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Ontology for Representing Human Needs
Abstract
Need satisfaction plays a fundamental role in human well-being. Hence understanding citizens’ needs is crucial for developing a successful social and economic policy. This notwithstanding, the concept of need has not yet found its place in information systems and online tools. Furthermore, assessing needs itself remains a labor-intensive, mostly offline activity, where only a limited support by computational tools is available. In this paper, we make the first step towards employing need management in the design of information systems supporting participation and participatory innovation by proposing OpeNeeD, a family of ontologies for representing human needs data. As a proof of concept, OpeNeeD has been used to represent, enrich and query the results of a needs assessment study in a local citizen community in one of the Vienna districts. The proposed ontology will facilitate such studies and enable the representation of citizens’ needs as Linked Data, fostering its co-creation and incentivizing the use of Open Data and services based on it.
... 3 We recognize the importance and interdependence of human and non-human needs (such as needs of plants, animals and ecosystems), but given the specific focus on human needs by other authors, cited above, we are using it as the focal-point of this article. currently we do not even have broad agreement(s) across communities, disciplines or cultures on a single definition (or a set of co-existing definitions) of what needs are (and are not) [5,6], let alone what constitutes high-priority needs for individuals, organizations, or societies. Nor do we know how AI can assist in determining what responses are going to best satisfy needs, or even how needs satisfaction is best measured. ...
... Need(s) in this context is a specific term, just as are the terms "intelligence" and "artificial intelligence". The word need (especially when used as a noun) is deliberately selected by authors (including us) because it has the connotation of meaning a[n intrinsic] necessity for [the well-being or well-functioning of] a system (e.g., a human, a living agent, an organization, or a society) 6 . This perspective, we hope, can be helpful to distinguish needs from other terms such as "wants" [12], "cravings", "wishes", "motivators", or "desires" in most cases. ...
... Needs have played an essential role throughout the history of philosophy and science. From Aristotle to Marx, many philosophers have used both the concept of needs, and the powerful literary tool of the word need, as a part of their philosophical frameworks (see [6] for an overview). More recently, psychologists, cognitive scientists, social scientists, economists, and experts from many disciplines and sectors have also conceptualized and applied needs in practical ways (see [19] for a collection of references). ...
Throughout our history, we, Homo sapiens, have used technologies to better satisfy our needs . The relation between needs and technology is so fundamental that the US National Research Council defines the distinguishing characteristic of technology as its goal “to make modifications in the world [in order] to meet human needs” [1]. Artificial intelligence (AI) is one of the most promising emerging technologies of our time. Similar to other technologies, AI is expected by many “to meet [human] needs”. In this article, we reflect on the relationship between needs and AI, and call for the realization of needs-aware AI systems. We argue that re-thinking needs for , through , by , and with AI can be a very useful means towards the development of realistic approaches for sustainable H uman-aware, A ccountable, L awful, and E thical (HALE) AI systems. We discuss some of the most critical gaps, barriers, enablers, and drivers of co-creating future AI-based sociotechnical systems in which [human] needs are well considered and met. Finally, we provide an overview of potential challenges and considerations that should be carefully taken into account; and call for joint, immediate, and interdisciplinary efforts and collaborations to start on the path to needs-aware AI.
... Yet, in this article, we weigh the ethical and pragmatic implications of this ambition-and consider what it would take to make needs-aware AI a reality. After all, currently we do not even have broad agreement(s) across communities, disciplines or cultures on a single definition (or a set of co-existing definitions) of what needs are (and are not) [4,5], let alone what constitutes high-priority needs for individuals, organizations, or societies. Nor do we know how AI can assist in determining what responses are going to best satisfy needs, or even how needs satisfaction is best measured. ...
... Needs have played an essential role throughout the history of philosophy and science. From Aristotle to Marx, many philosophers have used both the concept of needs, and the powerful literary tool of the word need, as a part of their philosophical frameworks (see [5] for an overview). More recently, psychologists, cognitive scientists, social scientists, economists, and experts from many disciplines and sectors have also conceptualized and applied needs in practical ways (see [12] for a collection of references). ...
... 1. Defining need and needs: a historical challenge What is a need, what are human needs, what are potential categories or classes needs, what are the relationships (or potential hierarchies) among needs, and how can needs be satisfied, have been a topic of inquiry since the time of ancient philosophers (see [5]). In the last century, other disciplines diversified the discourse, but no common answers, definition, or agreement within and across different disciplines exist. ...
Throughout their history, homo sapiens have used technologies to better satisfy their needs. The relation between needs and technology is so fundamental that the US National Research Council defined the distinguishing characteristic of technology as its goal "to make modifications in the world to meet human needs". Artificial intelligence (AI) is one of the most promising emerging technologies of our time. Similar to other technologies, AI is expected "to meet [human] needs". In this article, we reflect on the relationship between needs and AI, and call for the realisation of needs-aware AI systems. We argue that re-thinking needs for, through, and by AI can be a very useful means towards the development of realistic approaches for Sustainable, Human-centric, Accountable, Lawful, and Ethical (HALE) AI systems. We discuss some of the most critical gaps, barriers, enablers, and drivers of co-creating future AI-based socio-technical systems in which [human] needs are well considered and met. Finally, we provide an overview of potential threats and HALE considerations that should be carefully taken into account, and call for joint, immediate, and interdisciplinary efforts and collaborations.
... The study of human needs has roots in psychology, economics, philosophy, sociology, anthropology, and social sciences, which indicates the importance of needs, and their satisfaction in human life. Despite that fact, there is still a shortage of incorporating human needs in information systems and tools [14]. Augmented reality is a growing field that may benefit from the utilization of human needs. ...
... Based on the above reasoning, this paper looks into the development of an ontology that combines the concepts of augmented reality, human needs' satisfaction, and the detection of those needs from context and user information to support conceptual modeling. Previous studies on ontologies included a representation of needs as they are found in various theories of human needs [14], an ontology focusing only on Max-Neef's model of human needs [22], context modeling [23], and developing augmented reality based on ontological context awareness [16]. ...
... The researchers in [14] pinpointed the limited use of human needs concepts in information systems and the lack of needs assessment tools in computing. They developed an ontology called OPENEED and incorporated need theories and need assessment methods. ...
Augmented Reality is a display and interaction method of future computing. It augments digital information in real environments in text, audio, image, or video formats. Augmented reality can be more effective if supported by knowledge about human needs. Basic human needs are finite in number, and with the right methods, they are detectable or predictable. This research develops an ontology that describes the structure and relations between the elements of augmented reality, context information, and human needs, with the ultimate goal of developing a robust conceptual model. Ontology development is a knowledge-driven approach used to represent data and reasoning. This paper focuses on linking the aforementioned concepts to enable correct data representation and reasoning. The research approach, process used, and the evaluation of the ontology is presented as well.
... The conceptualization of preliminary data gathered in the pre-experiment survey in order to group the involved participants according to their music genre preferences and demographics. Generating playlists, in an intelligent and novel manner, by using our microservice-oriented Web system adopting the functional (FaaS-Functions As A Service) serverless paradigm [4,5]; this prototype, deployed on a popular cloud computing platform, was developed to manage knowledge about user preferences of music genres. This approach could bring also benefits for user interface adaptation by using semantic Web techniques. ...
... Human needs-a family of ontologies for representing human needs is proposed in order to represent, enrich and query the results of a needs assessment study in a local citizen community [5]. ...
... (4) Performing the experiment, by giving two tests conducted when the participants had their favorite music in the background, and the other set of tests was administered with undesirable background music. (5) Analyzing and discussing the results. ...
A knowledge-driven approach is proposed for assessing the music influence on university students. The proposed method of modeling and conducting the interactive pilot study can be useful to convey other surveys, interviews, and experiments created in various phases of the user interface (UI) design processes, as part of a general human-computer interaction (HCI) methodology. Benefiting from existing semantic Web and linked data standards, best practices, and tools, a microservice-oriented system is developed as a testbed platform able to generate playlists in a smart way according to users’ music preferences. This novel approach could bring also benefits for user interface adaptation by using semantic Web techniques. Statistical analysis based on the ANOVA method and post-experiment survey data led to the conclusion that music listened has a significant impact on students’ cognitive abilities in various contexts. All obtained results were semantically enhanced by using different conceptual models in order to create a knowledge graph providing support for automated reasoning. Also, a knowledge-based persona Web smart editor was implemented in order to include music preferences for certain categories of the potential users operating a specific interactive system.
... This research aims to enrich augmented reality paradigms by developing a novel AR experience trigger: a needs trigger. Despite the importance of needs and their satisfaction in human life, there is still a shortage of incorporating human needs in information systems and tools [13]. Augmented reality is a growing field that may benefit from the use of human needs. ...
... Needs representation: Some scholars attempted to represent human needs using ontologies [13,32], others used directed graphs [33]. ...
Augmented Reality aims to enhance the real world with computer-generated information. AR technology is both attractive and promising. Current AR experiences depend on external elements to launch, such as markers, images, and location. For an AR experience to be more personalized, this research proposes a scheme to trigger AR experiences based on human needs. This approach should enable human needs to be captured, and analyze them to select the most suited experiences that fulfill or aids in fulfilling needs. The contribution of this paper includes (1) a study of current AR technologies and triggers, (2) an analysis of human needs into measurable elements, and (3) a description of a needs-based AR application process with a demonstration of the process guidelines. The research presents a proof of concept prototype of a restaurant that satisfies the subsistence need for hunger. The results show the effectiveness of the guidelines in detecting human needs and recommending AR experiences; however, producing correct predictions and recommendations requires a well-established dataset.
... • End-user empowering socio-technical information systems [19] that function based on human needs and values [20], [21] and consider human-centric [6], [22] aspects of personal data protection and consenting should be developed. • The widely ignored (or even misused) aspects of personal data protection and consenting-i.e. ...
Consent plays an essential role in different digital regulations, such as the European General Data Protection Regulation (GDPR). As a result, obtaining consent from data subjects (e.g. end-users or end-customers) are widely practised by many data controllers (e.g. service providers, companies, or organizations). Considering the importance and the widespread practice of consent-obtaining in different domains, critical and interdisciplinary studies of the current consent-obtaining mechanisms are highly needed. In this paper, we first shortly discuss an interdisciplinary human-centric perspective to consenting and propose that, among others, the contextuality of consent, as well as the potential intersectionality of consent, should be carefully considered in the development of consent-obtaining mechanisms. Then we elaborate on the distinction between “consent to personal data processing for commercial purposes” and “consent to personal data donations intended for research” in the field of direct-to-consumer genetic testing (DTC-GT). We show that based on our human-centric perspective, the contextuality and intersectionality of consent are sometimes overlooked in the current DTC-GT services, which are of considerable significance in the emerging genetic data markets. We hope that this paper can contribute towards the development of human-centric, accountable, lawful, and ethical (HALE) sociotechnical information systems dealing with consent and privacy management as fundamental building blocks of a sustainable digital economy.
... Business ontologies partially describe consumer/customer and related concepts, for instance, The Enterprise Ontology of Edinburgh [14] contain the "Marketing" section; business model ontology describes "Client Segment", "Marketing Channels", "Client Relations" [15]; ontology of [16] discuses consumer needs and desires; ontology of [17] discusses the consumer role in value co-creation. However, such business ontologies discuss consumer/ customer and their knowledge, but not in enough detail. ...
Knowledge economy and further development of the information society made knowledge of all market interaction participants a key factor of consumption, adding value, including joint generation of value and innovation. Alongside with general increase in information volumes and decrease in consumer trust to it, the very products and services, as well as consumption technology and culture have become more complex and, thus, demonstrate relevance of managing consumer knowledge. Such complexity requires to teach consumers and to exchange knowledge with them. Consumer knowledge is of paramount importance for innovative products and services, as it is a key factor of innovation-decision process. Consumer knowledge practice needs clear understanding of this concept ("consumer knowledge"), its kinds and features, processes of acquiring and changing this knowledge, its influence on consumer behaviour, as well as company’s capabilities to establish consumer knowledge. Such understanding will be provided by creating ontology of innovative products and services’ consumer knowledge. Such ontology will help to resolve a whole range of enterprise engineering tasks: design of innovative products and services, as well as ecosystem surrounding them; design of an interaction system between a company and a consumer during a whole customer journey. This paper describes main requirements on ontology, discusses some existing ontologies, as well as contains primary results of ontology conceptualisation.
... It has been proposed that information systems should be human-centric [25] and pluralist [26,27], i.e to continuously consider their users' diverse abilities, limits, needs [28] and values [26]. It is, however, imperative that systems be accountable, at a minimum, to their users. ...
Users’ perception of geographic space depends heavily on geographic information systems (GIS). GIS are the most common way for users to estimate travel time, provide routing information and recommend appropriate forms of transportation. This article analyses how predictions made by Google Maps, one of the most popular GIS, influence users’ perceptions and travel choices. To analyze this influence, a pre-study in a classroom setting (n=36) as well as an online survey (n=521) were conducted. We study users intuitive perception of travel time, before using the Google Maps Mobile App as a ’treatment’ to see how it influences their perceptions of travel time and choice of transportation type. We then contrast this original Google Maps treatment to a mock-up ’warning label version’ of Google which informs users about biases in Google Maps and an ’unbiased version’ of Google Maps based on ground truth data. Our analysis suggests that Google Maps systematically underestimates necessary car driving time, which has an impact on users’ choice of transportation.
... Aristotle (Reader, 2005) Necessity is closely related to needs. Figure 1 shows OpeNeed as an example of pluralist approaches in the development of ontologies for representing human needs (Human, Fahrenbach, Kragulj & Savenkov, 2017). OpeNeed has a light-weight and robust Core Ontology (Figure 1-a) which only includes a limited set of optional classes and properties that are common among need theories. ...
In our increasingly digital societies, many companies have business models that perceive users' (or customers') personal data as a siloed resource, owned and controlled by the data controller rather than the data subjects. Collecting and processing such a massive amount of personal data could have many negative technical, social and economic consequences, including invading people's privacy and autonomy. As a result, regulations such as the European General Data Protection Regulation (GDPR) have tried to take steps towards a better implementation of the right to digital privacy. This paper proposes that such legal acts should be accompanied by the development of complementary technical solutions such as Cognitive Personal Assistant Systems to support people to effectively manage their personal data processing on the Internet. Considering the importance and sensitivity of personal data processing, such assistant systems should not only consider their owner's needs and values, but also be transparent, accountable and controllable. Pluralist approaches in computational cognitive modelling of human needs and values which are not bound to traditional paradigmatic borders such as cognitivism, connectionism, or enactivism, we argue, can create a balance between practicality and usefulness, on the one hand, and transparency, accountability, and controllability, on the other, while supporting and empowering humans in the digital world. Considering the threat to digital privacy as significant to contemporary democracies, the future implementation of such pluralist models could contribute to power-balance, fairness and inclusion in our societies.
... To this end, Polyphony supports disagreement annotations of varying granularity: from the ontology level to the level of single triple, or a collection of triples. As a proof of concept, Polyphony was applied to OpeNeeD, a modular ontology for human needs data proposed by Human et al. (2017), to represent disagreements between different modules of the OpeNeeD ontology, i.e. to annotate epistemic disagreements between needs theories. ...
A crucial concept in philosophy and social sciences, epistemic disagreement, has not yet been adequately reflected in the Web. In this paper, we call for development of intelligent tools dealing with epistemic disagreements on the Web to support pluralism. As a first step, we present Polyphony, an ontology for representing and annotating epistemic disagreements.
... More complex regularities, at increasingly slower time scales, are dealt with at higher levels. This can potentially provide a formal solution for dealing with different levels of needs, desires, satisfiers, etc (see Human et al. 2017, for a discussion on these notions). (II) Contextual probabilities: Predictions at any level of the hierarchy are subject to contextual modulation. ...
In this paper, based on the predictive processing approach to cognition, an enactive theory of need satisfaction is discussed. The theory can be seen as a first step towards a computational cognitive model of need satisfaction.
By defining the current limits (and thereby the frontiers), many boundaries are shaping, and will continue to shape, the future of Artificial Intelligence (AI). We push on these boundaries to make further progress into what were yesterday’s frontiers. They are both pliable and resilient—always creating new boundaries of what AI can (or should) achieve. Among these are technical boundaries (such as processing capacity), psychological boundaries (such as human trust in AI systems), ethical boundaries (such as with AI weapons), and conceptual boundaries (such as the AI people can imagine). It is within these boundaries that we find the construct of needs and the limitations that our current concept of need places on the future AI.
Augmented Reality (AR) is one of the most modern and attractive information visualization technologies. Despite the proliferation of AR with the spread of mobile devices, the technology is still limited in providing relevant and personalized experiences. This limitation inspired the idea to incorporate human needs in an augmented reality system to enable personalized and focused suggestions which is a step closer to achieving pervasiveness. The main question is: How to detect human needs from sensed data and provide augmented reality experiences to satisfy the needs? The research gives an overview of the analysis of data elements and sensor requirements for the fundamental human needs defined by Manfred Max-Neef; a proof-of-concept prototype that enables need detection; prediction of the subsistence, protection, and leisure needs from analyzed data; and recommendations on augmented reality experiences based on human needs. An experiment is conducted, data analysis and predictive modelling techniques are applied to the Context-Aware Personalization for Augmented Reality (CAP-AR) dataset to achieve the research objectives. A reflection on the data requirements to predict human needs and implications on planning and design of pervasive applications to detect and satisfy human needs constitutes the research results.KeywordsDataAnalyticsHuman needsNeeds detectionAugmented reality
An inspiring and compelling vision can help cities and regions to develop knowledge-based capabilities; it can guide future policy making, and it can set a city apart from other cities. In this article, we will apply the theoretical framework of the ‘Theory Wave’ to suggest how cities can develop a vision that is (1) participative as it involves persons from all relevant stakeholder groups, and (2) future-oriented as it considers how people imagine their ideal city to be in the year 2030. To illustrate how such a knowledge-based vision development looks like in practice, we present a case study where we worked with around 300 citizens of a small city in Germany to develop a new vision for the city. Given that there is a recent interest in how knowledge management can support regional development processes, we will reflect on the types of knowledge that are involved in such a process.
Needs drive organizational learning and guide organizational change. Current research proposes efficient methods to identify (shared) needs in organizations. However, there is a lack of organizational learning methodologies that utilize knowledge about (shared) needs and promote the development of need‐based solutions. In organizational practice, we face complex social dynamics, which strongly influence such learning processes. Design thinking is one approach to cope with these dynamics and provides a frame for participatory methodologies to develop need‐based solution. In this article, we clarify the concept of shared need. Moreover, we review seminal literature on design thinking to crystallize its basic principles. We consider how these principles could enhance the necessary capacities to turn needs into viable satisfiers. We report from a first attempt to implement these principles in practice and reflect on the results of this organizational learning intervention.
Too many new products fail. New products which are hard to differentiate from existing products won’t capture the customer’s imagination. The failure is due to a poor understanding of customers’ needs. Companies need to take a radical approach to identifying customers’ real needs, and this book demonstrates innovative ways to achieve this.
We introduce a new methodological framework, called Bewextra, for the creation of the knowledge of needs in organizations. The development of our framework builds on theoretical engagement with literature from several disciplines including visioning and philosophy of needs as well as empirical data from vision development processes we have accompanied. To the best of our knowledge it is the first theoretical work that describes learning from an envisioned future and the generation of need knowledge as an abductive process in a methodologically replicable way. The advantages and practical implications of our method introduced are discussed in detail.
In this chapter we outline a novel theory of the consumer market, in which information plays the key role. Consumers know only part of the available business offers and cannot ascertain the quality of the products they desire and businesses have even less knowledge of what consumers desire. In the market consumers and businesses must find a match with severely deficient information. Instead of optimisation under the constraints, our theory focuses on how the information constraints can be gradually reduced. We show that upon constraint-reduction we do not come closer to the full information limit typically portrayed in mainstream economics; rather both consumer wants and business offers expand with concomitant new information deficiencies. Therefore the consumer market is always in non-equilibrium and information will always be deficient. We argue that in the dynamic pursuit to reduce information constraints wealth is created and this is the main driving force that powers economic growth.
The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.
What are the relationships between human needs and human wellbeing? I will address the question by considering the conceptual linkages between these two umbrella categories. This requires investigation of the nature of each of them as a family of concepts. That is attempted in sections 2.3 and 2.4 of this chapter. I briefly point to the further topic of their empirical connections in section 2.5. Bracketing these discussions, the opening and closing parts of the chapter consider and compare human needs and human wellbeing as research programmes. How far is the wellbeing programme a continuation or successor to the tradition of thinking and investigation on human needs, and what lessons may arise from the somewhat troubled history of research on needs? The rise of wellbeing as an important, if not yet major, research focus in development studies and policy and more widely is extremely welcome and long overdue. As recently as 1994, Routledge's The Social Science Encyclopaedia (Kuper and Kuper 1994) could appear without an entry on wellbeing or quality of life or happiness. Even in two excellent late 1980s textbooks on the emergent field of economic psychology (Furnham and Lewis 1986; Lea, Tarpy and Webley 1987) wellbeing remained a minor theme. Lea et al. in over 500 pages did not discuss it as a separate topic; Furnham and Lewis devoted just four pages to the relationship between wealth and happiness.
By definition your needs assessment should assess needs, but how do you define them? Further, how do you operationalize that definition to measure needs? Do your partners and stakeholders also hold the same conceptual, and operational, definitions? Is there agreement that the project is only going to assess needs and not wants, assets, capacity, or solutions? Or are you really expected to assess all five? Each of these is an important consideration that can substantially influence the success of any needs assessment. In this chapter, the authors examine how definitions and use of the word need influence the design and implementation of an assessment, suggesting that the definition can shape the results of what is found.
Stakeholder theory begins with the assumption that values are necessarily and explicitly a part of doing business. It asks managers to articulate the shared sense of the value they create, and what brings its core stakeholders together. It also pushes managers to be clear about how they want to do business, specifically what kinds of relationships they want and need to create with their stakeholders to deliver on their purpose. This paper offers a response to Sundaram and Inkpen's article "The Corporate Objective Revisited" by clarifying misconceptions about stakeholder theory and concluding that truth and freedom are best served by seeing business and ethics as connected.
A focus on needs and the ability to generate knowledge about needs is highly valuable for organizations because it extends the range of possible solutions and therefore enables them to create more innovative and sustainable products and services. Our paper will explore how a framework based on an abductive reasoning process for the creation and discovery of knowledge about needs in organizations can look like and what the main steps of such a framework are, in order to integrate this approach into the model of the knowledge-based firm. Moreover we will present empirical findings from a project with Austrian companies where this framework has been used.
Structurally, the Web resembles a marketplace: Web clients download documents from servers just like customers buy goods from kiosks. Interestingly, the marketplace metaphor for the Web goes further: most Web users are in the role of the customer and the documents downloaded in most cases actually represent commercial offers. This second resemblance leads to a fundamental asymmetry: in general, commercial offers are represented as first-class objects on the Web. Consumer needs, however, the very notions that drive the interaction, only materialize in the form of search terms or browsing ehaviour. In this paper, we present an approach for explicitly representing needs as first-class objects on the Web of data in a way that allows interacting with them.
The Web as related to commerce suffers from a fundamental asymmetry. While there is a great number of commercial offers available, consumer needs are rarely represented explicitly. Thus, the most widely applied process of connecting the prospective consumer of a resource with its supplier is Web search. In Web search, the user needs are implicit, driving the interaction, and therefore only the interaction partners can try to deduce them. We present an approach for a) publishing needs on the Web of Data and b) building a protocol that allows decentralized matching of needs and communication between need owners. Albeit inspired by the analysis of marketplaces, the proposed framework allows for a much broader range of social applications, such as collaborative problem solving, help organizing the sharing economy or finding interesting people to meet.
Some of the duties of individuals and organisations involve responsiveness to need. This requires knowledge of need, so the epistemology of need is relevant to practice. The prevailing contention among philosophers who have broached the topic is that one can know one’s own needs (as one can know some kinds of desires) by feeling them. The article argues against this view. The main positive claims made in the article are as follows. Knowledge of need, in both first‐person and second‐person cases, is a type of knowledge‐that with no basic epistemological source. Needs, like medical conditions, have signs and symptoms. Knowledge of these, with inference, results in knowledge of need. Finally, it is argued that need is akin to, but not a special case of, metaphysical necessity de re. Some implications of this for the epistemology of need are explained.
The concept of need is promising and alluring because of three factors:
In this paper we present three cases of instructional design that illustrates both horizontal didactising, the activity of
using already established principles to design instruction, and vertical didactising the activity of developing new tools
and principles for instructional design. The first case illustrates horizontal didactising by elaborating how the constructs
chains of signification and models were used to design an instructional sequence involving linear growth. The second and third
cases illustrate vertical didactising by developing argumentation analyses and generative listening, respectively, as instructional
design tools. In the second case, argumentation analyses emerge as a tool that other designers can use to anticipate the quality
of conversations that can occur as students engage in tasks prior to implementing the instructional sequence. The third case
develops the notion of generative listening as a conceptual tool within the context of designing differential equations instruction
to gain insights into what are, for students, experientially-real starting points that are mathematical in nature and to provide
inspirations for revisions to instructional sequences.
Across a sample of 123 countries, we examined the association between the fulfillment of needs and subjective well-being (SWB), including life evaluation, positive feelings, and negative feelings. Need fulfillment was consistently associated with SWB across world regions. Life evaluation was most associated with fulfilling basic needs; positive feelings were most associated with social and respect needs; and negative feelings were most associated with basic, respect, and autonomy needs. Societal need fulfillment predicted SWB, particularly for life evaluation, beyond individuals' fulfillment of their own needs, indicating the desirability of living in a flourishing society. In addition, the associations of SWB with the fulfillment of specific needs were largely independent of whether other needs were fulfilled. These trends persisted when household income was taken into account. The emergent ordering of need fulfillment for psychosocial needs were fairly consistent across country conditions, but the fulfillment of basic and safety needs were contingent on country membership.
Human behavior is impacted by emotion, mood, personality, needs and subjective well-being. Emotion and mood are human affective states while personality, needs and subjective well-being are influences on those affective states. Ontologies are a method of representing real-world knowledge, such as human affective states and their influences, in a format that a computer can process. They allow researchers to build systems that harness affective states. By unifying terms and meanings, ontologies enable these systems to communicate and share knowledge with each other. In this paper, we survey existing ontologies on affective states and their influences. We also provide the psychological background of affective states, their influences and representational models. The paper discusses a total of 20 ontologies on emotion, one ontology on mood, one ontology on needs, and 11 general purpose ontologies and lexicons. Based on the analysis of existing ontologies, we summarize and discuss the current state of the art in the field.
Intrinsic motivation is the innate, natural propensity to engage one’s interests and exercise one’s capacities, and in so doing, to seek and conquer optimal challenges. Such motivation emerges spontaneously from internal tendencies and can motivate behavior even without the aid of extrinsic rewards or environmental controls. Intrinsic motivation is also an important motivator of the learning, adaptation, and growth in competencies that characterize human development. One would think from this description that intrinsic motivation is a ubiquitous phenomenon, and yet the examination of many settings suggests just the opposite. In factories and classrooms, offices and kitchens, one finds evidence of boredom, alienation, and inactivity. There appears to be a strong indication that people are prone to disinterest and stagnation.
In Chapter 8 we introduced the notion of ‘universal satisfier characteristics’: those ‘inputs’ which, according to the best available knowledge, contribute positively to the ‘output’ of individual health and autonomy in all cultures. We identified eleven such characteristics, which we called ‘intermediate needs’. In this chapter, we shall elaborate on each of these, trying to do two things. First, its inclusion will be justified by referring to the scientific evidence linking particular universal satisfier characteristics to either physical health or autonomy as they have been operationalised in the preceeding chapter. Often there is no sharp dividing line between the two: a ‘physical health satisfier’ like nutrition will also affect cognitive and emotional development if seriously deficient, while an ‘autonomy satisfier’ like childhood security will also affect physical health if seriously deficient. Second, we shall specify cross-cultural indicators for each intermediate need or, where these are unsatisfactory or unavailable, propose alternatives.
This book sets forth a provocative agenda for the scientific study of human personality. Blending no-nonsense empiricism with the humanistic desire to understand the whole person, the book is as relevant today as it was to its many readers seventy years ago. The book sets forth a full theory of human personality, illustrated with a bevy of creative methods for personality assessment, and presenting the results of a landmark study of fifty Harvard men. The book is one of the great classics in 20th-century psychology.
The question of how to teach mathematics has become increasingly problematic in recent years as critics from diverse perspectives have offered wide-ranging, and often seemingly incommensurate, challenges to conventional conceptions of the teacher's task. This article represents an effort to "bring into dialogue" some of the varied commentaries on mathematics teaching, using an enactivist framework to interpret and to propose an alternative way of framing mathematics teaching. In this report, the manner in which the teacher listens is offered as a metaphoric lens through which to reinterpret practice, as a practical basis for teaching action, and as a means of addressing some of the critics' concerns. The report is developed around an extended collaborative research project with a middle school mathematics teacher.
This chapter consists of an overview of needs assessment's rich history, definitions, models, tools, and techniques. These closely align its theory, research, and practice to several associated fields—most notably strategic planning and evaluation. The highlights of the content include a comparison to—and differentiation from—evaluation, a brief timeline of the recent history of the field, the notable emergence of hybrid assessment and asset/capacity building approaches, some discussion of opposition to needs assessment, and a description of two prominent models that guide what assessors do. The summary captures the dynamic nature of the enterprise and how it is evolving.
British literature related to the care of children in hospital states that they have ‘special needs’ This concept is not defined, neither are different writers in total agreement about what these needs may be This paper attempts to define needs, concluding that they are‘requirements that should be met’Children are seen as dynamic beings because they are in a state of constant development, both physically and psychosocially It is this state of development that makes their needs special to them They have special requirements, which should be met in specific ways Through the presentation of indicators of behaviours which would enable such needs to be met, it can be demonstrated that children should be cared for by people with the appropriate knowledge and understanding When children are admitted to hospital there may be a number of different people involved in determining how a need should be met An important part of this process should be nurses who have been specially educated for work with this age group
Aristotle’s account of human needs is valuable because it describes the connections between logical, metaphysical, physical, human and ethical necessities. But Aristotle does not fully draw out the implications of the account of necessity for needs and virtue. The proper Aristotelian conclusion is that, far from being an inferior activity fit only for slaves, meeting needs is the first part of Aristotelian virtue.
In marketing and branding, the mantra of the development process is “respond to customer needs.” But as Dev Patnaik makes clear, not all needs are created equal. Here, supported by examples and case studies, he describes a hierarchy of customer needs and suggests how corporations can use this design-based analysis—or system logics—to inform their strategic and tactical decision making.
This document contains a proposal for a Semantic Web Rule Language (SWRL) based on a combination of the OWL DL and OWL Lite sublanguages of the OWL Web Ontology Language with the Unary/Binary Datalog RuleML sublanguages of the Rule Markup Language. SWRL includes a high-level abstract syntax for Horn-like rules in both the OWL DL and OWL Lite sublanguages of OWL. A model-theoretic semantics is given to provide the formal meaning for OWL ontologies including rules written in this abstract syntax. An XML syntax based on RuleML and the OWL XML Presentation Syntax as well as an RDF concrete syntax based on the OWL RDF/XML exchange syntax are also given, along with several examples. Ce document propose un langage, SWRL (Semantic Web Rule Language ou langage de règles du Web sémantique), basé sur une combinaison des sous langages OWL DL et OWL Lite du langage ontologique Web OWL, avec les sous langages Datalog RuleML unaire/binaire du langage Rule Markup Language. SWRL intègre une syntaxe abstraite de haut niveau pour les règles de Horn dans les sous langages OWL DL et OWL Lite de OWL. Un modèle sémantique théorique permettant d'établir la signification formelle des ontologies OWL, y compris des règles rédigées dans cette syntaxe abstraite, est présenté. Une syntaxe XML basée sur RuleML et la syntaxe de présentation de OWL XML, ainsi qu'une syntaxe RDF concrète basée sur la syntaxe d'échange de OWL RDF/XML sont également proposées, avec plusieurs exemples.
Human need is a central but contested concept in social policy and the social sciences. This book provides an accessible overview of the subject using concepts from many disciplines. It presents a unique integrative model that shows how the main approaches may be reflected in social policy goals. The author engages with recent debates which advance our understanding of human need, including human wellbeing and 'happiness'; poverty, social exclusion and global inequality; human difference, the diversity of needs and the concept of human capabilities. Most crucially, the book explores how human needs may be translated into rights and how these can be informed by a politics of human need. The book offers essential insights for students of social policy, but will also be of interest to other social science disciplines, policy makers and political activists.
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A 36 cell matrix of needs; First dimension: 1. Subsistence,
2. Protection, 3. Affection, 4. Understanding,
5. Participation, 6. Leisure, 7. Creation, 8. Identity,
9. Freedom; Second dimension (existential categories):
1. Being (qualities), 2. Having (things), 3. Doing (actions),
4. Interacting (settings)