Monitoring for COVID-19 by universal testing in a homeless shelter in Germany: a prospective feasibility cohort study

Background: Living conditions in homeless shelters facilitate the transmission of COVID-19. Social determinants and pre-existing health conditions place homeless people at increased risk of severe disease. Described outbreaks in homeless shelters resulted in high proportions of infected residents and staff members. In addition to other infection prevention strategies, regular shelter-wide (universal) testing for COVID-19 may be valuable, depending on the level of community transmission and when resources permit. Methods: This was a prospective feasibility cohort study to evaluate universal testing for COVID-19 at a homeless shelter with 106 beds in Berlin, Germany. Co-researchers were recruited from the shelter staff. A PCR analysis of saliva or self-collected nasal/oral swab was performed weekly over a period of 3 weeks in July 2020. Acceptability and implementation barriers were analyzed by process evaluation using mixed methods including evaluation sheets, focus group discussion and a structured questionnaire. Results: Ninety-three out of 124 (75%) residents were approached to participate in the study. Fifty-one out of the 93 residents (54.8%) gave written informed consent; thus 41.1% (51 out of 124) of all residents were included in the study. Among these, high retention rates (88.9-93.6%) of a weekly respiratory specimen were reached, but repeated collection attempts, as well as assistance were required. Around 48 person-hours were necessary for the sample collection including the preparation of materials. A self-collected nasal/oral swab was considered easier and more hygienic to collect than a saliva specimen. No resident was tested positive by RT-PCR. Language barriers were the main reason for non-participation. Flexibility of sample collection schedules, the use of video and audio materials, and concise written information were the main recommendations of the co-researchers for future implementation. Conclusions: Voluntary universal testing for COVID-19 is feasible in homeless shelters. Universal testing of high-risk facilities will require flexible approaches, considering the level of the community transmission, the available resources, and the local recommendations. Lack of human resources and laboratory capacity may be a major barrier for implementation of universal testing, requiring adapted approaches compared to standard individual testing. Assisted self-collection of specimens and barrier free communication may facilitate implementation in homeless shelters. Program planning must consider homeless people's needs and life situation, and guarantee confidentiality and autonomy

OPAL—The Toolbox for the Integration and Analysis of IoT in a Semantically Annotated Way

Industrial Internet of Things (IIoT) applications are being used more and more frequently. Data collected by various sensors can be used to provide innovative digital services supporting increasing efficiency or cost reduction. The implementation of such applications requires the integration and analysis of heterogeneous data coming from a broad variety of sensors. To support these steps, this paper introduces OPAL, a software toolbox consolidating several software components for the semantically annotated integration and analysis of IoT-data. Data storage is realized in a standardized and INSPIRE-compliant way utilizing the SensorThings API. Supporting a broad variety of use cases, OPAL provides several import adapters to access data sources with various protocols (e.g., the OPC UA protocol, which is often used in industrial environments). In addition, a unified management and execution environment, called PERMA, is introduced to allow the programming language independent integration of algorithms

Employing Geospatial Semantics and Semantic WebTechnologies in Natural Disaster Management

In a natural disaster situation, it is crucial to orchestrate an efficient response, which prevents, or - at least - mitigates damages. Based on the assumption, that a well-informed decision maker can make the best decisions, s/he should have access to all available information. Thus, employing both internal and external data empowers decision makers. Since natural disasters are usually limited to a certain (previously unknown) area, it is of high importance to get to know about the local context of a disaster. Critical infrastructure, such as hospitals, energy supply, buildings with vulnerable beings (kindergarten, elder care, etc.) play an important role in crisis management. Nevertheless, a decision maker might not be aware of all of these places; yet, knowledge about these can often be found in external, public knowledge bases, such as Wikidata. Semantic Web Technology offers tools to integrate data from diverse data stores, offering a giant source of information. To improve situational awareness, this information should be tapped. By employing geospatial semantic features of knowledge bases, it is possible to integrate several data stores and only find information, that is valid within the range of a disaster and therefore of interest to a decision maker. The poster presents the integration of Wikidata as an external knowledge-base into a Decision-Support-System by using federated queries. Through employing geospatial semantic features, only relevant information is retrieved

An Ontology for Cultural Heritage Protection against Climate Change

Environmental factors, worsened by the increasing climate change impact, represent significant threats to European Cultural Heritage (CH) assets. In Europe, the huge number and diversity of CH assets, together with the different climatological sub-regions aspects, as well as the different adaptation policies to climate change adopted (or to be adopted) by the different nations, generate a very complex scenario. This paper will present a multidisciplinary methodology that will bridge the gap between two different worlds: the CH stakeholders and the scientific/technological experts. Since protecting cultural heritage assets and increasing their resilience against effects caused by the climate change is a multidisciplinary task, experts from many domains need to work together to meet their conservation goals. This paper discusses a method for facilitating the work for the different experts. A new ontology has been designed integrating all necessary aspects for improving the resilience of cultural heritages on site. This ontology combines the following topics: Cultural Heritage Assets, Stakeholders and Roles, Climate and Weather Effects, Risk Management, Conservation Actions, Materials, Sensors, Models and Observations, Standard Operation Procedures/Workflows and Damages

Using crowdsource information for managing climate events through the use of modern mobile technology: Paper presented at 2nd International Conference on Citizen Observatories for natural hazards and Water Management, COWM 2018, Venice, 27-30 November 2018

- We propose a mobile application facilitating an ontology to support all participants of a climate-related crises. - Semantic classification is achieved by involving the user and without requiring semantic analysis tools. - Participants in the field can share and exchange information with the control centre. - Using multimodal input and potent analysis modules enhance situational awareness. - Additional crowdsourcing based on ontological backend offers machine-interpretable dat

Implementing the HERACLES Ontology - An Ontology as backbone for a Knowledge Base in the Cultural Heritage Protection Domain

Environmental factors, worsened by the increasing climate change impact, represent significant threats to European Cultural Heritage (CH) assets. In Europe, the huge number and diversity of CH assets, together with the different climatological sub-regions aspects, as well as the different adaptation policies to climate change adopted (or to be adopted) by the different nations, generate a very complex scenario. This paper will present a multidisciplinary methodology that will bridge the gap between two different worlds: the CH stakeholders and the scientific/technological experts. Since protecting cultural heritage assets and increasing their resilience against effects caused by the climate change is a multidisciplinary task, experts from many domains need to work together to meet their conservation goals. In this paper we introduce the HERACLES Ontology, which structures data and explicitly links adjacent data. Furthermore the implementation of the HERACLES Ontology within the HERACLES Knowledge Base is described. Use cases and benefits of the application are given. The ontology comprises the following topics: Cultural Heritage Assets, Stakeholders and Roles, Climate and Weather Effects, Risk Management, Conservation Actions, Materials, Sensors, Models and Observations, Standard Operation Procedures/Workflows and Damages

Management of Sensor Data with Open Standards

In an emergency, getting up-to-date information about the current situation is crucial to orchestrate an efficient response. Due to its objectivity, preciseness and comparability, time-series data offer broad possibilities to manage emergency incidents. Since the Internet of Things (IoT) is rapidly growing with an estimated number of 30 billion sensors in 2020, it offers excellent potential to collect time-series data for improving situational awareness. The IoT brings several challenges: caused by a splintered sensor manufacturer landscape, data comes in various structures, incompatible protocols and unclear semantics. To tackle these challenges a well-defined interface, from where uniform data can be queried, is necessary. The Open Geospatial Consortium (OGC) has recognized this demand and developed the Sensor Things API standard, an open, unified way to interconnect devices throughout the IoT, which is implemented by the FRaunhofer-Open source-SensorThings-Server (FROST). This paper presents the standard, its implementation and the application to the domain of crisis management

Introducing the HERACLES Ontology—Semantics for Cultural Heritage Management

Cultural Heritage (CH) (In the context of this paper, we consider cultural heritage built tangible cultural heritage, such as buildings or monuments.) is an important source of identity for humankind and needs to be conserved for future generations. Climate change (CC) will morph the environmental landscape, thus leading to climate stress imposed on CH. Experts from different domains, including, but not limited to, material scientists, conservators and managers of cultural heritage collaborate to find out how CC affects CH and how potentially harmful impacts can be mitigated. To find and understand correlations and effects of different factors, researchers collect and analyse vast amounts of data. Still, experts often cannot exchange or make efficient use of data since it often is unstructured, incompatible, or its plain existence is simply unknown. This article introduces means to achieve consent about available knowledge, to exploit synergy effects through the combination of available information and to provide a flexible multisource information platform in collaborative cultural heritage management projects. In the context of the European project HERACLES (HERACLES—HEritage Resilience Against CLimate Events on Site. Further information: http://www.heracles-project.eu/), an application-ontology was developed. The ontology facilitates reuse and integration of data through structuring and representing its semantics. The involvement in the HERACLES project guaranteed end-user driven development, practical results and encompassment of all domains represented in the project

The Backbone of Decision Support Systems: The Sensor to Decision Chain

Understanding the current situation is critical in every natural disaster or crisis. Therefore, there is a need for accurate and up-to-date information about the scope, extent and impact of a disaster. The basis for this information is data that is available through a variety of sensors. Decision Support Systems (DSSs) support decision makers in disaster management, response, and recovery by providing early warnings, insights into the current situation and recommendations for mitigation actions. For this purpose, raw sensor data needs to be collected, analyzed, integrated, and its semantics need to be automatically understood by the system. This series of processes forms a generic sensor to decision chain. In this paper, we present solutions and technologies to integrate those steps seamlessly, also demonstrating how each step of the pipeline can be visualized