Philosophy of Earth Sciences

When we look at 800,000 year ice core data CO2 levels since 1950 have risen at a rate of 123-fold faster than the fastest rate in 800,000 years. When we see that this rise is precisely correlated with global carbon emissions the human link to climate change seems certain and any rebuttal becomes ridiculously implausible. The 800,000 year correlation between CO2 and global temperatures seems to be predicting at least 9 degrees C of more warming based on current CO2 levels.

Summary Analogue models are actual physical setups used to model something else. They are especially useful when what we wish to investigate is difficult to observe or experiment upon due to size or distance in space or time: for example, if the thing we wish to investigate is too large, too far away, takes place on a time scale that is too long, does not yet exist or has ceased to exist. The range and variety of analogue models is too (...) extensive to attempt a survey. In this article, I describe and discuss several different analogue model experiments, the results of those model experiments, and the basis for constructing them and interpreting their results. Examples of analogue models for surface waves in lakes, for earthquakes and volcanoes in geophysics, and for black holes in general relativity, are described, with a focus on examining the bases for claims that these analogues are appropriate analogues of what they are used to investigate. A table showing three different kinds of bases for reasoning using analogue models is provided. Finally, it is shown how the examples in this article counter three common misconceptions about the use of analogue models in physics. (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 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)

Recent work by Frigg et. al. and Mayo-Wilson have called attention to a particular sort of error associated with attempts to model certain complex systems: structural modeling error. The assessment of the degree of SME in a model presupposes agreement between modelers about the best way to individuate natural systems, an agreement which can be more problematic than it appears. This problem, which we dub “the system individuation problem” arises in many of the same contexts as SME, and the two (...) often compound one another. This paper explores the common roots of the two problems in concerns about the precision of predictions generated by scientific models, and discusses how both concerns bear on the study of complex natural systems, particularly the global climate. (shrink)

Earthquakes are among the world’s deadliest natural phenomena. On an increasingly crowded Earth, earthquake risk management therefore should be taken seriously as a global policy problem. Thus, this chapter discusses some of the ethical dimensions of earthquakes as a phenomenon of planetary significance in the Anthropocene. I do not attempt an exhaustive survey, but consider one background ethical issue: the kinds of harms that occur when an earthquake impacts human habitation. We may distinguish three categories of human-related harms: personal harms, (...) which accrue to individual humans; social harms, which impact on social relationships between humans; and institutional harms, which compromise the ability of institutions to respond to the quake. This analysis will help us better appreciate the moral salience of earthquakes as a global policy imperative in the Anthropocene. (shrink)

While the predominant focus of the philosophical literature on scientific modeling has been on single-scale models, most systems in nature exhibit complex multiscale behavior, requiring new modeling methods. This challenge of modeling phenomena across a vast range of spatial and temporal scales has been called the tyranny of scales problem. Drawing on research in the geosciences, I synthesize and analyze a number of strategies for taming this tyranny in the context of conceptual, physical, and mathematical modeling. This includes several strategies (...) that can be deployed in physical modeling, even when strict dynamical scaling fails. In all cases, I argue that having an adequate conceptual model—given both the nature of the system and the particular purpose of the model—is essential. I draw a distinction between depiction and representation, and use this research in the geosciences to advance a number of debates in the philosophy of modeling. (shrink)

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...

When do probability distribution functions (PDFs) about future climate misrepresent uncertainty? How can we recognise when such misrepresentation occurs and thus avoid it in reasoning about or communicating our uncertainty? And when we should not use a PDF, what should we do instead? In this paper we address these three questions. We start by providing a classification of types of uncertainty and using this classification to illustrate when PDFs misrepresent our uncertainty in a way that may adversely affect decisions. We (...) then discuss when it is reasonable and appropriate to use a PDF to reason about or communicate uncertainty about climate. We consider two perspectives on this issue. On one, which we argue is preferable, available theory and evidence in climate science basically excludes using PDFs to represent our uncertainty. On the other, PDFs can legitimately be provided when resting on appropriate expert judgement and recognition of associated risks. Once we have specified the border between appropriate and inappropriate uses of PDFs, we explore alternatives to their use. We briefly describe two formal alternatives, namely imprecise probabilities and possibilistic distribution functions, as well as informal possibilistic alternatives. We suggest that the possibilistic alternatives are preferable. -/- . (shrink)

The development of nineteenth-century geodetic measurement challenges the dominant coherentist account of measurement success. Coherentists argue that measurements of a quantity are epistemically successful if their numerical outcomes converge across varying contextual constraints. Aiming at numerical convergence, in turn, offers an operational aim for scientists to solve problems of coordination. Geodesists faced such a problem of coordination between two indicators of the earth’s ellipticity, which were both based on imperfect ellipsoid models. While not achieving numerical convergence, their measurements produced novel (...) data that grounded valuable theoretical hypotheses. Consequently, they ought to be regarded as epistemically successful. This insight warrants a dynamic revision of coherentism, allowing to judge the success of a metric based on both its coherence and fruitfulness. On that view, scientific measurement aims to coordinate theoretical definitions and produce novel data and theoretical insights. (shrink)

Most philosophical discussions of disagreement have used idealized disagreements to draw conclusions about the nature of disagreement. I closely examine an actual, non-idealized disagreement in dinosaur paleobiology and show that it can not only teach us about the features of some of our real world disagreements, but can help us to argue for the possibility of reasonable real world disagreement.

Outside the philosophy classroom, global skeptics – skeptics about all (purported) knowledge of the external world – are rare. But there are people who describe themselves as “skeptics” about various more specific domains, including self-professed “skeptics” about the reality of anthropogenic climate change. There is little to no philosophical literature that juxtaposes the climate change skeptic with the external world skeptic. While many “traditional” epistemologists assume that the external world skeptic poses a serious philosophical challenge in a way that the (...) climate change skeptic doesn’t, many “applied” or “social” epistemologists assume that there isn’t much to be learned from debates about the external world skeptic, finding her challenge to be distant from both common sense and real-world concerns. I try to show that both of these views are mistaken. The external world skeptic raises deep questions that are important for our everyday deliberation about what to believe, and there are significant structural parallels between the arguments for external world skepticism and those for at least a form of climate change skepticism that is idealized – but not too idealized! – from the views of flesh-and-blood climate change skeptics. As such, we have strong reasons to think in parallel about how to reply to both skeptics’ challenges. I thus finish by (briefly) considering how different widespread responses to the external world skeptic might or might not generalize happily to the climate change skeptic’s challenge. (shrink)

At the intersection of taxonomy and nomenclature lies the scientific practice of typification. This practice occurs in biology with the use of holotypes (type specimens), in geology with the use of stratotypes, and in metrology with the use of measurement prototypes. In this paper I develop the first general definition of a scientific type and outline a new philosophical theory of types inspired by Pierre Duhem. I use this general framework to resolve the necessity-contingency debate about type specimens in philosophy (...) of biology, to advance the debate over the myth of the absolute accuracy of standards in metrology, and to address the definition-correlation debate in geology. I conclude that just as there has been a productive synergy between philosophical accounts of natural kinds and scientific taxonomic practices, so too there is much to be gained from developing a deeper understanding of the practices and philosophy of scientific types. (shrink)

In 2012, the Geological Time Scale, which sets the temporal framework for studying the timing and tempo of all major geological, biological, and climatic events in Earth’s history, had one-quarter of its boundaries moved in a widespread revision of radiometric dates. The philosophy of metrology helps us understand this episode, and it, in turn, elucidates the notions of calibration, coherence, and consilience. I argue that coherence testing is a distinct activity preceding calibration and consilience, and I highlight the value of (...) discordant evidence and trade-offs scientists face in calibration. The iterative nature of calibration, moreover, raises the problem of legacy data. (shrink)

We explore three questions about Earth system modeling that are of both scientific and philosophical interest: What kind of understanding can be gained via complex Earth system models? How can the limits of understanding be bypassed or managed? How should the task of evaluating Earth system models be conceptualized?

In this review of Milan Ćirković’s The Great Silence: Science and Philosophy of Fermi’s Paradox, we attempt to reconstruct the logic of Fermi’s paradox as understood by the author, and we critically examine the reasoning that leads to the paradox. We show that there is no plausible solution to Fermi’s paradox that can satisfy all of Ćirković’s proposed desiderata, which in turn suggests that the author’s standards for hypothesis adjudication need to be revised.

Projections of future climate change cannot rely on a single model. It has become common to rely on multiple simulations generated by Multi-Model Ensembles (MMEs), especially to quantify the uncertainty about what would constitute an adequate model structure. But, as Parker points out (2018), one of the remaining philosophically interesting questions is: “How can ensemble studies be designed so that they probe uncertainty in desired ways?” This paper offers two interpretations of what General Circulation Models (GCMs) are and how MMEs (...) made of GCMs should be designed. In the first interpretation, models are combinations of modules and parameterisations; an MME is obtained by “plugging and playing” with interchangeable modules and parameterisations. In the second interpretation, models are aggregations of expert judgements that result from a history of epistemic decisions made by scientists about the choice of representations; an MME is a sampling of expert judgements from modelling teams. We argue that, while the two interpretations involve distinct domains from philosophy of science and social epistemology, they both could be used in a complementary manner in order to explore ways of designing better MMEs. (shrink)

In climate science, climate models are one of the main tools for understanding phenomena. Here, we develop a framework to assess the fitness of a climate model for providing understanding. The framework is based on three dimensions: representational accuracy, representational depth, and graspability. We show that this framework does justice to the intuition that classical process-based climate models give understanding of phenomena. While simple climate models are characterized by a larger graspability, state-of-the-art models have a higher representational accuracy and representational (...) depth. We then compare the fitness-for-providing understanding of process-based to data-driven models that are built with machine learning. We show that at first glance, data-driven models seem either unnecessary or inadequate for understanding. However, a case study from atmospheric research demonstrates that this is a false dilemma. Data-driven models can be useful tools for understanding , specifically for phenomena for which scientists can argue from the coherence of the models with background knowledge to their representational accuracy and for which the model complexity can be reduced such that they are graspable to a satisfactory extent. When citing this paper, please use the full journal title Studies in History and Philosophy of Science. (shrink)

In climate science, observational gridded climate datasets that are based on in situ measurements serve as evidence for scientific claims and they are used to both calibrate and evaluate models. However, datasets only represent selected aspects of the real world, so when they are used for a specific purpose they can be a source of uncertainty. Here, we present a framework for understanding this uncertainty of observational datasets which distinguishes three general sources of uncertainty: (1) uncertainty that arises during the (...) generation of the dataset; (2) uncertainty due to biased samples; and (3) uncertainty that arises due to the choice of abstract properties, such as resolution and metric. Based on this framework, we identify four different types of dataset ensembles — parametric, structural, resampling, and property ensembles—as tools to understand and assess uncertainties arising from the use of datasets for a specific purpose. We advocate for a more systematic generation of dataset ensembles by using these sorts of tools. Finally, we discuss the use of dataset ensembles in climate model evaluation. We argue that a more systematic understanding and assessment of dataset uncertainty is needed to allow for a more reliable uncertainty assessment in the context of model evaluation. The more systematic use of such a framework would be beneficial for both scientific reasoning and scientific policy advice based on climate datasets. (shrink)

A review of Thomas Moynihan's Spinal Catastrophism: A Secret History (2019).

Model evaluation for long term climate predictions must be done on quantities other than the actual prediction, and a comprehensive uncertainty quantification is impossible. An ad hoc alternative is provided by coordinated model intercomparisons which typically use a “one model one vote” approach. The problem with such an approach is that it treats all models as independent and equally plausible. Reweighting all models of the ensemble for performance and dependence seems like an obvious way to improve on model democracy, yet (...) there are open questions on what constitutes a “good” model, how to define dependency, how to interpret robustness, and how to incorporate background knowledge. Under¬standing those issues has the potential to increase confidence in model predictions in modeling efforts outside of climate science where similar challenges exist. (shrink)

This introductory chapter summarises key findings of the twenty-two book chapters in terms of five propositions. These propositions, each building on relevant findings linked to forward-looking suggestions for research, policy and practice, reflect the architecture of the book, whose sections proceed from setting the stage to critical issues, followed by a section on methods and tools, to chapters that provide geographic perspectives, and finally to a section that identifies potential policy options. The propositions comprise (1) Risk management can be an (...) effective entry point for aligning perspectives and debates, if framed comprehensively, coupled with climate justice considerations and linked to established risk management and adaptation practice; (2) Attribution science is advancing rapidly and fundamental to informing actions to minimise, avert, and address losses and damages; (3) Climate change research, in addition to identifying physical/hard limits to adaptation, needs to more systematically examine soft limits to adaptation, for which we find some evidence across several geographies globally; (4) Climate risk insurance mechanisms can serve the prevention and cure aspects emphasised in the L&D debate but solidarity and accountability aspects need further attention, for which we find tentative indication in applications around the world; (5) Policy deliberations may need to overcome the perception that L&D constitutes a win-lose negotiation “game” by developing a more inclusive narrative that highlights collective ambition for tackling risks, mutual benefits and the role of transformation. [Open access]. (shrink)

Mineral species are, at first glance, an excellent candidate for an ideal set of natural kinds somewhere beyond the periodic table. Mineralogists have a detailed set of rules and formal procedure for ratifying new species, and minerals are a less messy subject matter than biological species, psychological disorders, or even chemicals more broadly—all areas of taxonomy where the status of species as natural kinds has been disputed. After explaining how philosophers have tended to get mineralogy wrong in discussions of natural (...) kinds, I show how minerals species don’t behave like natural kinds. They are defined on the basis of human intentionality, not merely natural distinctions. They aren’t ideal grounds for inductive inference. And they don’t form a system that divides nature along a set of equivalent joints. While this is a regrettable outcome to those of us who like the idea of science relying on natural kinds, I contend that mineralogy is doing just fine without a natural kind-based taxonomy, and may in fact be better off without one. (shrink)

The idea that we are living in the Anthropocene, a new geological epoch defined by human activity, has gained substantial currency across the academy and with the broader public. Within the earth sciences, however, the question of the Anthropocene is hotly debated, recognized as a question that gets at both the foundations of geological science and issues of broad philosophical importance. For example, official recognition of the Anthropocene requires us to find a way to use the methods of historical science (...) to make predictions. It also involves determining the role that political motivations should play in establishing scientific kinds. I bring the perspective of philosophy of science to bear on these questions, ultimately arguing that formal recognition of the Anthropocene should be indefinitely deferred. 1A New Epoch 1.1Criteria for designating a new epoch2The Future Geologist’s Perspective 2.1Climate change2.2The fossil record, excluding humans2.3The human fossil record2.4Direct anthropogenic deposits2.5Chemical markers2.6Hydrology2.7Summing up3The Synchronic Perspective4The Anthropocene Is Not yet Set in Stone. (shrink)

In the spirit of explanatory pluralism, this chapter argues that causal and noncausal explanations of a phenomenon are compatible, each being useful for bringing out different sorts of insights. After reviewing a model-based account of scientific explanation, which can accommodate causal and noncausal explanations alike, an important core conception of noncausal explanation is identified. This noncausal form of model-based explanation is illustrated using the example of how Earth scientists in a subfield known as aeolian geomorphology are explaining the formation of (...) regularlyspaced sand ripples. The chapter concludes that even when it comes to everyday "medium-sized dry goods" such as sand ripples, where there is a complete causal story to be told, one can find examples of noncausal scientific explanations. (shrink)

Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not a measure of its epistemic reliability. (...) Instead it is the fidelity of the data that matters. Second, the fidelity of a data model in capturing the signal of interest is a matter of degree. Third, the fidelity of a data model can be improved ‘vicariously’, such as through the use of post hoc model-based correction techniques. And, fourth, data models, like theoretical models, should be assessed as adequate for particular purposes. (shrink)

Reports of the Intergovernmental Panel on Climate Change (IPCC) employ an evolving framework of calibrated language for assessing and communicating degrees of certainty in findings. A persistent challenge for this framework has been ambiguity in the relationship between multiple degree-of-certainty metrics. We aim to clarify the relationship between the likelihood and confidence metrics used in the Fifth Assessment Report (2013), with benefits for mathematical consistency among multiple findings and for usability in downstream modeling and decision analysis. We discuss how our (...) proposal meshes with current and proposed practice in IPCC uncertainty assessment. (shrink)

In this paper we take a close look at current interdisciplinary modeling practices in the environmental sciences, and suggest that closer attention needs to be paid to the nature of scientific practices when investigating and planning interdisciplinarity. While interdisciplinarity is often portrayed as a medium of novel and transformative methodological work, current modeling strategies in the environmental sciences are conservative, avoiding methodological conflict, while confining interdisciplinary interactions to a relatively small set of pre-existing modeling frameworks and strategies (a process we (...) call crystallization). We argue that such practices can be rationalized as responses in part to cognitive constraints which restrict interdisciplinary work. We identify four salient integrative modeling strategies in environmental sciences, and argue that this crystallization, while contradicting somewhat the novel goals many have for interdisciplinarity, makes sense when considered in the light of common disciplinary practices and cognitive constraints. These results provide cause to rethink in more concrete methodological terms what interdisciplinarity amounts to, and what kinds of interdisciplinarity are obtainable in the environmental sciences and elsewhere. (shrink)

The Intergovernmental Panel on Climate Change has developed a novel framework for assessing and communicating uncertainty in the findings published in their periodic assessment reports. But how should these uncertainty assessments inform decisions? We take a formal decision-making perspective to investigate how scientific input formulated in the IPCC’s novel framework might inform decisions in a principled way through a normative decision model.

Climate model projections are used to inform policy decisions and constitute a major focus of climate research. Confidence in climate projections relies on the adequacy of climate models for those projections. The question of how to argue for the adequacy of models for climate projections has not gotten sufficient attention in the climate modelling community. The most common way to evaluate a climate model is to assess in a quantitative way degrees of “model fit”; i.e., how well model results fit (...) observation-based data (empirical accuracy) and agree with other models or model versions (robustness). However, such assessments are largely silent about what those degrees of fit imply for a model’s adequacy for projecting future climate. We provide a conceptual framework for discussing the evaluation of the adequacy of models for climate projections. Drawing on literature from philosophy of science and climate science, we discuss the potential and limits of inferences from model fit. We suggest that support of a model by background knowledge is an additional consideration that can be appealed to in arguments for a model’s adequacy for long-term projections, and that this should explicitly be spelled out. Empirical accuracy, robustness and support by background knowledge neither individually nor collectively constitute sufficient conditions in a strict sense for a model’s adequacy for long-term projections. However, they provide reasons that can be strengthened by additional information and thus contribute to a complex non-deductive argument for the adequacy of a climate model or a family of models for long-term climate projections. (shrink)

Can we attribute individual extreme weather events to human-induced climate change? In this chapter I will be turning a philosophical eye on this question, asking what concept (or concepts) of causation are being employed by scientists and asking which concept of causation is most appropriate. I will show that scientists, politicians, and journalists have made a number of mistakes in their thinking about the causal links between individual extreme events and climate change, and argue that scientists should be less hesitant (...) when it comes to attributing such events to climate change. (shrink)

This essay furthers debate about the burgeoning science of Probabilistic Event Attribution (PEA) and its relevance to imminent climate policy decisions. It critically examines Allen Thompson and Friederike Otto’s recent arguments concerning the implications of PEA studies for how the United Nations Framework Convention on Climate Change (UNFCCC) policy framework should be revised during the 2016 ‘review and decision.’ I show that their contention that PEA studies cannot usefully inform decision-making about adaptation policies and strategies is misguided and argue that (...) the current UNFCCC treaty, the “Paris Agreement,” supersedes their proposed revision. (shrink)

Uncertainty is recognized as a key issue in water resources research, amongst other sciences. Discussions of uncertainty typically focus on tools and techniques applied within an analysis, e.g. uncertainty quantification and model validation. But uncertainty is also addressed outside the analysis, in writing scientific publications. The language that authors use conveys their perspective of the role of uncertainty when interpreting a claim —what we call here “framing” the uncertainty. This article promotes awareness of uncertainty framing in four ways. 1) It (...) proposes a typology of eighteen uncertainty frames, addressing five questions about uncertainty. 2) It describes the context in which uncertainty framing occurs. This is an interdisciplinary topic, involving philosophy of science, science studies, linguistics, rhetoric, and argumentation. 3) We analyze the use of uncertainty frames in a sample of 177 abstracts from the Water Resources Research journal in 2015. This helped develop and tentatively verify the typology, and provides a snapshot of current practice. 4) Provocative recommendations promote adjustments for a more influential, dynamic science. Current practice in uncertainty framing might be described as carefully-considered incremental science. In addition to uncertainty quantification and degree of belief (present in ~5% of abstracts), uncertainty is addressed by a combination of limiting scope, deferring to further work (~25%) and indicating evidence is sufficient (~40%) – or uncertainty is completely ignored (~8%). There is a need for public debate within our discipline to decide in what context different uncertainty frames are appropriate. Uncertainty framing cannot remain a hidden practice evaluated only by lone reviewers. (shrink)

In this paper I sketch William Whewell’s attempts to impose order on classificatory mineralogy, which was in Whewell’s day (1794e1866) a confused science of uncertain prospects. Whewell argued that progress was impeded by the crude reductionist assumption that all macroproperties of crystals could be straightforwardly explained by reference to the crystals’ chemical constituents. By comparison with biological classification, Whewell proposed methodological reforms that he claimed would lead to a natural classification of minerals, which in turn would support advances in causal (...) understanding of the properties of minerals. Whewell’s comparison to successful biological classification is particularly striking given that classificatory biologists did not share an understanding of the causal structure underlying the natural classification of life (the common descent with modification of all organisms). Whewell’s key proposed methodological reform is consideration of multiple, distinct principles of classification. The most powerful evidence in support of a natural classificatory claim is the consilience of claims arrived at through distinct lines of reasoning, rooted in distinct conceptual approaches to the target objects. Mineralogists must consider not only elemental composition and chemical affinities, but also symmetry and polarity. Geometrical properties are central to what makes an individual mineral the type of mineral that it is. In Whewell’s view, function and organization jointly define life, and so are the keys to understanding what makes an organism the type of organism that it is. I explain the relationship between Whewell’s teleological account of life and his natural theology. I conclude with brief comments about the importance of Whewell’s classificatory theory for the further development of his philosophy of science and in particular his account of consilience. (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)

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 highlights the “role of women in development of Pakistan”. Women participation is very vital for the prosperity of economy of Pakistan. Pakistan is a male dominated society despite the fact that its major population consists of women. In Pakistan the women face lots of obstacles when they want to utilize their skills for the growth and development of the country such as religious, political, social and environmental, although education, health and nutrition are the main issues on the top (...) of list of severe problems. The Pakistani women are neglected and targeted by the customs and values of their families and relationships. The drastic fact is that majority of women of Pakistan live in rural areas as compared to the urban areas where they are treated as animals. However, it is also a fact that currently lots of metropolitan women in all provinces perform marvelous activities for the progress of Pakistan. The study reveals women play dynamic role in boosting economy. We cannot ignore the astonishing performance of women in building developed countries. (shrink)

William Whewell’s work on historical science has received some attention from historians and philosophers of science. Whewell’s own work on the history of German Gothic church architecture has been touched on within the context of the history of architecture. To a large extent these discussions have been conducted separately. I argue that Whewell intended his work on Gothic architecture as an attempt to (help) found a science of historical architecture, as an exemplar of historical science. I proceed by analyzing the (...) key features of Whewell’s philosophy of historical science. I then show how his architectural history exemplifies this philosophy. Finally, I show how Whewell’s philosophy of historical science matches some developments in a science (biological systematics) that, in the mid-to latenineteenth century, came to be reinterpreted as a historical science. I comment briefly on Whewell as a potential influence on nineteenth century biology and in particular on Darwin. (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)

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)

Climate change adaptation is largely a local matter, and adaptation planning can benefit from local climate change projections. Such projections are typically generated by accepting climate model outputs in a relatively uncritical way. We argue, based on the IPCC’s treatment of model outputs from the CMIP5 ensemble, that this approach is unwarranted and that subjective expert judgment should play a central role in the provision of local climate change projections intended to support decision-making.

There are many parts of science in which a certain sort of underdetermination of theory by evidence is known to be common. It is argued that reflection on this fact should serve to shift the burden of proof from scientific anti-realists to scientific realists at a crucial point in the debate between them.