dataesr/scientific-paragraphs-categorization huggingface dataset:
F. RQ6: Missing Links In Figures  9  and 10  we detail two categories of missing links that Relink fails to recover. The examples are presented as used in the testing dataset where we had removed any explicit reference to the bug reports so as to assess the core algorithm of ReLink. The first example highlights the fact that ReLink's features of links could be augmented to take into account mappings between bug reporter name and patch acknowledgement texts. Indeed, although the change log and bug report description texts in Figure  9  are not similar, we can infer a link, based on the date, report metadata and the acknowledgement in change log. Figure  10  however details a different miss by ReLink. Although there exist text similarity between the change log and the bug report, and a mapping between the bug owner (i.
G. RQ7: Extraneous Links The precision of ReLink results is usually very high as detailed in Sections V-A, V-B and V-C. This, as the authors have suggested in their paper  [15] , is largely due to the use of different heuristics through a number of features of links. Nonetheless, we have found that the stdcxx program involves datasets that make ReLink's precision drop significantly. Manual investigation of the false positives for this program has exposed two bug reports, namely STDCXX-11 and STDCXX-8, for which ReLink mistakenly finds links to several commits. Figure  11  shows an excerpt of STDCXX-11. In the bug reports extraneously linked we observe that the bug reporter has directly dumped his code, his compilation command lines and even gdb output. The generality of the terms appearing in the text may have lead ReLink to wrongly assign many links to the bug.
H. Threats to Validity Our empirical evaluation bears some threats to both internal and external validity. The main threats to internal validity are related to the process of building the benchmark dataseti. We have tried to minimize this threat by our assessment of the soundness and completeness of the links extracted from the JIRA-based issue tracking system. Threats to external validity refers to the generalizability of our findings. We minimize this threat by considering a wide range of projects of various domains written in different programming languages. Another threat lies in the use of only JIRA as a bug tracking system. To improve this study, there is a need to evaluate other bug linking tools including tools that do not use data-mining, machine learning and information retrieval techniques.
A. Bug Linking There have been a number of studies that propose various techniques to either identify bug reports or link bug reports to the revisions that fix them. Antoniol et al. propose a technique to classify if a change request is a request for enhancement or a bug report  [25]. Tian et al. propose a technique that detects if a revision is a bug fixing revision or not  [26]. Bird et al. propose a technique named LINKSTER that could be used to aid developers in linking bug reports to the revisions that fix them  [14]. Their approach is semiautomated. Sureka et al. have used a probabilistic approach based on the Fellegi-Model for traceability link to recover bug links  [12]. Wu et al. have recently proposed ReLink which is an information-retrieval based technique  [15]. In this study, we evaluate the effectiveness of ReLink in several dimensions and compare it with existing work on information retrieval that has been applied to software traceability studies  [17] -  [19].
VII. CONCLUSION AND FUTURE WORK Bug linking is an important problem which, if thoroughly addressed, will significantly improve software maintenance and evolution studies and enhance capabilities of various research tools for improving defect prediction and fix recommendations. Such studies are indeed largely discussed in the literature as useful for improving the quality of software. In our work we provide a clean benchmark dataset for evaluating bug linking tools. We have applied several research questions to the state of the art tool, namely ReLink, to assess its effectiveness on recovering missing links. The results of our experiments show that, overall, ReLink achieves very good precisions, over 90%, for some programs, but delivers lesser recall rates, dropping below 10%. The F-measure results in our various scenarios show that there is room for improvement in the area of bug linking.
This paper introduces a systemic framework to bring a comprehensive and equipped approach of the service innovation process to companies. To respect the paper format, we only present some screenshots but the session will be the occasion of a case study demonstration. Section 2 presents the service innovation  [6]  approach as a holistic and opened  [7]  but still handmade practice. It starts from the general Double Diamond diagram and proposes a framework that deals with the necessary construction of a long term strategy. Section 3 details two main components of this framework: Knowledge and Tools. It gives an overview of the exiting tools and presents Umagus, a dedicated software. It also introduces the two other components: Places and People. Finally, Section 4 concludes and gives some perspectives.
Existing Tool-related Works to Support some Service Design Phases Few works exist on the capture and semi-automation of required elements. Most of them propose creative methodologies and toolkits but few works really speak about a technological and complete solution. However, it is essential to capture/accumulate a lot of service design knowledge and data within a specific database to envisage the comparison and analysis of designed services or service design processes. We can cite an Austrian initiative called myServiceFellow  [9]  and stemming from the results of a research project of the Management Center Innsbruck -MCI Tourism, financed by the Tyrolean science fund and the hardware kindly supported by mobilkom Austria. myServiceFellow was a mobile ethnography application for smartphone.
It allowed the capture of customer journeys and their enrichment (photo, video, voice). We can also quote the well-known Swiss works on the automation of Business Model Canvas modeling/use  [10]  through an application available on iTunes. Another interesting project is the European project MEPSS (Methodologies for Product-Service System) that has worked on a web-based tool for the development of product-service systems. MEPSS proposed a modular approach to guide companies in the process of "developing and implementing a successful and sustainable productservice system"  [11]. The Creative Design Institute of the University of Sungkyunkwan is also working on intelligent tutoring systems that aim to investigate computer-based aid to product-service systems design. This Korean team is developing a software primarily based on the service blueprint  [12].
Umagus, a Way to Scale Up and Automate the Overall Service Design Process As part of a research and development project on the transformation process through services, and in order to implement the second building block of our framework (softwares and tools) which is still not completely addressed, we have worked on the conception of a specific tool and its database called Umagus (figure  4 ). Umagus aims to scale up and shift from the current handmade approach to an industrialized approach with a structured and semi-automated process. In its first version, it is a web-based platform to support the innovation process and keep the value of its findings and productions. Technologically speaking, it has been developed as a SaaS platform with a graph-database given the nature of the studied phenomena as heterogeneous and interconnected entities  [14]  and given the few constraints of this kind of database which does not require joint relationships between pre-established tables and which can store a huge amount of data.
Umagus is a comprehensive "user experience-oriented" solution for services innovation and management. It enables to capture, organize and visualize "a large amount of information about the targeted company, its value chain, its activities or its users' profiles and usages"  [15]. Umagus also facilitates inter-trade co-creation. Indeed, service design is natively a co-design approach. Thanks to collaborative and versioning functionalities, Umagus manages the cooperation of multiple participants in a project, allowing them to share their individual production and interact over it in a synchronous or asynchronous way, but also to think about and produce directly together. It improves the flow of data between distant stakeholders and helps them to appropriate new methods and models. It is thus a good solution to capture, store and visualize complex systems and to facilitate calculations on these systems thanks to algorithms.
Key functionalities have already been implemented, tested, validated and used by some companies: service innovation projects management, heterogeneous data and knowledge management (user, market, aso), key methods and models integration and enrichment (persona, service journey with key stages and moments of truth, service blueprint, storyboarding…), dashboards generation (for services managers), service visualizations for different stakeholders, technology or product functionalities specifications from a service system perspective. Umagus aims to become a key help for companies and service designers to do projects quickly and to don't lose any data and any value from the findings and productions of the service innovation process. But, to go further than the functionalities, our R&D project now focuses on analysis and comparison of all the data that are generated by service design projects and capitalized into Umagus.
We have now to pursue its use to feed the database and to integrate new kinds of analysis and calculation to make it more automated, collaborative and robust. Other current works concern the deployment and test of dedicated places. These perspectives and their implementation will be the objects of further publications. An oral presentation would be the occasion to concretely demonstrate our works through a simple service design case. Finally, it seems also interesting to consider Umagus and the overall framework we conceived as possible supports for service design education since this field courses and programs are still under development and will benefit from it.
It will allow researchers to integrate in the same "triple store" database, description of FLOSS artifacts or actors with variable structures, still relying on common semantics and a harmonized URI nomenclature that reflects the origin of these resources. But for FLOSS developers alike, these semantic Web Techniques should offer potential interesting applications, in particular to create new global services that need to interconnect different heterogenous project tools  [4]. As an illustration, we can imagine a new "global bug tracking system" that aims at correlating similar bug reports filed in different Linux distributions. It can be helpful to offer better support responses, allowing navigation between reports which may have been related to each-other previously. Such a system will require to interface to lots of different bugtracker APIs.
Linked Data Representation of Debian Source Packages We have improved the Debian PTS to add the generation of RDF descriptions for all Debian source packages. Every Debian source package, which used to have an HTML page accessible at a URL like http://packages. qa. debian. org/apache2, now has a corresponding RDF document available at the same URL, either as Turtle  [1]  or RDF/XML format. Applying a common Linked Data pattern, HTTP clients will be redirected automatically to the proper HTML or RDF document depending on the content-type that is requested by the HTTP client, so that the same URL can be used to represent both the human-readable HTML pages or the machine-processable RDF document. Thus, each package in Debian can be identified on the Semantic Web with a unique URI like http://packages.
Deployment on debian. org The authors have deployed the XSLT stylesheets generating these RDF documents on the PTS service of the Debian project  12. Alongside the HTML pages of the PTS, the RDF descriptions of Debian source packages are thus refreshed every time new revisions will appear in the Debian archive. A full RDF dump of all the meta-data is also available to Debian project members  13. It contains around 2. 1 million triples at the time of writing.
DOAP Published by FLOSS Directories A number of projects maintain public DOAP descriptions of their programs, or other RDF descriptions of meta-data about the releases they produce. They may be interested in complementing descriptions with ADMS. SW, or could offer sources of descriptions that could be interlinked with the ones produced by the Debian PTS. A quick survey conducted by the authors showed the following sources 14  : -Gnome project -Apache project -PyPI (Python Package Index) directory -CPAN (Comprehensive Perl Archive Network) directory Listing 2 shows an excerpt of the DOAP description of the Apache Geronimo project as published by this project  15  , and converted to Turtle for readability. A quick review of samples from these sources showed a lack of consensus on the use of certain meta-data, and that URIs adopted to reference the same projects or programs tend to vary, even for doap:homepage URLs (a great portion of these documents are manually crafted, or projects may have various pages that can be considered their homepage, in particular when the project is not hosted on its own top level domain).
Projects Hosted on FusionForge Forges An ADMS. SW plugin for the FusionForge 5. 2 software development forge has also been created by one of the authors  16  , in order to allow the description of projects hosted on FusionForge based development forges. It may be complemented by another FusionForge plugin providing FOAF profiles  [12]  for project participants, which can enrich the Linked Data representations. The plugin is still under active development, and targetted at a post 5. 2 release of FusionForge, so it will take a certain time until it is deployed on public forges hosting FLOSS projects 17.
Large Scale Perspective The RDF-ization of the Debian PTS has just started. Next steps will include modelling of relations between source and binary packages. These will probably require extending ADMS. SW or integrating complementary ontologies. When deployments of ADMS. SW have been made on software forges (like FusionForge servers), software catalogues (like Joinup) or in other FLOSS distributions, it will become one of the tools allowing automated traceability at large scale of FLOSS releases and associated artefacts, by interlinking their Linked Data resources. Some interlinking of security advisories, patches, or bug reports (for instance combined with the OSLC-CM standard 22 ) should then be easier, and diminish manual intervention needs, for the benefits of all actors along the FLOSS production chains.
Future Developments We believe the current early result can be a driving force for more deployments around ADMS. SW as a standardization core. However there seems to be a reluctance in adopting RDF in FLOSS projects, to some extent, maybe linked to an erronous perception that RDF must be expressed as XML (which is certainly not the case, with representations of the RDF model like Turtle  [1] , which has been adopted as a default for the Debian PTS). We can foresee that when novel inter-project "killer" applications making use of such Linked Data will have been developed, will it be possible to convince FLOSS projects that adoption of Linked Data standards descriptions can really be for their own benefit. It is likely that even when lots of Linked Data descriptions of FLOSS artifacts are made available by major FLOSS projects, achieving effective interoperability will require many implementation efforts, far beyond a single actor's reach.
Conclusion We have presented a first significant deployment of an ADMS. SW 1. 0 implementation, which illustrates the potential for interlinking large sets of FLOSS project descriptions on the Semantic Web. ADMS. SW allows us to describe relations between projects, programs and their releases so that such entities become part of the Linked Open Data "cloud". In  [4] , we envisioned some novel uses of Linked Data representations of FLOSS development artefacts, both for software engineers and researchers observing their efforts. But to achieve the full potential of that approach, the Linked Data representations must be semantically interoperable, authoritative, accurate, and using standard naming schemes for the same resources. We have achieved a first concrete step in this direction, through the current results for the Debian PTS.
The authors thank the ICARE Data and Services Center team for providing access to the PARASOL data and for general assistance and development support. CIMEL sunphotometers calibration was performed at LOA using AERONET-EUROPE calibration center, supported by ACTRIS (European Union Seventh Framework Program (FP7/2007-2013) under grant agreement No. 262254). The authors are grateful to T. Lapyonok for the help in processing data using new algorithm developed by ODiscussion Paper | Discussion Paper | Discussion Paper | long-range transfer monitoring and regional ecological problems solution: field validation of retrieval techniques, Opt. Pur. y Apl.
Background: Constant technological advances have allowed scientists in biology to migrate from conventional single-omics to multi-omics experimental approaches, challenging bioinformatics to bridge this multi-tiered information. Ongoing research in renal biology is no exception. The results of large-scale and/or high throughput experiments, presenting a wealth of information on kidney disease are scattered across the web. To tackle this problem, we recently presented the KUPKB, a multi-omics data repository for renal diseases. Results: In this article, we describe KUPNetViz, a biological graph exploration tool allowing the exploration of KUPKB data through the visualization of biomolecule interactions. KUPNetViz enables the integration of multi-layered experimental data over different species, renal locations and renal diseases to protein-protein interaction networks and allows association with biological functions, biochemical pathways and other functional elements such as miRNAs.
g. systems functioning in the same tissue/organ/similar disease situation) and eventually design new experiments for hypothesis validation. The renal biology field is facing similar problems. Although kidney diseases have been extensively studied in different species (i. e. human, mouse, rat), this wealth of information remains hidden across several layers of public data and/or literature repositories. Although considerable effort has been devoted in aggregating data from several resources  [5] [6] [7] , the resulting databases fail to meet the multi-omics attribute and remain dispersed across the web. To address this problem, we developed the Kidney and Urinary Pathway Knowledge Base (KUPKB)  [8] , a publicly available repository which organizes an important amount of existing knowledge regarding renal tissue, cell and disease categorization, using Semantic Web technologies  [9].
The KUPKB can be queried through the user-friendly iKUP browser,  [8] , accessible at http://www. kupkb. org. The iKUP comprises a powerful tool in terms of speed, selectivity and descriptive power. Nevertheless, its nature restricts the user to viewing the query results in tabular format, only skimming the surface of the rich interconnected data otherwise available in the KUPKB. In addition, although it succeeds in displaying findings hidden in scattered repositories, such as the expression of a set of genes under a very specific combination of kidney tissue, cellular type and disease, it remains unable to map this information to interaction networks available as background information and in a multiple species manner. The value of biological network representations has been extensively analyzed in bioinformatics and systems biology literature  [10, 11].
Some important aspects include the ability to capture fixed snapshots of cellular states  [12]  otherwise hidden in tables, to infer functional associations  [13] , to reduce complexity by combining protein interaction, gene expression and metabolic profiles in a single image  [14] , and perform pattern recognition in a network snapshot  [15]. In this article, we describe KUPNetViz, an interactive biological network querying and visualization application. Its main purpose is to assist renal scientists to extend their research by providing an alternative KUPKB data image depicting interactions among the queried molecules and their neighbors, coupled with functional and biochemical pathway annotation in both a species dependent and independent manner. The main tasks supported and promoted by KUPNetViz are: i) the display, exploration and manipulation of general proteinprotein interaction as well as functional and biochemical pathway association networks for a number of widely studied mammalian species, ii) the transformation of these general networks to kidney specific networks through their association with related gene/protein/ miRNA expression datasets, iii) the mining of possibly hidden relationships among co-regulated and/or directly interacting ("neighboring") entities under several combinations of kidney anatomies and/or disease models and iv) the extrapolation of both expression data and network interactions across different diseases, anatomies but also different species facilitating the quick formulation and screening of biological hypotheses and the design of new experiments.
General architecture The KUPNetViz is a web application developed using PHP for server side programming and jQuery (http:// www. jquery. org) coupled with static HTML for the client side. The backend of the application is a MySQL database hosting the background knowledge used to build the mappings among entities, the network interactions, annotation data and properly parsed experimental data that make up the most important part of the KUPKB. The backend database can be very easily updated and maintained as it can be rebuilt in an automated fashion with a single one-line command, through a series of Perl scripts that download, parse and import KUPKB data and the background knowledge resources into the schema, using a wrapper script and a simple YAML (http://www. yaml. org) configuration file.
Background knowledge The background knowledge integrated in KUPNetViz from KUPKB has been extensively described elsewhere  [8, 18]. Briefly, gene, protein and miRNA annotations are derived from NCBI gene, UniProt  [19]  and Ensembl  [20] , and Microcosm  [21]  respectively. For the mappings among the various biological entities and accession numbers, we used the mapping files provided by NCBI (ftp. ncbi. nlm. nih. gov) as well as the Biomart web services  [22]. Files provided by NCBI were also used for the mapping of genes to their respective GO terms. Molecule interactions are extracted from the STRING protein-protein interaction database  [23]  by parsing publicly available flat files and miRNA to gene interactions are extracted from the Microcosm miRNA target files (http://www. ebi. ac.
Data input The user can query KUPNetViz using a variety of molecule identification types, including HUGO gene symbols (e. g. "CALR", but the search is case-insensitive), Entrez accession numbers (e. g. 811), UniProt accessions (e. g. P27797), Ensembl gene and protein IDs (e. g. ENSG00000179218 or ENSP00000320866), miRBase accessions (e. g. hsa-miR-362-3p) or by simple free text (e. g. "calreticulin"). All the above accessions and search terms are equivalent to calreticulin and can be used in mixed identification types. Four different mammalian species are currently supported, namely human, mouse, rat and dog. A strong feature of KUPNetViz, which is rare among other application of the same kind, is the ability to query multiple species for protein-protein network reconstruction at the same time.