Data Driven Discovery in Astrophysics

We review some aspects of the current state of data-intensive astronomy, its methods, and some outstanding data analysis challenges. Astronomy is at the forefront of "big data" science, with exponentially growing data volumes and data rates, and an ever-increasing complexity, now entering the Petascale regime. Telescopes and observatories from both ground and space, covering a full range of wavelengths, feed the data via processing pipelines into dedicated archives, where they can be accessed for scientific analysis. Most of the large archives are connected through the Virtual Observatory framework, that provides interoperability standards and services, and effectively constitutes a global data grid of astronomy. Making discoveries in this overabundance of data requires applications of novel, machine learning tools. We describe some of the recent examples of such applications.Comment: Keynote talk in the proceedings of ESA-ESRIN Conference: Big Data from Space 2014, Frascati, Italy, November 12-14, 2014, 8 pages, 2 figure

New business and economic models in the connected digital economy

This paper discusses business models as a systemic phenomenon as opposed to traditional reductionistic approaches of business disciplines. It presents the ways connectivity change economic models due to the availability of consumption data as an economic resource, markets forming at consumption spaces, and how industries could disrupt one another when connected through consumption technologies. The paper further suggests that the challenges posed by connectivity results in the redrawing of traditional firm and market boundaries. It proposes for more research into modularity, transaction costs, the future role of the firm, and the necessary transformation of businesses to stay agile in a connected digital economy

Digital and algorithmic technology: the impact on employment and the workforce

L’obiettivo di questo articolo è rispondere alle domande inerenti al futuro del lavoro dal punto di vista della trasformazione tecnologica, con l’uso della robotica, dell’intelligenza algoritmica, dei social media e dell’evoluzione dei modelli di business. Lo studio parte da un’analisi della metà degli anni 2000, durante una seconda rivoluzione informatica, in cui l’affermazione dell’economia digitale è stata osservata con l’intensificazione del processo di outsourcing e la contingenza dei modelli contemporanei di organizzazione del lavoro e della produzione. Si parte dall’analisi del lavoro mediante piattaforma, con la premessa che si tratta di un fenomeno distinto da quello dell’Industria Digitale 4.0 perché riguarda la realizzazione di intensi processi di produzione di beni e servizi che vengono completamente esternalizzati da qualsiasi luogo produttivo tradizionale. Così, l’articolo mira ad analizzare questa nuova evoluzione della produzione nell’ultima era digitale algoritmica, studiandone il funzionamento e l’impatto sul lavoro, i salari e la società. La prospettiva teorica è quella di utilizzare un’analisi rinnovata di questa dimensione produttiva

10471 Abstracts Collection -- Scalable Visual Analytics

From 21.11. to 26.11.2010, the Dagstuhl Seminar 10471 ``Scalable Visual Analytics\u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Data Driven Discovery in Astrophysics

We review some aspects of the current state of data-intensive astronomy, its methods, and some outstanding data analysis challenges. Astronomy is at the forefront of "big data" science, with exponentially growing data volumes and data rates, and an ever-increasing complexity, now entering the Petascale regime. Telescopes and observatories from both ground and space, covering a full range of wavelengths, feed the data via processing pipelines into dedicated archives, where they can be accessed for scientific analysis. Most of the large archives are connected through the Virtual Observatory framework, that provides interoperability standards and services, and effectively constitutes a global data grid of astronomy. Making discoveries in this overabundance of data requires applications of novel, machine learning tools. We describe some of the recent examples of such applications

From Sensor to Observation Web with Environmental Enablers in the Future Internet

This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)

Access to Digital Cultural Heritage: Innovative Applications of Automated Metadata Generation Chapter 1: Digitization of Cultural Heritage – Standards, Institutions, Initiatives

The first chapter "Digitization of Cultural Heritage – Standards, Institutions, Initiatives" provides an introduction to the area of digitisation. The main pillars of process of creating, preserving and accessing of cultural heritage in digital space are observed. The importance of metadata in the process of accessing to information is outlined. The metadata schemas and standards used in cultural heritage are discussed. In order to reach digital objects in virtual space they are organized in digital libraries. Contemporary digital libraries are trying to deliver richer and better functionality, which usually is user oriented and depending on current IT trend. Additionally, the chapter is focused on some initiatives on world and European level that during the years enforce the process of digitization and organizing digital objects in the cultural heritage domain. In recent years, the main focus in the creation of digital resources shifts from "system-centred" to "user-centred" since most of the issues around this content are related to making it accessible and usable for the real users. So, the user studies and involving the users on early stages of design and planning the functionality of the product which is being developed stands on leading position

Concept of a Self-Learning Workplace Cell for Worker Assistance While Collaboration with a Robot Within the Self-Adapting-Production-Planning-System

For some time, the focus of past research on industrial workplace designs has been the optimization of processes from the technological point of view. Since human workers have to work within this environment the design process must regard Human Factor needs. The operators are under additional stress due to the range of high dynamic processes and due to the integration of robots and autonomous operating machines. There have been few studies on how Human Factors influence the design of workplaces for Human-Robot Collaboration (HRC). Furthermore, a comprehensive, systematic and human-centred design solution for industrial workplaces particularly considering Human Factor needs within HRC is widely uncertain and a specific application with reference to production workplaces is missing. The research findings described in this paper aim the optimization of workplaces for manual production and maintenance processes with respect to the workers within HRC. In order to increase the acceptance of integration of human-robot teams, the concept of the Assisting-Industrial-Workplace-System (AIWS) was developed. As a flexible hybrid cell for HRC integrated into a Self-Adapting-Production-Planning-System (SAPPS) assists the worker while interaction