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Squamous cell carcinoma (SCC) is the second most common malignancy skin cancer. It is characterized by abnormal, accelerated growth of squamous cells (SCs). SCC occurs when DNA damage from exposure to ultraviolet radiation or other damaging agents trigger abnormal changes in the SCs, presenting as painless lesions on areas of high sun exposure, such as the dorsum of the hand and upper extremity. For most skin SCC, the surgical excision alone is standard practice. However, recent efforts in new treatment strategies have involved around adjuvant or concomitant electrochemotherapy (ECT). ECT is a non-thermal tumor ablation modality, safe and effective on any type of solid tumor. An 87-year-old patient affected by hand SCC with invasion of deep structures including tendons was treated with neoadjuvant intra-tumoral ECT sessions followed by a selective surgical removal and reconstruction of the substance loss with collagen dermal template (CDT). Two neoadjuvant intra-tumoral ECT procedures, at distance of 3 months, with the aim to reduce the tumor size before a selective surgery, were performed. This study shows that combined surgical selective excision with ECT and CDT is a valid technique for the extended-deep dorsal hand tumor lesions reconstruction.

In a decentralized household energy system comprised of various devices such as home appliances, electric vehicles, and solar panels, end-users are able to dig deeper into the system's details and further achieve energy sustainability if they are presented with data on the electric energy consumption and production at the granularity of the device. However, many databases in this field are siloed from other domains, including solely information pertaining to energy. This may result in the loss of information (e.g. weather) on each device's energy use. Meanwhile, a large number of these datasets have been extensively used in computational modeling techniques such as machine learning models. While such computational approaches achieve great accuracy and performance by concentrating only on a local view of datasets, model reliability cannot be guaranteed since such models are very vulnerable to data input fluctuations when information omission is taken into account. This article tackles the data isolation issue in the field of smart energy systems by examining Semantic Web methods on top of a household energy system. We offer an ontology-based approach for managing decentralized data at the device-level resolution in a system. As a consequence, the scope of the data associated with each device may easily be expanded in an interoperable manner throughout the Web, and additional information, such as weather, can be obtained from the Web, provided that the data is organized according to W3C standards., Comment: Published in Sustainable Energy, Grids and Networks (SEGAN) 2022

Recently ontologies have been exploited in a wide range of research areas for data modeling and data management. They greatly assists in defining the semantic model of the underlying data combined with domain knowledge. In this paper, we propose the Climate Analysis (CA) Ontology to model climate datasets used by remote sensing analysts. We use the data published by National Oceanic and Atmospheric Administration (NOAA) to further explore how ontology modeling can be used to facilitate the field of climatic data processing. The idea of this work is to convert relational climate data to the Resource Description Framework (RDF) data model, so that it can be stored in a graph database and easily accessed through the Web as Linked Data. Typically, this provides climate researchers, who are interested in datasets such as NOAA, with the potential of enriching and interlinking with other databases. As a result, our approach facilitates data integration and analysis of diverse climatic data sources and allows researchers to interrogate these sources directly on the Web using the standard SPARQL query language., Published in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2021

In a decentralized household energy system consisting of various devices such as washing machines, heat pumps, and solar panels, understanding the electric energy consumption and production data at the granularity of the device helps end-users be closer to the system and further achieve the sustainability of energy use. However, many datasets in this area are isolated from other domains with records of only energy-related data. This may raise a loss of information (e.g. weather) that is relevant to the energy use of each device. A noticeable disadvantage is that many of those datasets have to be used in computational modeling approaches such as machine learning models, which are vulnerable to the data feed, to advance the understanding of energy consumption and production. Although such computational methods have achieved a high benchmark merely through a local view of datasets, the reusability cannot be firmly guaranteed when the information omission is taken into account. This paper addresses the data isolation problem in the smart energy systems area by exploring Semantic Web techniques on top of a household energy system. We propose an ontology modeling solution for the management of decentralized data at the resolution of a device in the system. As a result, the scope of the data concerning each device can be easily extended to be wider across the web and more information that may be of interest such as weather can be retrieved from the Web if the data are structured by the ontology., Published in IEEE International Conference on Smart Energy Systems and Technologies (SEST), 2021

The MEPDaW workshop series targets one of the emerging and fundamental problems of the Web, specifically the management and preservation of evolving knowledge graphs. During the past six years, the workshop series has been gathering a community of researchers and practitioners around these challenges. To date, the series has successfully published more than 30 articles allowing more than 50 individual authors to present and share their ideas. This 6th edition, virtually co-located with the International Semantic Web Conference (ISWC 2020), gathered the community around nine research publications and one invited keynote presentation. The event took place online on the 1st of November, 2020.

Chronic ulcers are characterized by loss of substance without a normal tendency towards spontaneous healing. The Wound Bed Preparation Guideline advises that after diagnosis, the expert should correct the biological state of the ulcer micro-environment based on TIME principles (Tissue, Infection, Moisture balance, Epidermal). There are many ways to treat such ulcers, for example through use of advanced dressings, negative pressure, surgical toilets, dermal substitutes, autologous skin grafting, and free or local flaps. In vitro and in vivo pre-clinical models hold widely acknowledged potential yet complex limitations. Tissue bioengineering could be an ideal approach to foster innovative strategies in wound healing. Our observational study reports on an in vitro and in vivo evaluation of a bio-functionalized scaffold composed of platelet-rich plasma (PRP) and hyaluronic acid (HA) used in 182 patients affected by chronic ulcers (diabetic and vascular), comparing the results with a control group of 182 patients treated with traditional dressings (HA alone). After 30 days the patients who had undergone the combined treatment (PRP + HA), showed 96.8% &plusmn, 1.5% re-epithelialization, as compared to 78.4% &plusmn, 4.4% in the control group (HA only). Within 80 days, they had 98.4% &plusmn, 1.3% re-epithelialization as compared to 87.8% &plusmn, 4.1% in the control group (HA only, p &lt, 0.05). No local recurrence was observed during the follow-up period. PRP + HA treatment showed stronger regenerative potential in terms of epidermal proliferation and dermal renewal compared with HA alone.

The healing of venous and arterial ulcers is slow, and in some cases, they may not heal at all. This study aims to demonstrate the clinical advantage of Nevelia&reg, an innovative collagen dermal template substitute (DS) in venous and arterial chronic ulcers treatment. 35 patients affected by chronic vascular ulcers with a mean area of 35.1 &plusmn, 31.8 cm2 were treated with DS followed by autologous dermal epidermal graft (DEG). Follow-up was performed at 7-14-21 and 28 days after DS implant and 7-14-21 and 28 days after DEG. At 28 days after DEG, the mean values of Manchester Scar Scale was of 1.8 &plusmn, 0.7 for skin color, 1.6 &plusmn, 0.7 for skin contour, 1.7 &plusmn, 0.7 for distortion, and 1.7 &plusmn, 0.7 for skin texture, whereas skin was matte in 27 patients (77%) and shiny in the remaining eight cases (23%). Histological findings correlate with the clinical result showing a regenerated skin with reactive epidermal hyperplasia and dermal granulation tissue after two weeks (T1), and after three weeks (T2) a re-epithelialization and a formed new tissue architecture analogue to normal skin physiology. These data suggest that Nevelia&reg, could be useful to treat chronic venous and arterial ulcers.

Smart energy systems in general, and solar energy analysis in particular, have recently gained increasing interest. This is mainly due to stronger focus on smart energy saving solutions and recent developments in photovoltaic (PV) cells. Various data-driven and machine-learning frameworks are being proposed by the research community. However, these frameworks perform their analysis - and are designed on - specific, heterogeneous and isolated datasets, distributed across different sites and sources, making it hard to compare results and reproduce the analysis on similar data. We propose an approach based on Web (W3C) standards and Linked Data technologies for representing and converting PV and weather records into an Resource Description Framework (RDF) graph-based data format. This format, and the presented approach, is ideal in a data integration scenario where data needs to be converted into homogeneous form and different datasets could be interlinked for distributed analysis., Published in Proc. International Conference on Smart Energy Systems and Technologies (SEST), 2019

Companion Proceedings of The 2019 World Wide Web Conference on - WWW '19 The 2019 World Wide Web Conference, WWW '19, San Francisco, USA, 13 May 2019 - 17 May 2019; New York, NY : ACM Press 961-965 (2019). doi:10.1145/3308560.3316521, Published by ACM Press, New York, NY

A paper explaining as a recommendation for publishing fiscal data, including assessment framework for fiscal datasets.

Public administrations are continuously publishing open data, increasing the amount of government open data over time. The published data includes budgets and spending as part of fiscal data; publishing these data is an important part of transparent and accountable governance. However, open fiscal data should also meet open data publication guidelines. When requirements in data guidelines are not met, effective data analysis over published datasets cannot be performed effectively. In this article, we present Open Fiscal Data Publication (OFDP), a framework to assess the quality of open fiscal datasets. We also present an extensive open fiscal data assessment and common data quality issues found; additionally, open fiscal data publishing guidelines are presented. We studied and surveyed main quality factors for open fiscal datasets. Moreover, the collected quality factors have been scored according to the results of a questionnaire to score quality factors within the OFDP assessment framework. We gather and comprehensively analyze a representative set of 77 fiscal datasets from several public administrations across different regions at different levels (e.g., supranational, national, municipality). We characterize quality issues commonly arising in these datasets. Our assessment shows that there are many quality factors in fiscal data publication that still need to be taken care of so that the data can be analyzed effectively. Our proposed guidelines allow for publishing open fiscal data where these quality issues are avoided.

Unification and automation of RESTful web services' documentation and descriptions is currently receiving increasing attention. The open-source OpenAPI Specification (formerly known as Swagger) has become core of this effort and has been adopted by a number of major companies. It allows the description of RESTful web services using objects represented in JSON or YAML file formats. As a result, the created descriptions are human and machine-readable, but not machine-understandable. In this paper, we propose a nonintrusive approach for the addition of semantic annotations (similar to RDFa and JSON-LD for HTML) to specific fields of the OpenAPI Specification. We created a lightweight vocabulary for describing RESTful web services using this specification. Furthermore, we practically demonstrate how OpenAPI objects can be enriched with semantic descriptions in a minimally invasive way by adding URIs in the values of chosen OpenAPI properties.

This paper presents an approach for metadata reconciliation, curation and linking for Open Governamental Data Portals (ODPs). ODPs have been lately the standard solution for governments willing to put their public data available for the society. Portal managers use several types of metadata to organize the datasets, one of the most important ones being the tags. However, the tagging process is subject to many problems, such as synonyms, ambiguity or incoherence, among others. As our empiric analysis of ODPs shows, these issues are currently prevalent in most ODPs and effectively hinders the reuse of Open Data. In order to address these problems, we develop and implement an approach for tag reconciliation in Open Data Portals, encompassing local actions related to individual portals, and global actions for adding a semantic metadata layer above individual portals. The local part aims to enhance the quality of tags in a single portal, and the global part is meant to interlink ODPs by establishing relations between tags., 8 pages,10 Figures - Under Revision for ICSC2016

We conduct a systematic survey with the aim of assessing open government data initiatives, that is; any attempt, by a government or otherwise, to open data that is produced by a governmental entity. We describe the open government data life-cycle and we focus our discussion on publishing and consuming processes required within open government data initiatives. We cover current approaches undertaken for such initiatives, and classify them. A number of evaluations found within related literature are discussed, and from them we extract challenges and issues that hinder open government initiatives from reaching their full potential. In a bid to overcome these challenges, we also extract guidelines for publishing data and provide an integrated overview. This will enable stakeholders to start with a firm foot in a new open government data initiative. We also identify the impacts on the stakeholders involved in such initiatives.

Clostridial myonecrosis (CM) is a rare, life threatening necrotizing infection of a skeletal muscle caused by Clostridium perfringens in the majority of cases. The diagnosis may be difficult because of few diagnostic and cutaneous signs early in its course. Standard therapy involves surgical debridements of a devitalized tissue and high-dose organism-specific antibiotic therapy. The hyperbaric oxygen has also showed its usefulness in the treatment of these infections. Autograft systems as tissue replacement, based on bioengineered materials, have been demonstrated to be safe and effective treatments for chronic wounds and a suitable physiotherapy is recommended for the recovery of functional impairments of upper extremities. We present a rare case of CM of right upper limb treated with a combination of standard treatments and new techniques.

A 61-year-old patient was affected by flaccid paraplegia for 20 years because of post-traumatic medullar injury caused by an accidental fall, with stage IV sacral pressure ulcer for 3 years. The patient later developed stage IV sacral pressure ulcer. After 6 months, a new granulation tissue formation appeared in the wound and a reduction of its diameter was observed (length 20 cm, width 15 cm, depth 5 cm). We therefore treated the wound with PRP (platelet rich plasma) intra-lesion and peri-lesional injections. The wounds were covered with three-dimensional polymerised hyaluronic acid medicated biologic dressing. After the surgery, a moderate reduction in diameter and the depth was observed. Super-oxidised solution (SOS-Dermacyn) was applied to control infection locally together with negative pressure to control the exudate and the local bacteremia, to avoid infectious complications without application of systematic antibiotic therapy.

International audience; Wikis are often considered as being a wide source of information. However, identifying provenance information about their content is crucial, whether it is for computing trust in public wiki pages or to identify experts in corporate wikis. In this paper, we address this issue by providing a lightweight ontology for provenance management in wikis, based on the W7 model. Furthermore, we showcase the use of our model in a framework that computes provenance information in Wikipedia, also using DBpedia to compute provenance and contribution information per category, and not only per page.

Patellofemoral Pain Syndrome (PFPS) is a common musculoskeletal complaint. The presence of a delay between vastus medialis obliquus (VMO) and vastus lateralis (VL) muscle onset has been suggested in the literature as a possible cause of PFPS, with poor agreement amongst authors on the value of the delay. In this study we computed the delay in the activation of VMO and VL in 15 PFPS patients and 20 age-matched controls (Ctrls) during the following tasks: sit to stand, stand to sit, squat, step up and step down. Activation instants were detected from surface EMG data by a double-threshold statistical detector. In order to compare the muscle activity throughout the task, we computed the delay between the instants in which the VMO and VL normalised envelopes reached subsequent normalised amplitude levels, until the envelope peak. In all investigated tasks but sit to stand, the onset delay was lower or equal then 0.02s, without group differences. Similarly, no differences between Ctrls and PFPS timing were found throughout all tasks, until the peak. Our results do not support the hypothesis that an onset delay between VMO and VL can be one of the causes of PFPS.

Environmental exposures transported across air, land and water can affect our health making us more susceptible to developing a disease. Therefore, researchers need to face the complex task of integrating environmental exposures and linking them to health events with the relevant spatiotemporal and health context for individuals or populations. We present a usability evaluation approach and study of a semantic framework (i.e. Knowledge Graph, Methodology and User Interface) to enable Health Data Researchers (HDR) to link particular health events with environmental data for rare disease research. The usability study includes 17 HDRs with expertise in health data related to Anti-Neutrophil Cytoplasmic Antibody (ANCA)-associated vasculitis (AAV) in Ireland and Kawasaki Disease in Japan, and with no previous practical experience in using Semantic Web (SW) technologies. The evaluation results are promising in that they indicate that the framework is useful in allowing researchers themselves to link health and environmental data whilst hiding the complexities of SW technologies. As a result of this work, we also discuss the limitations of the approach together with the applicability to other domains. Beyond the direct impact on environmental health studies, the description of the evaluation approach can guide researchers in making SW technologies more accessible to domain experts through usability studies.

Governments are one of the largest producers and collectors of data in many different domains. As one major aim of open government data initiatives is the release of social and commercial value, we here explore existing processes of value creation on government data. We identify the dimensions that impact, or are impacted by value creation, and distinguish between the different value creating roles and participating stakeholders. We propose the use of Linked Data as an approach to enhance the value creation process, and provide a Value Creation Assessment Framework to analyse the resulting impact.

Poster in a RASH HTML format detailing the architecture of OpenBudgets platform.Pre-print version of the paper acceptedat SEMANTiCS2017 conference in Amsterdam, Netherlands.