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In this paper, we propose an approach for an application of Bayesian optimization using Sequential Monte Carlo (SMC) and concepts from the statistical physics of classical systems. Our method leverages the power of modern machine learning libraries such as NumPyro and JAX, allowing us to perform Bayesian optimization on multiple platforms, including CPUs, GPUs, TPUs, and in parallel. Our approach enables a low entry level for exploration of the methods while maintaining high performance. We present a promising direction for developing more efficient and effective techniques for a wide range of optimization problems in diverse fields., Comment: 8 pages, 7 figures, accepted to the International Conference on Computer Science 2023

Frequently in socio-environmental sciences, models are used as tools to represent, understand, project and predict the behaviour of these complex systems. Along the modelling chain, Good Modelling Practices have been evolving that ensure -- amongst others -- that models are transparent and their results replicable. Whenever such models are represented in software, Good Modelling meet Good Software Practices, such as a tractable development workflow, good code, collaborative development and governance, continuous integration and deployment; and they meet Good Scientific Practices, such as attribution of copyrights and acknowledgement of intellectual property, publication of a software paper and archiving. Too often in existing socio-environmental model software, these practices have been regarded as an add-on to be considered at a later stage only; modellers have shied away from publishing their model as open source out of fear that having to add good practices is too demanding. We here argue for making a habit of following a list of simple and not so simple practices early on in the implementation of the model life cycle. We contextualise cherry-picked and hands-on practices for supporting Good Modelling Practice, and we demonstrate their application in the example context of the Viable North Sea fisheries socio-ecological systems model., Comment: 2 Figures

Developers rely on the Rust programming language's static safety guarantees to write secure and performant applications. However, Rust is frequently used to interoperate with other languages which allow design patterns that conflict with Rust's aliasing models. Miri is the only dynamic analysis tool capable of validating applications against these models, but it does not support foreign functions, indicating that there may be a critical correctness gap at the heart of the Rust ecosystem. We conducted a large-scale evaluation of Rust libraries that call foreign functions to determine whether Miri's dynamic analyses remain useful in this context. We used Miri and an LLVM interpreter to jointly execute applications that call foreign functions, where we found 48 instances of undefined or undesired behavior. These include three bugs from libraries that had over 10,000 daily downloads on average during our observation period and one from a library maintained by the Rust Project. Many of the errors we found involved incompatible aliasing patterns, but Rust's latest Tree Borrows aliasing model was significantly more permissive than the earlier Stacked Borrows model. The Rust community must invest in new, production-ready tooling for multi-language applications to ensure that developers can detect these errors., Comment: 13 pages, preprint

Datasets collecting software mentions from scholarly publications can potentially be used for research into the software that has been used in the published research, as well as into the practice of software citation. Recently, new software mention datasets with different characteristics have been published. We present an approach to assess the usability of such datasets for research on research software. Our approach includes sampling and data preparation, manual annotation for quality and mention characteristics, and annotation analysis. We applied it to two software mention datasets for evaluation based on qualitative observation. Doing this, we were able to find challenges to working with the selected datasets to do research. Main issues refer to the structure of the dataset, the quality of the extracted mentions (54% and 23% of mentions respectively are not to software), and software accessibility. While one dataset does not provide links to mentioned software at all, the other does so in a way that can impede quantitative research endeavors: (1) Links may come from different sources and each point to different software for the same mention. (2) The quality of the automatically retrieved links is generally poor (in our sample, 65.4% link the wrong software). (3) Links exist only for a small subset (in our sample, 20.5%) of mentions, which may lead to skewed or disproportionate samples. However, the greatest challenge and underlying issue in working with software mention datasets is the still suboptimal practice of software citation: Software should not be mentioned, it should be cited following the software citation principles., Comment: 17 pages, 8 figures, 8 tables. Revision of a submission to PeerJ Computer Science withdrawn due to impracticalities of examining a sufficient sample size

This chapter presents the potential of interoperability and standardised data publication for cultural heritage resources, with a focus on community-driven approaches and web standards for usability. The Linked Open Usable Data (LOUD) design principles, which rely on JSON-LD as lingua franca, serve as the foundation. We begin by exploring the significant advances made by the International Image Interoperability Framework (IIIF) in promoting interoperability for image-based resources. The principles and practices of IIIF have paved the way for Linked Art, which expands the use of linked data by demonstrating how it can easily facilitate the integration and sharing of semantic cultural heritage data across portals and institutions. To provide a practical demonstration of the concepts discussed, the chapter highlights the implementation of LUX, the Yale Collections Discovery platform. LUX serves as a compelling case study for the use of linked data at scale, demonstrating the real-world application of automated enrichment in the cultural heritage domain. Rooted in empirical study, the analysis presented in this chapter delves into the broader context of community practices and semantic interoperability. By examining the collaborative efforts and integration of diverse cultural heritage resources, the research sheds light on the potential benefits and challenges associated with LOUD., Comment: This is the preprint version of a chapter submitted to be included in the book "Decoding Cultural Heritage: a critical dissection and taxonomy of human creativity through digital tools", to be published by Springer Nature. The chapter is currently undergoing peer review for potential inclusion in the book

Vector embeddings have become ubiquitous tools for many language-related tasks. A leading embedding model is OpenAI's text-ada-002 which can embed approximately 6,000 words into a 1,536-dimensional vector. While powerful, text-ada-002 is not open source and is only available via API. We trained a simple neural network to convert open-source 768-dimensional MPNet embeddings into text-ada-002 embeddings. We compiled a subset of 50,000 online food reviews. We calculated MPNet and text-ada-002 embeddings for each review and trained a simple neural network to for 75 epochs. The neural network was designed to predict the corresponding text-ada-002 embedding for a given MPNET embedding. Our model achieved an average cosine similarity of 0.932 on 10,000 unseen reviews in our held-out test dataset. We manually assessed the quality of our predicted embeddings for vector search over text-ada-002-embedded reviews. While not as good as real text-ada-002 embeddings, predicted embeddings were able to retrieve highly relevant reviews. Our final model, Vec2Vec, is lightweight (<80 MB) and fast. Future steps include training a neural network with a more sophisticated architecture and a larger dataset of paired embeddings to achieve greater performance. The ability to convert between and align embedding spaces may be helpful for interoperability, limiting dependence on proprietary models, protecting data privacy, reducing costs, and offline operations., Comment: 14 pages, 6 figures, 5 tables

Process Execution Engines are a vital part of Business Process Management (BPM) and Manufacturing Orchestration Management (MOM), as they allow the business or manufacturing logic (expressed in a graphical notation such as BPMN) to be executed. This execution drives and supervises all interactions between humans, machines, software, and the environment. If done right, this will lead to a highly flexible, low-code, and easy to maintain solution, that allows for ad-hoc changes and functional evolution, as well as delivering a wealth of data for data-science applications. The Cloud Process Execution Engine CPEE.org implements a radically distributed scale-out architecture, together with a minimal set of interfaces, to allow for the simplest possible integration with existing services, machines, and existing data-analysis tools. Its open-source components can serve as a blueprint for future development of commercial solutions, and serves as a proven testbed for academic research, teaching, and industrial application since 2008. In this paper we present the architecture, interfaces that make CPEE.org possible, as well as discuss different lifecycle models utilized during execution to provide overarching support for a wide range of data-analysis tasks., Comment: 30 pages, 12 figures, 2 illustrations

Particle accelerators are among the largest, most complex devices. To meet the challenges of increasing energy, intensity, accuracy, compactness, complexity and efficiency, increasingly sophisticated computational tools are required for their design and optimization. It is key that contemporary software take advantage of the latest advances in computer hardware and scientific software engineering practices, delivering speed, reproducibility and feature composability for the aforementioned challenges. A new open source software stack is being developed at the heart of the Beam pLasma Accelerator Simulation Toolkit (BLAST) by LBNL and collaborators, providing new particle-in-cell modeling codes capable of exploiting the power of GPUs on Exascale supercomputers. Combined with advanced numerical techniques, such as mesh-refinement, and intrinsic support for machine learning, these codes are primed to provide ultrafast to ultraprecise modeling for future accelerator design and operations., Comment: 4 pages, 8 figures; NAPAC22, Invited Oral, TUYE2

Process management and process orchestration/execution are currently hot topics; prevalent trends such as automation and Industry 4.0 require solutions which allow domain-experts to easily model and execute processes in various domains, including manufacturing and health-care. These domains, in turn, rely on a tight integration between hardware and software, i.e. via the Internet of Things (IoT). While process execution is about actuation, i.e. actively triggering actions and awaiting their completion, accompanying IoT sensors monitor humans and the environment. These sensors produce large amounts of procedural, discrete, and continuous data streams, that hold the key to understanding the quality of process subjects (e.g. produced parts), outcome (e.g. quantity and quality), and error causes. Processes constantly evolve in conjunction with their IoT environment. This requires joint storage of data generated by processes, with data generated by the IoT sensors is therefore needed. In this paper, we present an extension of the process log standard format XES, namely SensorStream. SensorStream enables to connect IoT data to process events, as well as a set of semantic annotations to describe the scenario and environment during data collection. This allows to preserve the full context required for data-analysis, so that logs can be analyzed even when scenarios or hardware artifacts are rapidly changing. Through additional semantic annotations, we envision the XES extension log format to be a solid based for the creation of a (semi-)automatic analysis pipeline, which can support domain experts by automatically providing data visualization, or even process insights., Comment: 21 papges, 6 figures, 10 listings, not submitted to anywhere yet

As the number of cloud platforms supporting scientific research grows, there is an increasing need to support interoperability between two or more cloud platforms, as a growing amount of data is being hosted in cloud-based platforms. A well accepted core concept is to make data in cloud platforms Findable, Accessible, Interoperable and Reusable (FAIR). We introduce a companion concept that applies to cloud-based computing environments that we call a Secure and Authorized FAIR Environment (SAFE). SAFE environments require data and platform governance structures and are designed to support the interoperability of sensitive or controlled access data, such as biomedical data. A SAFE environment is a cloud platform that has been approved through a defined data and platform governance process as authorized to hold data from another cloud platform and exposes appropriate APIs for the two platforms to interoperate., Comment: 16 pages with 2 figures

The availability of open data and of tools to create visualizations on top of these open datasets have led to an ever-growing amount of geovisualizations on the Web. There is thus an increasing need for techniques to make geovisualizations FAIR - Findable, Accessible, Interoperable, and Reusable. This article explores what it would mean for a geovisualization to be FAIR, presents relevant approaches to FAIR geovisualizations and lists open research questions on the road towards FAIR geovisualizations. The discussion is done using three complementary perspectives: the computer, which stores geovisualizations digitally; the analyst, who uses them for sensemaking; and the developer, who creates them. The framework for FAIR geovisualizations proposed, and the open questions identified are relevant to researchers working on findable, accessible, interoperable, and reusable online visualizations of geographic information., Comment: Article accepted for publication in the International Journal of Geographical Information Science

Operational processes in production, logistics, material handling, maintenance, etc., are supported by cyber-physical systems combining hardware and software components. As a result, the digital and the physical world are closely aligned, and it is possible to track operational processes in detail (e.g., using sensors). The abundance of event data generated by today's operational processes provides opportunities and challenges for process mining techniques supporting process discovery, performance analysis, and conformance checking. Using existing process mining tools, it is already possible to automatically discover process models and uncover performance and compliance problems. In the DFG-funded Cluster of Excellence "Internet of Production" (IoP), process mining is used to create "digital shadows" to improve a wide variety of operational processes. However, operational processes are dynamic, distributed, and complex. Driven by the challenges identified in the IoP cluster, we work on novel techniques for comparative process mining (comparing process variants for different products at different locations at different times), object-centric process mining (to handle processes involving different types of objects that interact), and forward-looking process mining (to explore "What if?" questions). By addressing these challenges, we aim to develop valuable "digital shadows" that can be used to remove operational friction., Comment: 30 pages, 21 figures

Process mining starts from event data. The ordering of events is vital for the discovery of process models. However, the timestamps of events may be unreliable or imprecise. To further complicate matters, also causally unrelated events may be ordered in time. The fact that one event is followed by another does not imply that the former causes the latter. This paper explores the relationship between time and order. Moreover, it describes an approach to preprocess event data having timestamp-related problems. This approach avoids using accidental or unreliable orders and timestamps, creates partial orders to capture uncertainty, and allows for exploiting domain knowledge to (re)order events. Optionally, the approach also generates interleavings to be able to use existing process mining techniques that cannot handle partially ordered event data. The approach has been implemented using ProM and can be applied to any event log., Comment: 12 pages, 7 figures

The ability to independently deploy parts of a software system is one of the cornerstones of modern software development, and allows for these parts to evolve independently and at different speeds. A major challenge of such independent deployment, however, is to ensure that despite their individual evolution, the interfaces between interacting parts remain compatible. This is especially important for enterprise software systems, which are often highly integrated and based on heterogenous IT infrastructures. Although several approaches for interface evolution have been proposed, many of these rely on the developer to adhere to certain rules, but provide little guidance for doing so. In this paper, we present an approach for interface evolution that is easy to use for developers, and also addresses typical challenges of heterogenous enterprise software, especially legacy system integration., Comment: Preprint of a paper to be published at the 18th IEEE International Conference on Software Architecture (ICSA 2021)

Logs are a common way to record detailed run-time information in software. As modern software systems evolve in scale and complexity, logs have become indispensable to understanding the internal states of the system. At the same time however, manually inspecting logs has become impractical. In recent times, there has been more emphasis on statistical and machine learning (ML) based methods for analyzing logs. While the results have shown promise, most of the literature focuses on algorithms and state-of-the-art (SOTA), while largely ignoring the practical aspects. In this paper we demonstrate our end-to-end log classification pipeline, Linnaeus. Besides showing the more traditional ML flow, we also demonstrate our solutions for adaptability and re-use, integration towards large scale software development processes, and how we cope with lack of labelled data. We hope Linnaeus can serve as a blueprint for, and inspire the integration of, various ML based solutions in other large scale industrial settings., Comment: 8 pages, 7 figures; to be included in ICSE/WAIN'21

Applications of the Extended Reality (XR) spectrum, a superset of Mixed, Augmented and Virtual Reality, are gaining prominence and can be employed in a variety of areas, such as virtual museums. Examples can be found in the areas of education, cultural heritage, health/treatment, entertainment, marketing, and more. The majority of computer graphics applications nowadays are used to operate only in one of the above realities. The lack of applications across the XR spectrum is a real shortcoming. There are many advantages resulting from this problem's solution. Firstly, releasing an application across the XR spectrum could contribute in discovering its most suitable reality. Moreover, an application could be more immersive within a particular reality, depending on its context. Furthermore, its availability increases to a broader range of users. For instance, if an application is released both in Virtual and Augmented Reality, it is accessible to users that may lack the possession of a VR headset, but not of a mobile AR device. The question that arises at this point, would be "Is it possible for a full s/w application stack to be converted across XR without sacrificing UI/UX in a semi-automatic way?". It may be quite difficult, depending on the architecture and application implementation. Most companies nowadays support only one reality, due to their lack of UI/UX software architecture or resources to support the complete XR spectrum. In this work, we present an "automatic reality transition" in the context of virtual museum applications. We propose a development framework, which will automatically allow this XR transition. This framework transforms any XR project into different realities such as Augmented or Virtual. It also reduces the development time while increasing the XR availability of 3D applications, encouraging developers to release applications across the XR spectrum.

Services computing can offer a high-level abstraction to support diverse applications via encapsulating various computing infrastructures. Though services computing has greatly boosted the productivity of developers, it is faced with three main challenges: privacy and security risks, information silo, and pricing mechanisms and incentives. The recent advances of blockchain bring opportunities to address the challenges of services computing due to its build-in encryption as well as digital signature schemes, decentralization feature, and intrinsic incentive mechanisms. In this paper, we present a survey to investigate the integration of blockchain with services computing. The integration of blockchain with services computing mainly exhibits merits in two aspects: i) blockchain can potentially address key challenges of services computing and ii) services computing can also promote blockchain development. In particular, we categorize the current literature of services computing based on blockchain into five types: services creation, services discovery, services recommendation, services composition, and services arbitration. Moreover, we generalize Blockchain as a Service (BaaS) architecture and summarize the representative BaaS platforms. In addition, we also outline open issues of blockchain-based services computing and BaaS., Comment: 15 pages, 5 figures

The value creation potential of the Internet of Things (IoT), that is the connection of arbitrary objects to the Internet, lies in the creation of business benefits through accessing and processing the circa 80 Zettabytes (1 ZB = 10^21 Bytes) of data produced by an estimated 40 billions of IoT endpoints (prognosis for 2025). This contribution derives and presents the information technology-related fundament and basis required to be able to reap this potential. Quantity and heterogeneity of the devices and machines especially encountered in the industry at large in the so-called industrial IoT (IIoT) require the use of a typically cloud-based IoT platform for logical concentration and more efficient management of the -- unavoidable in industry -- complexity. Stringent non-functional requirements especially regarding (low) latency, (high) bandwidth, access to large processing capacities, and security and privacy-related aspects necessitate the deployment of intermediary IoT gateways endowed with different capability sets in the edge continuum between IoT endpoints and the IoT platform in the cloud. This will be illustrated in the form of two use cases from corporate projects using a component architecture view point. Finally we argue that this classical concept of IoT projects needs to be strategically widened towards application integration (key word: IT/OT integration) and API management resulting in the coupling of a suitable integration and API management platforms to the IoT platform in order to use this end-to-end understanding of IoT/IIoT to fully leverage the innovation-stimulating and transformational character of IIoT and Industry 4.0., Comment: 38 Seiten, 13 Abbildungen, 4 Tabellen, Abk\"urzungsverzeichnis. This contribution is in the German language. Dieser Beitrag ist in Deutscher Sprache.

The problem of integrating multiple overlapping models and data is pervasive in engineering, though often implicit. We consider this issue of model management in the context of the electrical power grid as it transitions towards a modern 'Smart Grid.' We present a methodology for specifying, managing, and reasoning within multiple models of distributed energy resources (DERs), entities which produce, consume, or store power, using categorical databases and symmetric monoidal categories. Considering the problem of distributing power on the grid in the presence of DERs, we show how to connect a generic problem specification with implementation-specific numerical solvers using the paradigm of categorical databases., Comment: In Proceedings ACT 2019, arXiv:2009.06334

The long-standing aspiration for software reuse has made astonishing strides in the past few years. Many modern software development ecosystems now come with rich sets of publicly-available components contributed by the community. Downstream developers can leverage these upstream components, boosting their productivity. However, components evolve at their own pace. This imposes obligations on and yields benefits for downstream developers, especially since changes can be breaking, requiring additional downstream work to adapt to. Upgrading too late leaves downstream vulnerable to security issues and missing out on useful improvements; upgrading too early results in excess work. Semantic versioning has been proposed as an elegant mechanism to communicate levels of compatibility, enabling downstream developers to automate dependency upgrades. While it is questionable whether a version number can adequately characterize version compatibility in general, we argue that developers would greatly benefit from tools such as semantic version calculators to help them upgrade safely. The time is now for the research community to develop such tools: large component ecosystems exist and are accessible, component interactions have become observable through automated builds, and recent advances in program analysis make the development of relevant tools feasible. In particular, contracts (both traditional and lightweight) are a promising input to semantic versioning calculators, which can suggest whether an upgrade is likely to be safe., Comment: to be published as Onward! Essays 2020

In recent years, Semantic Web technologies have been increasingly adopted by researchers, industry and public institutions to describe and link data on the Web, create web annotations and consume large knowledge graphs like Wikidata and DBPedia. However, there is still a knowledge gap between ontology engineers, who design, populate and create knowledge graphs; and web developers, who need to understand, access and query these knowledge graphs but are not familiar with ontologies, RDF or SPARQL. In this paper we describe the Ontology-Based APIs framework (OBA), our approach to automatically create REST APIs from ontologies while following RESTful API best practices. Given an ontology (or ontology network) OBA uses standard technologies familiar to web developers (OpenAPI Specification, JSON) and combines them with W3C standards (OWL, JSON-LD frames and SPARQL) to create maintainable APIs with documentation, units tests, automated validation of resources and clients (in Python, Javascript, etc.) for non Semantic Web experts to access the contents of a target knowledge graph. We showcase OBA with three examples that illustrate the capabilities of the framework for different ontologies.

Authentication and authorization are two key elements of a software application. In modern day, OAuth 2.0 framework and OpenID Connect protocol are widely adopted standards fulfilling these requirements. These protocols are implemented into authorization servers. It is common to call these authorization servers as identity servers or identity providers since they hold user identity information. Applications registered to an identity provider can use OpenID Connect to retrieve ID token for authentication. Access token obtained along with ID token allows the application to consume OAuth 2.0 protected resources. In this approach, the client application is bound to a single identity provider. If the client needs to consume a protected resource from a different domain, which only accepts tokens of a defined identity provider, then the client must again follow OpenID Connect protocol to obtain new tokens. This requires user identity details to be stored in the second identity provider as well. This paper proposes an extension to OpenID Connect protocol to overcome this issue. It proposes a client-centric mechanism to exchange identity information as token grants against a trusted identity provider. Once a grant is accepted, resulting token response contains an access token, which is good enough to access protected resources from token issuing identity provider's domain., Comment: This work will be published in a conference proceeding

To help facilitate expertise in IoT technologies, NLeSC and SURF worked together on a project focusing on IoT applications and platforms. The information included in this case study show the results of NLeSC and SURF's investigation, examining different features offered by cloud and self-maintained IoT platforms with an overall summary of an IoT architecture., Comment: 11 pages, 7 figures, technical report

In Positional-Slotted Object-Applicative (PSOA) RuleML, a predicate application (atom) can have an Object IDentifier (OID) and descriptors that may be positional arguments (tuples) or attribute-value pairs (slots). PSOA RuleML explicitly specifies for each descriptor whether it is to be interpreted under the perspective of the predicate in whose scope it occurs. This predicate-dependency dimension refines the space between oidless, positional atoms (relationships) and oidful, slotted atoms (framepoints): While relationships use only a predicate-scope-sensitive (predicate-dependent) tuple and framepoints use only predicate-scope-insensitive (predicate-independent) slots, PSOA uses a systematics of orthogonal constructs also permitting atoms with (predicate-)independent tuples and atoms with (predicate-)dependent slots. This supports data and knowledge representation where a slot attribute can have different values depending on the predicate. PSOA thus extends object-oriented multi-membership and multiple inheritance. Based on objectification, PSOA laws are given: Besides unscoping and centralization, the semantic restriction and transformation of describution permits rescoping of one atom's independent descriptors to another atom with the same OID but a different predicate. For inheritance, default descriptors are realized by rules. On top of a metamodel and a Grailog visualization, PSOA's atom systematics for facts, queries, and rules is explained. The presentation and (XML-)serialization syntaxes of PSOA RuleML are introduced. Its model-theoretic semantics is formalized by extending the interpretation functions for dependent descriptors. The open-source PSOATransRun system realizes PSOA RuleML by a translator to runtime predicates, including for dependent tuples (prdtupterm) and slots (prdsloterm). Our tests show efficiency advantages of dependent and tupled modeling., Comment: 39 pages, 5 figures, 2 tables; updates for PSOATransRun 1.3.1 to 1.4.2; refined terminology and metamodel

Grid infrastructures that have provided wide integrated use of resources are becoming the de-facto computing platform for solving large-scale problems in science, engineering and commerce. In this evolution, desktop grid technologies allow the grid communities to exploit the idle cycles of pervasive desktop PC systems to increase the available computing power. In this paper we present DotGrid, a cross-platform grid software. DotGrid is the first comprehensive desktop grid software utilising Microsoft's .NET Framework in Windows-based environments and MONO .NET in Unix-class operating systems to operate. Using DotGrid services and APIs, grid desktop middleware and applications can be implemented conveniently. We evaluated our DotGrid's performance by implementing a set of grid-based applications., Comment: 20 pages, 14 figures

DotGrid platform is a Grid infrastructure integrated with a set of open and standard protocols recently implemented on the top of Microsoft .NET in Windows and MONO .NET in UNIX/Linux. DotGrid infrastructure along with its proposed protocols provides a right and solid approach to targeting other platforms, e.g., the native C/C++ runtime. In this paper, we propose a new file transfer protocol called DotDFS as a high-throughput distributed file transfer component for DotGrid. DotDFS introduces some open binary protocols for efficient file transfers on current Grid infrastructures. DotDFS protocol also provides mechanisms for multiple file streams to gain high-throughput file transfer similar to GridFTP protocol, but by proposing and implementing a new parallel TCP connection-oriented paradigm. In our LAN tests, we have achieved better results than Globus GridFTP implementation particularly in multiple TCP streams and directory tree transfers. Our LAN experiences in memory-to-memory tests show that DotDFS accesses to the 94% bottleneck bandwidth while GridFTP is accessing 91%. In LAN disk-to-disk tests, comparing DotDFS protocol with GridFTP protocol unveils a set of interesting and technical problems in GridFTP for both the nature of the protocol and its implementation by Globus. In the WAN experimental studies, we propose a new idea for analytical modeling of file transfer protocols like DotDFS inspired by sampling, experimentation and mathematical interpolation approaches. The cross-platform and open standard-based features of DotDFS provide a substantial framework for unifying data access and resource sharing in real heterogeneous Grid environments., Comment: 28 pages, 21 figures

In this paper we introduce and describe the highly concurrent xDFS file transfer protocol and examine its cross-platform and cross-language implementation in native code for both Linux and Windows in 32 or 64-bit multi-core processor architectures. The implemented xDFS protocol based on xDotGrid.NET framework is fully compared with the Globus GridFTP protocol. We finally propose the xDFS protocol as a new paradigm of distributed systems for Internet services, and data-intensive Grid and Cloud applications. Also, we incrementally consider different developmental methods of the optimum file transfer systems, and their advantages and disadvantages. The vision of this paper tries as possible to minimize the overhead concerned with the file transfer protocol itself and to examine optimal software design patterns of that protocol. In all disk-to-disk tests for transferring a 2GB file with or without parallelism, the xDFS throughput at minimum 30% and at most 53% was superior to the GridFTP., Comment: 25 pages, 20 figures

At this time, developers of research information systems are experimenting with new tools for research outputs usage that can expand the open access to research. These tools allow researchers to record research as annotations, nanopublications or other micro research outputs and link them by scientific relationships. If these micro outputs and relationships are shared by their creators publicly, these actions can initiate direct scholarly communication between the creators and the authors of the used research outputs. Such direct communication takes place while researchers are manipulating and organising their research results, e.g. as manuscripts. Thus, researchers come to communication before the manuscripts become traditional publications. In this paper, we discuss how this pre-publication communication can affect existing research practice. It can have important consequences for the research community like the end of publication as a communication instrument, the higher level of transparency in research, changes for the Open Access movement, academic publishers, peer-reviewing and research assessment systems. We analyse a background that exists in the economics discipline for experiments with the pre-publication communication. We propose a set of experiments with already existed and new tools, which can help with exploring the end of publication possible impacts on the research community., Comment: 8 pages, 3 figures

In the context of the emergent Web of Data, a large number of organizations, institutes and companies (e.g., DBpedia, Geonames, PubMed ACM, IEEE, NASA, BBC) adopt the Linked Data practices and publish their data utilizing Semantic Web (SW) technologies. On the other hand, the dominant standard for information exchange in the Web today is XML. Many international standards (e.g., Dublin Core, MPEG-7, METS, TEI, IEEE LOM) have been expressed in XML Schema resulting to a large number of XML datasets. The SW and XML worlds and their developed infrastructures are based on different data models, semantics and query languages. Thus, it is crucial to provide interoperability and integration mechanisms to bridge the gap between the SW and XML worlds. In this chapter, we give an overview and a comparison of the technologies and the standards adopted by the XML and SW worlds. In addition, we outline the latest efforts from the W3C groups, including the latest working drafts and recommendations (e.g., OWL 2, SPARQL 1.1, XML Schema 1.1). Moreover, we present a survey of the research approaches which aim to provide interoperability and integration between the XML and SW worlds. Finally, we present the SPARQL2XQuery and XS2OWL Frameworks, which bridge the gap and create an interoperable environment between the two worlds. These Frameworks provide mechanisms for: (a) Query translation (SPARQL to XQuery translation); (b) Mapping specification and generation (Ontology to XML Schema mapping); and (c) Schema transformation (XML Schema to OWL transformation)., Comment: This paper appears in "Semantic Hyper/Multi-media Adaptation: Schemes and Applications", Springer 2013. arXiv admin note: text overlap with arXiv:1311.0536

A constantly growing amount of information is available through the web. Unfortunately, extracting useful content from this massive amount of data still remains an open issue. The lack of standard data models and structures forces developers to create adhoc solutions from the scratch. The figure of the expert is still needed in many situations where developers do not have the correct background knowledge. This forces developers to spend time acquiring the needed background from the expert. In other directions, there are promising solutions employing machine learning techniques. However, increasing accuracy requires an increase in system complexity that cannot be endured in many projects. In this work, we approach the web knowledge extraction problem using an expertcentric methodology. This methodology defines a set of configurable, extendible and independent components that permit the reutilisation of large pieces of code among projects. Our methodology differs from similar solutions in its expert-driven design. This design, makes it possible for subject-matter expert to drive the knowledge extraction for a given set of documents. Additionally, we propose the utilization of machine assisted solutions that guide the expert during this process. To demonstrate the capabilities of our methodology, we present a real use case scenario in which public procurement data is extracted from the web-based repositories of several public institutions across Europe. We provide insightful details about the challenges we had to deal with in this use case and additional discussions about how to apply our methodology.

Recent developments in the commercial open source community have catalysed the use of Linux containers for scalable deployment of web-based applications to the cloud. Scientific software can be containerized with dependencies, configuration files, post-processing tools and even simulation results, referred to as containerized computing. This new approach promises to significantly improve sustainability, productivity and reproducibility. We present our experiences, technology, and future plans for open source containerization of software used to model particle and radiation beams. Vagrant is central to our approach, using Docker for cloud deployment and VirtualBox virtual machines for deployment to Mac OS and Windows computers. Our technology enables seamless switching between the desktop and the cloud to simplify simulation development and execution., Comment: 2 pages

A low carbon society aims at fighting global warming by stimulating synergic efforts from governments, industry and scientific communities. Decision support systems should be adopted to provide policy makers with possible scenarios, options for prompt countermeasures in case of side effects on environment, economy and society due to low carbon society policies, and also options for information management. A necessary precondition to fulfill this agenda is to face the complexity of this multi-disciplinary domain and to reach a common understanding on it as a formal specification. Ontologies are widely accepted means to share knowledge. Together with semantic rules, they enable advanced semantic services to manage knowledge in a smarter way. Here we address the European Emissions Trading System (EU-ETS) and we present a knowledge base consisting of the EREON ontology and a catalogue of rules. Then we describe two innovative semantic services to manage ETS data and information on ETS scenarios.

The internet is considered as the most extensive market in the world. To keep its gradual reputation, it must confront real problems that result from its distribution and from the diversity of the protocols used to insure communications. The Web service technology has diminished significantly the effects of distribution and heterogeneity, but there are several problems that weaken their performance (unavailability, load increase of use, high cost of CPU time...). Faced with this situation, we are forced to move in the direction of the substitution of web services. In this context, we propose an effective technique of substitution based on a new method of matching that allows detecting and expressing the matching between the web services pairwise by considering that each of them is ontology. Also, our method performs a discovery of the most similar web service to that to be replaced by using an efficient method of similarity measurement., Comment: 9 pages, 11 figures, 2 tables

Web services allow communication between heterogeneous systems in a distributed environment. Their enormous success and their increased use led to the fact that thousands of Web services are present on the Internet. This significant number of Web services which not cease to increase has led to problems of the difficulty in locating and classifying web services, these problems are encountered mainly during the operations of web services discovery and substitution. Traditional ways of search based on keywords are not successful in this context, their results do not support the structure of Web services and they consider in their search only the identifiers of the web service description language (WSDL) interface elements. The methods based on semantics (WSDLS, OWLS, SAWSDL...) which increase the WSDL description of a Web service with a semantic description allow raising partially this problem, but their complexity and difficulty delays their adoption in real cases. Measuring the similarity between the web services interfaces is the most suitable solution for this kind of problems, it will classify available web services so as to know those that best match the searched profile and those that do not match. Thus, the main goal of this work is to study the degree of similarity between any two web services by offering a new method that is more effective than existing works., Comment: 7 pages, 4 figures, 8 tables, International Journal of Advanced Computer Science and Applications (IJACSA),Vol. 5, No. 8, 2014

HPC environments have traditionally been designed to meet the compute demand of scientific applications and data has only been a second order concern. With science moving toward data-driven discoveries relying more on correlations in data to form scientific hypotheses, the limitations of HPC approaches become apparent: Architectural paradigms such as the separation of storage and compute are not optimal for I/O intensive workloads (e.g. for data preparation, transformation and SQL). While there are many powerful computational and analytical libraries available on HPC (e.g. for scalable linear algebra), they generally lack the usability and variety of analytical libraries found in other environments (e.g. the Apache Hadoop ecosystem). Further, there is a lack of abstractions that unify access to increasingly heterogeneous infrastructure (HPC, Hadoop, clouds) and allow reasoning about performance trade-offs in this complex environment. At the same time, the Hadoop ecosystem is evolving rapidly and has established itself as de-facto standard for data-intensive workloads in industry and is increasingly used to tackle scientific problems. In this paper, we explore paths to interoperability between Hadoop and HPC, examine the differences and challenges, such as the different architectural paradigms and abstractions, and investigate ways to address them. We propose the extension of the Pilot-Abstraction to Hadoop to serve as interoperability layer for allocating and managing resources across different infrastructures. Further, in-memory capabilities have been deployed to enhance the performance of large-scale data analytics (e.g. iterative algorithms) for which the ability to re-use data across iterations is critical. As memory naturally fits in with the Pilot concept of retaining resources for a set of tasks, we propose the extension of the Pilot-Abstraction to in-memory resources., Comment: Submitted to HPDC 2015, 12 pages, 9 figures

Historical (Stressed-) Value-at-Risk ((S)VAR), and Expected Shortfall (ES), are widely used risk measures in regulatory capital and Initial Margin, i.e. funding, computations. However, whilst the definitions of VAR and ES are unambiguous, they depend on input distributions that are data-cleaning- and Data-Model-dependent. We quantify the scale of these effects from USD CDS (2004--2014), and from USD interest rates (1989--2014, single-curve setup before 2004, multi-curve setup after 2004), and make two standardisation proposals: for data; and for Data-Models. VAR and ES are required for lifetime portfolio calculations, i.e. collateral calls, which cover a wide range of market states. Hence we need standard, i.e. clean, complete, and common (i.e. identical for all banks), market data also covering this wide range of market states. This data is historically incomplete and not clean hence data standardization is required. Stressed VAR and ES require moving market movements during a past (usually not recent) window to current, and future, market states. All choices (e.g. absolute difference, relative, relative scaled by some function of market states) implicitly define a Data Model for transformation of extreme market moves (recall that 99th percentiles are typical, and the behaviour of the rest is irrelevant). Hence we propose standard Data Models. These are necessary because different banks have different stress windows. Where there is no data, or a requirement for simplicity, we propose standard lookup tables (one per window, etc.). Without this standardization of data and Data Models we demonstrate that VAR and ES are complex derivatives of subjective choices., Comment: 22 pages, 5 figures, 1 table

Most Java applications, including web based ones, follow the 3-tier architecture. Although Java provides standard tools for tier-to-tier interfaces, the separation of the tiers is usually not perfect. E.g. the database interface, JDBC, assumes that SQL statements are issued from the application server. Similarly, in web based Java applications, HTML code is assumed to be produced by servlets. In terms of syntax, this turns Java source code into mixtures of languages: Java and SQL, Java and HTML. These language mixtures are difficult to read, modify, and maintain. In this paper we examine criteria and methods to achieve a good separation of the 3 tiers and propose a technique to provide a clean separation. Our proposed technique requires an explicit Interface and Data Definitions. These allow isolation of the back-end, application server, and front-end development. The Definitions also enable application design in terms of aggregated data structures. As a result significant amounts of auxiliary code can be generated from the Definitions, enabling the developers to concentrate on the business logic. By and large the proposed approach greatly facilitates development and maintenance, and overall improves the quality of the products., Comment: 9 pages with code examples

For the last two decades, software architecture has been adopted as one of the main viable solutions to address the ever-increasing demands in the design and development of software systems. Nevertheless, the rapidly growing utilization of communication networks and interconnections among software systems have introduced some critical challenges, which need to be handled in order to fully unleash the potential of these systems. In this respect, Ultra-Large-Scale (ULS) systems, generally considered as a system of systems, have gained considerable attention, since their scale is incomparable to the traditional systems. The scale of ULS systems makes drastic changes in various aspects of system development. As a result, it requires that we broaden our understanding of software architectures and the ways we structure them. In this paper, we investigate the lack of an architectural maturity model framework for ULS system interoperability, and propose an architectural maturity model framework to improve ULS system interoperability.

The paper describes the need for and goals of tool-integration within software development processes. In particular we focus on agile software development but are not limited to. The integration of tools and data between the different domains of the process is essential for an efficient, effective and customized software development. We describe what the next steps in the pursuit of integration are and how major goals can be achieved. Beyond theoretical and architectural considerations we describe the prototypical implementation of an open platform approach. The paper introduces platform apps and a functionality store as general concepts to make apps and their functionalities available to the community. We describe the implementation of the approach and how it can be practically utilized. The description is based on one major use case and further steps are motivated by various other examples.

The Web of Data is an open environment consisting of a great number of large inter-linked RDF datasets from various domains. In this environment, organizations and companies adopt the Linked Data practices utilizing Semantic Web (SW) technologies, in order to publish their data and offer SPARQL endpoints (i.e., SPARQL-based search services). On the other hand, the dominant standard for information exchange in the Web today is XML. The SW and XML worlds and their developed infrastructures are based on different data models, semantics and query languages. Thus, it is crucial to develop interoperability mechanisms that allow the Web of Data users to access XML datasets, using SPARQL, from their own working environments. It is unrealistic to expect that all the existing legacy data (e.g., Relational, XML, etc.) will be transformed into SW data. Therefore, publishing legacy data as Linked Data and providing SPARQL endpoints over them has become a major research challenge. In this direction, we introduce the SPARQL2XQuery Framework which creates an interoperable environment, where SPARQL queries are automatically translated to XQuery queries, in order to access XML data across the Web. The SPARQL2XQuery Framework provides a mapping model for the expression of OWL-RDF/S to XML Schema mappings as well as a method for SPARQL to XQuery translation. To this end, our Framework supports both manual and automatic mapping specification between ontologies and XML Schemas. In the automatic mapping specification scenario, the SPARQL2XQuery exploits the XS2OWL component which transforms XML Schemas into OWL ontologies. Finally, extensive experiments have been conducted in order to evaluate the schema transformation, mapping generation, query translation and query evaluation efficiency, using both real and synthetic datasets., Comment: To appear in World Wide Web Journal (WWWJ), Springer 2013

To supervise and guarantee a network security, the administrator uses different security components, such as firewalls, IDS and IPS. For a perfect interoperability between these components, they must be configured properly to avoid misconfiguration between them. Nevertheless, the existence of a set of anomalies between filtering rules and alerting rules, particularly in distributed multi-component architectures is very likely to degrade the network security. The main objective of this paper is to check if a set of security components are interoperable. A case study using a firewall and an IDS as examples will illustrate the usefulness of our approach., Comment: Security component, relevancy, misconfigurations detection, interoperability cheking, formal correction,formal verification, projection, IDS, Firewall

Commercially available business process management systems (BPMS) still suffer to support organizations to enact their business processes in an effective and efficient way. Current BPMS, in general, are based on BPMN 2.0 and/or BPEL. It is well known, that these approaches have some restrictions according modeling and immediate transfer of the model into executable code. Recently, a method for modeling and execution of business processes, named subject-oriented business process management (S-BPM), gained attention. This methodology facilitates modeling of any business process using only five symbols and allows direct execution based on such models. Further on, this methodology has a strong theoretical and formal basis realizing distributed systems; any process is defined as a network of independent and distributed agents - i.e. instances of subjects - which coordinate work through the exchange of messages. In this work, we present a framework and a prototype based on off-the-shelf technologies as a possible realization of the S-BPM methodology. We can prove and demonstrate the principal architecture concept; these results should also stimulate a discussion about actual BPMS and its underlying concepts.

Nowadays, information management systems deal with data originating from different sources including relational databases, NoSQL data stores, and Web data formats, varying not only in terms of data formats, but also in the underlying data model. Integrating data from heterogeneous data sources is a time-consuming and error-prone engineering task; part of this process requires that the data has to be transformed from its original form to other forms, repeating all along the life cycle. With this report we provide a principled overview on the fundamental data shapes tabular, tree, and graph as well as transformations between them, in order to gain a better understanding for performing said transformations more efficiently and effectively., Comment: 9 pages

The following is an outline of possible strategies in using semantic web techniques and math with regard to environmental issues. The article uses concrete examples and applications and provides partially a rather basic treatment of semantic web techniques and math in order to adress a broader audience., Comment: 17 pages, 2 figures

Multiscale and multiphysics applications are now commonplace, and many researchers focus on combining existing models to construct combined multiscale models. Here we present a concise review of multiscale applications and their source communities. We investigate the prevalence of multiscale projects in the EU and the US, review a range of coupling toolkits they use to construct multiscale models and identify areas where collaboration between disciplines could be particularly beneficial. We conclude that multiscale computing has become increasingly popular in recent years, that different communities adopt very different approaches to constructing multiscale simulations, and that simulations on a length scale of a few metres and a time scale of a few hours can be found in many of the multiscale research domains. Communities may receive additional benefit from sharing methods that are geared towards these scales., Comment: 12 pages, 6 figures, 2 tables. Accepted by CiSE (with a constrained number of references; these were put in a separate literature list)

The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to unify many sources of structured knowledge and answer complex queries. However, the efficient alignment of large-scale knowledge bases still poses a considerable challenge. Here, we present Simple Greedy Matching (SiGMa), a simple algorithm for aligning knowledge bases with millions of entities and facts. SiGMa is an iterative propagation algorithm which leverages both the structural information from the relationship graph as well as flexible similarity measures between entity properties in a greedy local search, thus making it scalable. Despite its greedy nature, our experiments indicate that SiGMa can efficiently match some of the world's largest knowledge bases with high precision. We provide additional experiments on benchmark datasets which demonstrate that SiGMa can outperform state-of-the-art approaches both in accuracy and efficiency., Comment: 10 pages + 2 pages appendix; 5 figures -- initial preprint

Mapping complex metadata structures is crucial in a number of domains such as data integration, ontology alignment or model management. To speed up that process automatic matching systems were developed to compute mapping suggestions that can be corrected by a user. However, constructing and tuning match strategies still requires a high manual effort by matching experts as well as correct mappings to evaluate generated mappings. We therefore propose a self-configuring schema matching system that is able to automatically adapt to the given mapping problem at hand. Our approach is based on analyzing the input schemas as well as intermediate matching results. A variety of matching rules use the analysis results to automatically construct and adapt an underlying matching process for a given match task. We comprehensively evaluate our approach on different mapping problems from the schema, ontology and model management domains. The evaluation shows that our system is able to robustly return good quality mappings across different mapping problems and domains., Comment: 10 Pages

Interface adapters allow applications written for one interface to be reused with another interface without having to rewrite application code, and chaining interface adapters can significantly reduce the development effort required to create the adapters. However, interface adapters will often be unable to convert interfaces perfectly, so there must be a way to analyze the loss from interface adapter chains in order to improve the quality of interface adaptation. This paper describes a probabilistic approach to analyzing loss in interface adapter chains, which not only models whether a method can be adapted but also how well methods can be adapted. We also show that probabilistic optimal adapter chaining is an NP-complete problem, so we describe a greedy algorithm which can construct an optimal interface adapter chain with exponential time in the worst case., Comment: 20 pages, 2 figures

The Chem2Bio2RDF portal is a Linked Open Data (LOD) portal for systems chemical biology aiming for facilitating drug discovery. It converts around 25 different datasets on genes, compounds, drugs, pathways, side effects, diseases, and MEDLINE/PubMed documents into RDF triples and links them to other LOD bubbles, such as Bio2RDF, LODD and DBPedia. The portal is based on D2R server and provides a SPARQL endpoint, but adds on few unique features like RDF faceted browser, user-friendly SPARQL query generator, MEDLINE/PubMed cross validation service, and Cytoscape visualization plugin. Three use cases demonstrate the functionality and usability of this portal., Comment: 8 pages, 10 figures

In this paper we report on our re-engineering effort to refactor and unify two somewhat disjoint Java distributed middleware technologies -- Jini and JMS -- used in the implementation of the Demand Migration System (DMS). In doing so, we refactor their parent Demand Migration Framework (DMF), within the General Intensional Programming System (GIPSY). The complex Java-based GIPSY project is used to investigate on the intensional and hybrid programming paradigms., Comment: 16 pages; 9 figures; an index. v4 includes significant updates and a version was submitted to PPPJ'11