part of your research, where do you start? In this commentary, we discuss three ways in which anthropologists can use computational tools to enhance, support, and complement ethnographic methods. By presenting our reflections, we hope to contribute to the stirring conversations about the potential future role of data science vis-a-vis anthropology and ethnography, and to inspire other anthropologists to take up the use of digital methods, programming, (...) and computational tools in their own research. (shrink)

The wanton dissemination of network pseudohealth information has brought great harm to people’s health, life, and property. It is important to detect and identify network pseudohealth information. Based on this, this paper defines the concepts of pseudohealth information, data block, and data block integration, designs an architecture that combines the latent Dirichlet allocation algorithm and data block update integration, and proposes the combination algorithm model. In addition, crawler technology is used to crawl the pseudohealth information transmitted on (...) the Sina Weibo platform during the “epidemic situation” from February to March 2020 for the simulation test on the experimental case dataset. The research results show that the LDA model can deeply mine the semantic information of network pseudohealth information, obtain the features of document-topic distribution, and classify and train topic features as input variables; the dataset partitioning method can effectively block data according to the text attributes and class labels of network pseudohealth information and can accurately classify and integrate the block data through the data block reintegration method; and considering that the combination model has certain limitations on the detection of network pseudohealth information, the support vector machine model can extract the granularity content of data blocks in pseudohealth information in real time, thus greatly improving the recognition performance of the combination model. (shrink)

This book examines several epistemological regimes in studies of numerical data over the last four centuries. It distinguishes these regimes and mobilises questions present in the philosophy of science, sociology and historical works throughout the 20th century. Attention is given to the skills of scholars and their methods, their assumptions, and the socio-historical conditions that made calculations and their interpretations possible. In doing so, questions posed as early as Émile Durkheim’s and Ernst Cassirer’s ones are revisited and the concept (...) of symbolic form is put to the test in this particular survey, conducted over long period of time. Although distinct from a methodological and epistemological point of view, today these regimes may be found together in the toolbox of statisticians and those who comment on their conclusions. As such, the book is addressed to social scientists and historians and all those who are interested in numerical productions. (shrink)