Onlinestudie: Wissenschaftliches Arbeiten im Web 2.0

Das Web 2.0 eröffnet Wissenschaftlerinnen und Wissenschaftlern neue Möglichkeiten mit Wissen und Informationen umzugehen: Das Recherchieren von Informationen und Quellen, der Austausch von Wissen mit anderen, das Verwalten von Ressourcen und das Erstellen von eigenen Inhalten im Web ist einfach und kostengünstig möglich. Dieser Artikel thematisiert die Bedeutung des Web 2.0 für den Umgang mit Wissen und Informationen und zeigt auf, wie durch die Kooperation vieler Einzelner das Schaffen von neuem Wissen und von Innovationen möglich wird. Diskutiert werden der Einfluss des Web 2.0 auf die Wissenschaft und mögliche Vor- und Nachteile der Nutzung. Außerdem wird ein kurzer Überblick über Studien gegeben, die die Nutzung des Web 2.0 in der Gesamtbevölkerung untersuchen. Im empirischen Teil des Artikels werden Methode und Ergebnisse der Befragungsstudie „Wissenschaftliches Arbeiten im Web 2.0“ vorgestellt. Befragt wurden Nachwuchswissenschaftlerinnen und Nachwuchswissenschaftler in Deutschland zur Nutzung des Web 2.0 für die eigene wissenschaftliche Arbeit. Dabei zeigt sich, dass insbesondere die Wikipedia von einem Großteil der Befragten intensiv bis sehr intensiv für den Einstieg in die Recherche verwendet wird. Die aktive Nutzung des Web 2.0, z.B. durch das Schreiben eines eigenen Blogs oder dem Mitarbeiten bei der Online-Enzyklopädie Wikipedia ist bis jetzt noch gering. Viele Dienste sind unbekannt oder werden eher skeptisch beurteilt, der lokale Desktopcomputer wurde noch nicht vom Web als zentraler Speicherort abgelöst.

Demo Abstract: Disseminating WMSN Data by Using Social Network and Web

For smart cities applications, a key requirement is to disseminate data collected from both scalar and multimedia wireless sensor networks to thousands of end-users. Furthermore, the information must be delivered to non-specialist users in a simple, intuitive and transparent manner. In this context, we present Sensor4Cities, a user-friendly tool that enables data dissemination to large audiences, by using using social networks, or/and web pages. The user can request and receive monitored information by using social networks, e.g., Twitter and Facebook, due to their popularity, user-friendly interfaces and easy dissemination. Additionally, the user can collect or share information from smart cities services, by using web pages, which also include a mobile version for smartphones. Finally, the tool could be configured to periodically monitor the environmental conditions, specific behaviors or abnormal events, and notify users in an asynchronous manner. Sensor4Cities improves the data delivery for individuals or groups of users of smart cities applications and encourages the development of new user-friendly services.

A Concept of Semantics Extraction from Web Data by Induction of Fuzzy Ontologies

Traditionally, ontologies describe knowledge representation in a denotational, formalized, and deductive way. In addition, in this paper, we propose a semiotic, inductive, and approximate approach to ontology creation. We define a conceptual framework, a semantics extraction algorithm, and a first proof of concept applying the algorithm to a small set of Wikipedia documents. Intended as an extension to the prevailing top-down ontologies, we introduce an inductive fuzzy grassroots ontology, which organizes itself organically from existing natural language Web content. Using inductive and approximate reasoning to reflect the natural way in which knowledge is processed, the ontology’s bottom-up build process creates emergent semantics learned from the Web. By this means, the ontology acts as a hub for computing with words described in natural language. For Web users, the structural semantics are visualized as inductive fuzzy cognitive maps, allowing an initial form of intelligence amplification. Eventually, we present an implementation of our inductive fuzzy grassroots ontology Thus,this paper contributes an algorithm for the extraction of fuzzy grassroots ontologies from Web data by inductive fuzzy classification.

A distributed, semiotic-inductive and human-Oriented approach to web-scale knowledge retrieval

Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.

Towards an Emergent Semantic Web

In his in uential article about the evolution of the Web, Berners-Lee [1] envisions a Semantic Web in which humans and computers alike are capable of understanding and processing information. This vision is yet to materialize. The main obstacle for the Semantic Web vision is that in today's Web meaning is rooted most often not in formal semantics, but in natural language and, in the sense of semiology, emerges not before interpretation and processing. Yet, an automated form of interpretation and processing can be tackled by precisiating raw natural language. To do that, Web agents extract fuzzy grassroots ontologies through induction from existing Web content. Inductive fuzzy grassroots ontologies thus constitute organically evolved knowledge bases that resemble automated gradual thesauri, which allow precisiating natural language [2]. The Web agents' underlying dynamic, self-organizing, and best-effort induction, enable a sub-syntactical bottom up learning of semiotic associations. Thus, knowledge is induced from the users' natural use of language in mutual Web interactions, and stored in a gradual, thesauri-like lexical-world knowledge database as a top-level ontology, eventually allowing a form of computing with words [3]. Since when computing with words the objects of computation are words, phrases and propositions drawn from natural languages, it proves to be a practical notion to yield emergent semantics for the Semantic Web. In the end, an improved understanding by computers on the one hand should upgrade human- computer interaction on the Web, and, on the other hand allow an initial version of human- intelligence amplification through the Web.

Evaluating the prevalence, content and readability of complementary and alternative medicine (CAM) web pages on the internet.

Complementary and alternative medicine (CAM) use is growing rapidly. As CAM is relatively unregulated, it is important to evaluate the type and availability of CAM information. The goal of this study is to deter-mine the prevalence, content and readability of online CAM information based on searches for arthritis, diabetes and fibromyalgia using four common search engines. Fifty-eight of 599 web pages retrieved by a "condition search" (9.6%) were CAM-oriented. Of 216 CAM pages found by the "condition" and "condition + herbs" searches, 78% were authored by commercial organizations, whose pur-pose involved commerce 69% of the time and 52.3% had no references. Although 98% of the CAM information was intended for consumers, the mean read-ability was at grade level 11. We conclude that consumers searching the web for health information are likely to encounter consumer-oriented CAM advertising, which is difficult to read and is not supported by the conventional literature.

Comparing communication technology on Chinese, English, and Spanish diabetes web sites.

Technological and cultural factors influence access to health information on the web in multifarious ways. We evaluated structural differences and availability of communication services on the web in three diverse language and cultural groups: Chinese, English, and Spanish. A total of 382 web sites were analyzed: 144 were English language sites (38%), 129 were Chinese language sites (34%), and 108 were Spanish language sites (28%). We did not find technical differences in the number of outgoing links per domain or the total availability of communication services between the three groups. There were differences in the distribution of available services between Chinese and English sites. In the Chinese sites, there were more communication services between consumers and health experts. Our results suggest that the health-related web presence of these three cultural groups is technologically comparable, but reflects differences that may be attributable to cultural factors.

Assimilation and contrast in web product reviews: devaluing the recommendation of a proficient but dissimilar reviewer

When viewing web-consumer reviews consumers encounter the reviewers in an anonymous environment. Although their interactions are only virtual they still exchange social information, e.g. often reviewers refer to their proficiency or consumption motives within the review texts. Do these social information harm the viewers’ perception of the recommended products? The present study addresses this question by applying the paradigm of social comparison (Mussweiler, 2003) to web-consumer reviews. In a laboratory experiment with a student sample (n = 120) we manipulated the perceived similarity between reviewer and viewer and the perceived proficiency of the reviewer. A measurement of achievement goals (Elliott & McGregor, 2001) and average number of hours of study prior to the experiment allowed to introduce the reviewer as high [low] in proficiency and similar [dissimilar] in achievement goals. As predicted, the viewer’s evaluation of the recommended products differed as a function of this social information. Contrasting with the reviewer led to devaluing the products recommended by a proficient but dissimilar reviewer. However, against our prediction social comparison with the reviewer did not affect the viewer`s self-evaluation. Whether social information in web-product reviews affects the viewer`s self-evaluation and induces both social comparison processes remains an open question. Future studies aim to address this by manipulating the informational focus of the viewer, rather than the perceived similarity between viewer and reviewer. So far, the present study extends the application of social comparison to consumption environments and contributes to the understanding of the virtual social identity.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.