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Academic literature on the topic 'Model of provenance'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Model of provenance"

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Stojnić, Srđan, S. Orlović, D. Ballian, M. Ivankovic, M. Šijačić-Nikolić, A. Pilipović, S. Bogdan, et al. "Provenance by site interaction and stability analysis of European beech (Fagus sylvatica L.) provenances grown in common garden experiments." Silvae Genetica 64, no. 1-6 (December 1, 2015): 133–47. http://dx.doi.org/10.1515/sg-2015-0013.

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AbstractFifteen provenances of European beech (Fagus sylvatica L.) were evaluated for stability and adaptability by height growth at four test sites in Bosnia and Herzegovina (1), Croatia (1) and Serbia (2). Provenance trials were established in spring 2007 by planting 2- and 3-yearold seedlings and arranged in a randomized complete block design. The data from seven 6- year-old and eight 5-year-old provenances were obtained in 2009 and analyzed separately. Finlay and Wilkinson’s regression analysis and Additive main effects and multiplicative interaction model (AMMI model) were used to assess provenance by site interaction (P × S) and to identify beech provenances that have high and stable performance in different environments, at the juvenile stage of development. Analysis of variance showed that effects of provenance, site, and P×S interaction are highly significant (p<0.001) in both age groups. Linear regression model evidenced that most of the provenances had regression coefficients not significantly different from unity (b=1.0), except for provenances Sjeverni Dilj Caglinski (HR24) and Vranica-Bistrica (BA59). The partitioning of the total sum of squares (SS) exhibited that the site effect was the predominant source of variation in both age groups of provenances (50.7% and 38.5%, respectively). Additionally, regression analysis explained 15.8% and 33.2% of provenance by site interaction terms, in provenances age six and five years, respectively, while the AMMI analysis accounted for 62.2% and 78.7% in P×S interaction. The results of AMMI showed that the first principal component (PC1) was statistically significant in both age groups. Adaptability and stability of provenances to the test sites were estimated with AMMI1 and AMMI2 biplots. Provenance Sjeverni Dilj Caglinski (HR24) showed constant performance over tested sites, characterizing with aboveaverage height growth at low yielding environments. Provenances HR25 and BA61 showed the opposite type of adaptation, being adapted to high yielding sites. Provenance Valkonya (HU42) was characterized by IPCA1 score close to zero and above average mean height growth, suggesting general adaptation to the tested environments. The implication of P×S was discussed in light of impact of climate change on beech and selection of most suitable provenances for future reforestation programs.
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Funda, T., M. Lstibůrek, J. Klápště, I. Permedlová, and J. Kobliha. "Addressing spatial variability in provenance experiments exemplified in two trials with black spruce." Journal of Forest Science 53, No. 2 (January 7, 2008): 47–56. http://dx.doi.org/10.17221/2135-jfs.

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Two exemplary black spruce (<i>Picea mariana</i> [Mill.] B.S.P.) provenance trials were analyzed using traditional and spatial techniques. The objective was to find out possible differences between these approaches in terms of both the resulting fit-statistics and the estimated mean heights of provenances. Further, the spatial model was consequently adjusted to treat global and extraneous sources of variation. As expected, models incorporating spatial variation provided a better fit to the data. Consequently, there was also a noticeable shift in ranking of individual provenances, which has an important implication for the interpretation of provenance experiments results. Problems associated with the analysis of traditional randomized block designs in forestry research are discussed.
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Lavadinovic, Vera, Ljubinko Rakonjac, Danijela Djunisijevic-Bojovic, Zoran Miletic, and Filip Jovanovic. "Variability of potassium concentration in the needles of Douglas-fir provenances." Bulletin of the Faculty of Forestry, no. 120 (2019): 97–116. http://dx.doi.org/10.2298/gsf1920097l.

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Douglas-fir is one of the most common conifer species in the forest plantations of Europe. The provenance test model is based on the analysis of the properties (growth, anatomical, physiological, chemical, mechanical and other properties) of Douglas-fir in order to justify the transfer of seeds from North America to the ecosystems of Serbia. This type of program has been implemented in Serbia on several locations using different Douglas-fir provenances. Given that the analysis of different physiological properties of trees is important for the introduction of specified provenances into habitats in Serbia, in this paper the variability of potassium concentration in young Douglas-fir needles of different provenances was examined in an experimental field in Serbia. Potassium is very important in the physiological processes of plants. It is an essential element involved in a number of biochemical and physiological processes and plays a significant role in the adaptation of plants on biotic and abiotic stress factors. The highest potassium concentration was found in the ?Oregon 205-14? provenance - the only provenance in which the potassium concentration was significantly higher than the average value, so it can be characterized as a superior provenance for the uptake and accumulation of this element. It was found that, at this stage of development, the differences in the potassium concentration in trees in the provenance test have no significant effect on growth parameters. Further studies should show whether the concentration of this biogenic element in any way affects other properties important for the selection of provenances during the introduction process, such as resistance to stress factors.
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Al-Fedaghi, Sabah. "Flow-Based Provenance." Informing Science: The International Journal of an Emerging Transdiscipline 20 (2017): 019–36. http://dx.doi.org/10.28945/3665.

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Aim/Purpose: With information almost effortlessly created and spontaneously available, current progress in Information and Communication Technology (ICT) has led to the complication that information must be scrutinized for trustworthiness and provenance. Information systems must become provenance-aware to be satisfactory in accountability, reproducibility, and trustworthiness of data. Background: Multiple models for abstract representation of provenance have been proposed to describe entities, people, and activities involved in producing a piece of data, including the Open Provenance Model (OPM) and the World Wide Web Consortium. These models lack certain concepts necessary for specifying workflows and encoding the provenance of data products used and generated. Methodology: Without loss of generality, the focus of this paper is on OPM depiction of provenance in terms of a directed graph. We have redrawn several case studies in the framework of our proposed model in order to compare and evaluate it against OPM for representing these cases. Contribution: This paper offers an alternative flow-based diagrammatic language that can form a foundation for modeling of provenance. The model described here provides an (abstract) machine-like representation of provenance. Findings: The results suggest a viable alternative in the area of diagrammatic representation for provenance applications. Future Research: Future work will seek to achieve more accurate comparisons with current models in the field.
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Can, Ozgu, and Dilek Yilmazer. "A novel approach to provenance management for privacy preservation." Journal of Information Science 46, no. 2 (February 21, 2019): 147–60. http://dx.doi.org/10.1177/0165551519827882.

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Provenance determines the origin of the data by tracing and recording the actions that are performed on the data. Therefore, provenance is used in many fields to ensure the reliability and quality of data. In this work, provenance information is used to meet the security needs in information systems. For this purpose, a domain-independent provenance model is proposed. The proposed provenance model is based on the Open Provenance Model and Semantic Web technologies. The goal of the proposed provenance model is to integrate the provenance and security concepts in order to detect privacy violations by querying the provenance data. In order to evaluate the proposed provenance model, we illustrated our domain-independent model by integrating it with an infectious disease domain and implemented the Healthcare Provenance Information System.
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Sultana, Salmin, and Elisa Bertino. "A Distributed System for The Management of Fine-grained Provenance." Journal of Database Management 26, no. 2 (April 2015): 32–47. http://dx.doi.org/10.4018/jdm.2015040103.

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Existing provenance systems operate at a single layer of abstraction (workflow/process/OS) at which they record and store provenance. However, the provenance captured from different layers provides the highest benefit when integrated through a unified provenance framework. To build such a framework, a comprehensive provenance model able to represent the provenance of data objects with various semantics and granularity is the first step. In this paper, the authors propose a provenance model able to represent the provenance of any data object captured at any abstraction layer and present an abstract schema of the model. The expressive nature of the model enables a wide range of provenance queries. The authors also illustrate the utility of their model in real world data processing systems. In the paper, they also introduce a data provenance distributed middleware system composed of several different components and services that capture provenance according to their model and securely stores it in a central repository. As part of our middleware, the authors present a thin stackable file system, called FiPS, for capturing local provenance in a portable manner. FiPS is able to capture provenance at various degrees of granularity, transform provenance records into secure information, and direct the resulting provenance data to various persistent storage systems.
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Kim, In-Sik, Hae-Yun Kwon, Keun-Ok Ryu, and Wan Yong Choi. "Provenance by Site Interaction of Pinus densiflora in Korea." Silvae Genetica 57, no. 1-6 (December 1, 2008): 131–39. http://dx.doi.org/10.1515/sg-2008-0020.

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Abstract Thirty-six provenances of Pinus densiflora were evaluated for stability and adaptability for height growth at 11 test sites in Korea. The data were obtained from measurements at age 6 and analyzed using linear regression model and AMMI (additive main effect and multiplicative interaction) model. There was significant provenance by site interaction effect (p < 0.011). The interaction term explained 7.1% of total variation. While the regression model accounted for 15.8% of GxE interaction term, the AMMI model accounted for 74.9% with four PCA values. Most of the provenances were not significantly different from the unity (b =1.0), except for Inje (1), Jungsun (4), Bongwha (5), Koryung (26), Hamyang (30) and Seoguipo (36). Adaptability of provenances to the test sites was estimated with mean height growth and first AMMI component scores (IPCA 1). Inje (1), Bongwha (5), Taean (20) and Seoguipo (36) were specifically adapted to the high yielding environments. Considering the first and second AMMI components (IPCA 1 and IPCA 2, respectively) scores, Whachun (2), Samchuk (10), Joongwon (14) and Buan (29) provenances were more stable than others. The implication of GxE interaction was discussed in view of seed transfer and delineation of seed zones.
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O’Neill, Gregory A., Gordon Nigh, Tongli Wang, and Peter K. Ott. "Growth response functions improved by accounting for nonclimatic site effects." Canadian Journal of Forest Research 37, no. 12 (December 2007): 2724–30. http://dx.doi.org/10.1139/x07-100.

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Growth response functions (GRFs) that relate the growth of a population to the climate of the sites in which it is tested are gaining attention for their ability to predict impacts of climate change on tree growth. However, nonclimatic site to site variation introduces error into GRFs. Using data from a large lodgepole pine ( Pinus contorta Dougl. ex Loud.) provenance test in British Columbia and the Yukon, Canada, a technique is presented that accounts for the effect of nonclimatic variation in GRFs. The mean height of the “local” provenances at each test site was used to predict “site height” from site climate variables in multiple regression. Residuals from the site height equation provided an index of the nonclimatic effect for each site and were included as a covariate in quadratic GRFs that related provenance height at each test site to mean annual temperature at each test site. Inclusion of the nonclimatic index in the model resulted in a moderate or large displacement of GRFs for 25% of the provenances, while increasing mean R2 values for 138 of 140 provenances and decreasing the root mean squared error for 113 of 140 provenances. These results suggest that inclusion of the nonclimatic index in GRF models could substantially affect height predictions for some provenances and reduce prediction error for most provenances.
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Li, Chunqiu, and Shigeo Sugimoto. "Provenance description of metadata application profiles for long-term maintenance of metadata schemas." Journal of Documentation 74, no. 1 (January 8, 2018): 36–61. http://dx.doi.org/10.1108/jd-03-2017-0042.

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Purpose Provenance information is crucial for consistent maintenance of metadata schemas over time. The purpose of this paper is to propose a provenance model named DSP-PROV to keep track of structural changes of metadata schemas. Design/methodology/approach The DSP-PROV model is developed through applying the general provenance description standard PROV of the World Wide Web Consortium to the Dublin Core Application Profile. Metadata Application Profile of Digital Public Library of America is selected as a case study to apply the DSP-PROV model. Finally, this paper evaluates the proposed model by comparison between formal provenance description in DSP-PROV and semi-formal change log description in English. Findings Formal provenance description in the DSP-PROV model has advantages over semi-formal provenance description in English to keep metadata schemas consistent over time. Research limitations/implications The DSP-PROV model is applicable to keep track of the structural changes of metadata schema over time. Provenance description of other features of metadata schema such as vocabulary and encoding syntax are not covered. Originality/value This study proposes a simple model for provenance description of structural features of metadata schemas based on a few standards widely accepted on the Web and shows the advantage of the proposed model to conventional semi-formal provenance description.
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Tannen, Val. "Provenance analysis for FOL model checking." ACM SIGLOG News 4, no. 1 (February 9, 2017): 24–36. http://dx.doi.org/10.1145/3051528.3051533.

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Dissertations / Theses on the topic "Model of provenance"

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Tang, Yaobin. "Butterfly -- A model of provenance." Worcester, Mass. : Worcester Polytechnic Institute, 2009. http://www.wpi.edu/Pubs/ETD/Available/etd-031309-095511/.

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Thakur, Amritanshu. "Semantic construction with provenance for model configurations in scientific workflows." Master's thesis, Mississippi State : Mississippi State University, 2008. http://library.msstate.edu/etd/show.asp?etd=etd-07312008-092758.

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Liu, Jun. "W7 MODEL OF PROVENANCE AND ITS USE IN THE CONTEXT OF WIKIPEDIA." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145314.

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Data provenance refers to the lineage or pedigree of data, including information such as its origin and key events that affect it over the course of its lifecycle. In recent years, provenance has become increasingly important as more and more people are using data that they themselves did not generate. Tracking data provenance helps ensure that data provided by many different providers and sources can be trusted and used appropriately. Data provenance also has several other critical uses, including data quality assessment, generating data replication recipes, data security management, etc.One of the major objectives of our research is to investigate the semantics or meaning of data provenance. We describe a generic ontology of data provenance called the W7 model that represents the semantics of data provenance. Formalized in the conceptual graph formalism, the W7 model represents provenance as a combination of seven interconnected elements including "what," "when," "where," "how," "who," "which" and "why." The W7 model is designed to be general and comprehensive enough to cover a broad range of provenance-related vocabularies. However, the W7 model alone, no matter how comprehensive it is, is insufficient for capturing all domain-specific provenance requirements. We hence present a novel approach to developing domain ontologies of provenance. This approach relies on various conceptual graph mechanisms, including schema definitions and canonical formation rules, and enables us to easily adapt and extend the W7 model to develop domain ontologies of provenance. The W7 model for data provenance has been widely adopted and adapted for use within Raytheon Missile Systems and the iPlant Collaborative, as well as the US Army's ATRAP IV (Asymmetric Threat Response and Analysis Program) system.We also developed a domain ontology of provenance for Wikipedia based on the W7 model. This domain ontology enables us to extract provenance for each Wikipedia article. We present a study in which we use their provenance to assess the quality of Wikipedia articles. Assessing and guaranteeing data quality has become a critical concern that, to a large extent, determines the future success and survival of Wikipedia since the quality of Wikipedia has been continuously called into question due to various incidents of vandalism and misinformation since its launch in 2001. Our study shows that the quality of Wikipedia articles depends not only on the different types of contributors but also on how they collaborate. We identify a number of contributor roles based on the provenance. Based on the roles and provenance, our research identifies several collaboration patterns that are preferable or detrimental for data quality, thus providing insights for designing tools and mechanisms to improve Wikipedia article quality.
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Ali, Mufajjul. "Provenance-based data traceability model and policy enforcement framework for cloud services." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/393423/.

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In the context of software, provenance holds the key to retaining a reproduceable instance of the duration of a service, which can be replayed/reproduced from the beginning. This entails the nature of invocations that took place, how/where the data were created, modified, updated and the user's engagement with the service. With the emergence of the cloud and the benefits it encompasses, there has been a rapid proliferation of services being developed and adopted by commercial businesses. However, these services expose very little internal workings to their customers, and insufficient means to check for the right working order. This can cause transparency and compliance issues, especially in the event of a fault or violation, customers and providers are left to point finger at each other. Provenance-based traceability provides a means to address a part of this problem by being able to capture and query events that have occurred in the past to understand how and why it took place. On top of that, provenance-based policies are required to facilitate the validation and enforcement of business level requirements for end-users satisfaction. This dissertation makes four contributions to the state of the art: i) By defining and implementing an enhanced provenance-based cloud traceability model (cProv), that extends the standardized Prov model to support characteristics related to cloud services. The model is then able to conceptualize the traceability of a running cloud service. ii) By the creation of a provenance-based policy language (cProvl) in order to facilitate the declaration and enforcement of the business level requirements. iii) By developing a traceability framework, that provides client and server-side stacks for integrating service-level traceability and policy-based enforcement of business rules. iv) Finally by the implementation and evaluation of the framework, that leverages on the standardized industry solutions. The framework is then applied to the commercial service: `ConfidenShare' as a proof of concept.
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Amanqui, Flor Karina Mamani. "Using a provenance model and spatiotemporal information to integrate heterogeneous biodiversity semantic data." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-30012018-093704/.

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In the last few years, the Web of data is being rapidly populated with biodiversity data. However, when researchers need to retrieve, integrate, and visualize these data, they need to rely on semi-manual approaches. That is due to the fact that biodiversity repositories, such as GBIF, offer data as just strings in CSV format spreadsheets. There is no machine readable metadata that could add meaning (semantics) to data. Without this metadata, automatic solutions are impossible and labor intensive semi-manual approaches for data integration and visualization are unavoidable. To reduce this problem, we present a novel architecture, called STBioData, to automatically link spatiotemporal biodiversity data, from heterogeneous data sources, to enable easier searching, visualization and downloading of relevant data. It supports the generation of interactive maps and mapping between biodiversity data and ontologies describing them (such as Darwin Core, DBpedia, GeoSPARQL, Time and PROV-O). A new biodiversity provenance model (BioProv), extending the W3C PROV Data Model, was proposed. BioProv enables applications that deal with biodiversity data to incorporate provenance data in their information. A web based prototype, based on this architecture, was implemented. It supports biodiversity domain experts in tasks, such as identifying a species conservation status, by automating most of the necessary tasks. It uses collection data, from important Brazilian biodiversity research institutions, and species geographic distributions and conservation status, from the IUCN Red List of Threatened Species. These data are converted to linked data, enriched and saved as RDF Triples. Users can access the system, using a web interface, and search for collection and species distribution records based on species names, time ranges and geographic location. After a data set is recovered, it can be displayed in an interactive map. The records contents are also shown (including provenance data) together with links to the original records at GBIF and IUCN. Users can export datasets, as a CSV or RDF file, or get a print out in PDF (including the visualizations). Choosing different time ranges, users can, for instance, verify the evolution of a species distribution. The STBioData prototype was tested using use cases. For the tests, 46,211 collection records, from SpeciesLink, and 38,589 conservation status records (including maps), from IUCN, for marine mammal were converted to 2,233,782. RDF triples and linked using well known ontologies. 90% of biodiversity experts, using the tool to determine conservation status, were able to find information about dolphin species, with a satisfactory recovery time, and were able to understand the interactive map. In an information retrieval experiment, when compared with SpeciesLink keyword based search, the prototypes semantic based search performed, on average, 24% better in precision and 22% in recall tests. And that does not takes into account cases where only the prototype returned search results. These results demonstrate the value of having public available linked biodiversity data with semantics.
Nos últimos anos, a Web de dados está sendo rapidamente preenchida com dados de biodiversidade. No entanto, quando pesquisadores precisam recuperar, integrar e visualizar esses dados, eles precisam confiar em abordagens semi-manuais. Isso ocorre devido ao fato de que repositórios sobre biodiversidade, como GBIF, oferecem dados como cadeias de caracteres em planilhas no formato CSV. Não há nenhum metadado legível por máquinas que poderia acrescentar significado (semântico) aos dados. Sem os metadados, soluções automáticas são impossíveis, sendo necessário para visualização e integração dos dados, a utilização de abordagens semi-manuais. Para reduzir esse problema, apresentamos uma arquitetura chamada STBioData. Com ela é possível vincular automaticamente dados de biodiversidade, com informações espaço-temporais provenientes de fontes heterogêneas, tornando mais fácil a pesquisa, visualização e download dos dados relevantes. Ele suporta a geração de mapas interativos e o mapeamento entre dados de biodiversidade e ontologias que os descrevem (como Darwin Core, DBpedia, GeoSPARQL, Time e PROV-O). Foi proposto um novo modelo de proveniência para biodiversidade (BioProv), que estende o modelo de dados PROV W3C. BioProv permite que aplicativos que lidam com dados de biodiversidade incorporem os dados de proveniência em suas informações. Foi implementado um protótipo Web baseado nesta arquitetura. Ele oferece suporte aos especialistas do domínio de biodiversidade em tarefas como, identificação do status de conservação da espécie, além de automatizar a maioria das tarefas necessária. Foi utilizado coleções de dados de importantes pesquisas brasileiras sobre biodiversidade, juntamente com dados de distribuição geográfica das espécies e seu estado de conservação, provenientes da lista de espécies ameaçadas da IUCN (Red List). Esses dados são convertidos em dados conectados, enriquecidos e salvados como triplas RDF. Os usuários podem acessar o sistema, usando uma interface web que permite procurar, utilizando os nomes das espécies, intervalos de tempo e localização geográfica. Os dados recuperados podem ser visualizados no mapa interativo. O conteúdo de registros também é mostrado (incluindo dados de proveniência), juntamente com links para os registros originais no GBIF e IUCN. Os usuários podem exportar o conjunto de dados, como um arquivo CSV ou RDF, ou salvar em PDF (incluindo as visualizações). Escolhendo diferentes intervalos de tempo, os usuários podem por exemplo, verificar a evolução da distribuição das espécies. O protótipo STBioData foi testado usando casos de uso. Para esses testes, 46.211 registros de coleção do SpeciesLink e 38.589 registros de estado de conservação da IUCN (incluindo mapas), sobre mamíferos marinhos, foram convertidos em 2.233.782 triplas RDF. Essas triplas reutilizam ontologias representativas da área . 90% dos especialistas em biodiversidade, usaram a ferramenta para determinar o estado de conservação, eles foram capaz de encontrar as informações sobre determinada espécie de golfinho, com um tempo de recuperação satisfatório e também foram capaz de entender o mapa interativo gerado. Em um experimento sobre recuperação de informações, quando comparado com o sistema de busca por palavra-chave utilizado pela base SpeciesLink, a busca semântica realizada pelo protótipo STBioData, em média, é 24% melhor em testes de precisão e 22% melhor em testes de revocação. Não são considerados os casos onde o protótipo somente retornou o resultado da busca. Esses resultados demonstram o valor de ter dados conectados sobre biodiversidade disponíveis publicamente em um formato semântico.
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Miksa, Elizabeth J. "A model for assigning temper provenance to archaeological ceramics with case studies from the American Southwest." Diss., The University of Arizona, 1998. http://hdl.handle.net/10150/288805.

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Well-designed provenance studies form the basis from which questions of human economy and behavior are addressed. Pottery is often the subject of such studies, requiring geological and archaeological evidence to establish patterns of ceramic economy. A generalized theoretical and methodological framework for provenance studies is presented, followed by specific considerations for ceramic provenance studies. Four main sources of variation affect pottery composition: geological distribution of resources, geological resource variability, differential economic factors affecting resource use, and technological manipulation of materials. Post depositional alteration is also considered. This ceramic provenance model provides explicit guidelines for the assessment of geological aspects of provenance, since geological resource availability affects acquisition by humans and thus archaeological research designs, in which interdependent geological and archaeological scalar factors must be balanced against budgets. Two case studies illustrate the model. The first is of sand-tempered pottery from the Tonto Basin, Arizona, where the bedrock geology is highly variable giving rise to geographically unique sands. Zones with similar sand compositions are modeled using actualistic petrofacies, the Gazzi-Dickinson point-counting technique, and multivariate statistics. Methods used to create a petrofacies model are detailed, as is the model's application to sand tempered utilitarian sherds from three Tonto Basin project areas. Data analysis reveals strong temporal and spatial ceramic production and consumption patterns. The second is of crushed-schist-tempered Hohokam pottery. Crushed schist was often used to temper pre-Classic Hohokam plain ware pottery in central Arizona's middle Gila River valley. Systematic investigation of rocks from the Pinal Schist terrane in the middle Gila River valley was conducted to assess how many sources were exploited prehistorically, and whether schist or schist-tempered pottery were exchanged. Chemical analysis shows that the sources can be statistically discriminated from one another. Schist source data were compared to schist extracted from plain ware sherds and to unmodified pieces of schist recovered from two archaeological sites. Preliminary indications are that schist was derived from several sources. This model provides a flexible, archaeologically relevant framework for assessing temper provenance. Hopefully, archaeologists and petrologists alike will use it to define ceramic provenance research problems and communicate effective solutions to one another.
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Valente, Wander Antunes Gaspar. "SciProv: uma arquitetura para a busca semântica em metadados de proveniência no contexto de e-Science." Universidade Federal de Juiz de Fora (UFJF), 2011. https://repositorio.ufjf.br/jspui/handle/ufjf/4417.

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A e-Science se caracteriza pela manipulação de um vasto volume de dados e utilização de recursos computacionais em larga escala, muitas vezes localizados em ambientes distribuídos. Nesse cenário, representado por alta complexidade e heterogeneidade, torna-se relevante o tratamento da proveniência de dados, que tem por objetivo descrever os dados que foram gerados ao longo da execução de um experimento científico e apresentar os processos de transformação pelos quais foram submetidos. Assim, a proveniência auxilia a formar uma visão da qualidade, da validade e da atualidade dos dados produzidos em um ambiente de pesquisa científica. O SciProv consiste em uma arquitetura cujo objetivo é interagir com sistemas de gerenciamento de Workflows científicos para promover a captura e a gerência dos metadados de proveniência gerados. Para esse propósito, o SciProv adota uma abordagem baseada em um modelo abstrato para a representação da proveniência. Esse modelo, denominado Open Provenance Model, confere ao SciProv a capacidade de prover uma infraestrutura homogênea e interoperável para a manipulação dos metadados de proveniência. Como resultado, o SciProv permite disponibilizar um arcabouço para consulta às informações de proveniência geradas em um cenário complexo e diversificado de e-Science. Mais importante, a arquitetura faz uso de tecnologia web semântica para processar as consultas aos metadados de proveniência. Nesse contexto, a partir do emprego de ontologias e máquinas de inferências, o SciProv provê recursos para efetuar deduções sobre os metadados de proveniência e obter resultados importantes ao extrair informações adicionais além daquelas que encontram-se registradas de forma explícita nas informações gerenciadas.
E-Science is characterized by manipulation of huge data set and large scale computing resources usage, often located in distributed environments. In this scenario, represented by high complexity and heterogeneity, it becomes important to treat data provenance, which aims to describe data that were generated during a scientific experiment execution and presents processes of transformation by which underwent. Thus, lineage helps to form a quality, validity and topicality vision of data produced in a scientific research environment. SciProv consists of an architecture that aims to interact with scientific workflows management systems for capture and manipulation of generated provenance metadata. For this purpose, SciProv adopts an approach based on an abstract model for representing the lineage. This model, called Open Provenance Model, provides to SciProv the ability to set up a homogeneous and interoperable infrastructure for handling provenance metadata. As a result, SciProv is able to provide a framework for query data provenance generated in a complex and diverse e-Science scenario. More important, the architecture makes use of semantic web technology to process metadata provenance queries. In this context, using ontologies and inference engines, SciProv provides resources to make inferences about lineage and to obtain important results in allowing the extraction of information beyond those that are registered explicitly from managed data.
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Nel, Daniel Hermanus Greyling. "Performative digital asset management: To propose a framework and proof of concept model that effectively enables researchers to document, archive and curate their non-traditional research data." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/84761/3/Daniel_Nel_Exegesis.pdf.

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This cross disciplinary study was conducted as two research and development projects. The outcome is a multimodal and dynamic chronicle, which incorporates the tracking of spatial, temporal and visual elements of performative practice-led and design-led research journeys. The distilled model provides a strong new approach to demonstrate rigour in non-traditional research outputs including provenance and an 'augmented web of facticity'.
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Saghafi, Salman. "A Framework for Exploring Finite Models." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-dissertations/458.

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This thesis presents a framework for understanding first-order theories by investigating their models. A common application is to help users, who are not necessarily experts in formal methods, analyze software artifacts, such as access-control policies, system configurations, protocol specifications, and software designs. The framework suggests a strategy for exploring the space of finite models of a theory via augmentation. Also, it introduces a notion of provenance information for understanding the elements and facts in models with respect to the statements of the theory. The primary mathematical tool is an information-preserving preorder, induced by the homomorphism on models, defining paths along which models are explored. The central algorithmic ideas consists of a controlled construction of the Herbrand base of the input theory followed by utilizing SMT-solving for generating models that are minimal under the homomorphism preorder. Our framework for model-exploration is realized in Razor, a model-finding assistant that provides the user with a read-eval-print loop for investigating models.
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Santos, Renata Ribeiro dos. "Modelo de procedência para auxiliar na análise da qualidade do dado geográfico." Universidade Federal de São Carlos, 2016. https://repositorio.ufscar.br/handle/ufscar/8609.

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The quality of the geographic data must be a relevant concern for providers and consumers of this type of data because the manipulation and analysis of low quality geographic data may result in errors, which will be propagated through the consequent data. Thus it is important to properly document the information which allows for certifying the quality of the geographic data. In order to provide a minimum amount of metadata for such purpose, this dissertation presents an approach based on the provenance of the geographic data, which corresponds to the information about the history of such data from its origin until the processes that resulted in its current state. For this purpose, a provenance model called ProcGeo was proposed, in which it was defined a minimum amount of metadata that must be considered for the analysis of the quality of a certain geographic data. Although a few works and geographic metadata standards, such as Federal Geographic Data Committee (FGDC) and ISO 19115, consider the information about the provenance in the analysis of the quality of geographic data, it´s the opinion of the author that some metadata considered important for this purpose are not adequately contemplated. In this work, the prototype of an interface called ProcGeoInter was also implemented, aiming to guarantee the completeness and correctness in the filling out of the defined metadata in the ProcGeo model as well as the visualization of their content. The validation of the ProcGeo model and of the ProcGeoInter interface were made through tests and surveys applied to providers and consumers of geographic data. As a means of comparison, the interface for filling out and visualization of metadata available by SIG Quantum GIS (plugin Metatools) was used, which implements the FGDC geographic metadata standard. The obtained results indicated that the metadata defined in the ProcGeo model helped the geographic data provider in the description of the provenance of such data, when compared to those defined in the FGDC geographic metadata standard. Through the consumer´s focus it was possible to notice that the information filled out in the metadata defined by the ProcGeo favored the analysis of the quality of the consumed data. It was clear that both providers and consumers do not possess the habit of providing or consuming the information predicted in the FGDC and ISO 19115 geographic metadata standards.
A qualidade do dado geográfico deve ser uma preocupação relevante para provedores e consumidores desse tipo de dado, pois a manipulação e análise de um dado geográfico com baixa qualidade podem resultar em erros que vão se propagar nos dados gerados a partir desse. Assim, é importante que a informação que permita atestar a qualidade do dado geográfico seja adequadamente documentada. Com o propósito de oferecer um conjunto mínimo de metadados para essa finalidade, esse trabalho apresenta uma abordagem baseada na procedência do dado geográfico, que corresponde à informação sobre a história do dado, desde a sua origem até os processos que resultaram no seu estado atual. Para tanto, foi proposto um modelo de procedência denominado ProcGeo no qual foi definido um conjunto mínimo de metadados que devem ser considerados para a análise da qualidade de um dado geográfico. Embora alguns trabalhos e padrões de metadados geográficos, como o Federal Geographic Data Committee (FGDC) e o ISO 19115, considerem a informação da procedência para a análise da qualidade do dado geográfico, sob o ponto de vista da autora deste trabalho, alguns metadados considerados importantes para essa finalidade não são adequadamente contemplados. Neste trabalho também foi implementado o protótipo de uma interface denominada ProcGeoInter, que tem como finalidade garantir a corretude e completude do preenchimento dos metadados definidos no modelo ProcGeo e a visualização do conteúdo dos mesmos. A validação do modelo ProcGeo e da interface ProcGeoInter foram realizados por meio de testes e questionários aplicados a provedores e consumidores de dados geográficos. Para efeito de comparação, foi considerada a interface para preenchimento e visualização de metadados disponibilizada no SIG Quantum GIS (plugin Metatoools), que implementa o padrão de metadados geográficos FGDC. Os resultados obtidos indicaram que os metadados definidos no modelo ProcGeo auxiliaram o provedor de dados geográficos na descrição da procedência desses dados, quando comparados aos definidos no padrão de metadados geográficos FGDC. Pelo foco do consumidor foi possível perceber que as informações preenchidas nos metadados definidos pelo ProcGeo favoreceram a análise da qualidade dos dados consumidos. Ficou evidente que tanto provedores quanto consumidores não possuem o hábito de prover ou consumir as informações previstas nos padrões de metadados geográficos FGDC e ISO 19115.
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Books on the topic "Model of provenance"

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Liu, Qing. Data Provenance and Data Management in eScience. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Liu, Qing, Quan Bai, Darrell Williamson, Stephen Giugni, and Johnn Taylor. Data Provenance and Data Management in EScience. Springer Berlin / Heidelberg, 2014.

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Liu, Qing, Quan Bai, and Stephen Giugni. Data Provenance and Data Management in eScience. Springer, 2012.

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Glavic, Boris. Data Provenance: Origins, Applications, Algorithms, and Models. Now Publishers, 2021.

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Liu, Huan, Geoffrey Barbier, Zhuo Feng, and Pritam Gundecha. Provenance Data in Social Media. Morgan & Claypool Publishers, 2013.

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Liu, Huan, Geoffrey Barbier, Zhuo Feng, and Pritam Gundecha. Provenance Data in Social Media. Springer International Publishing AG, 2013.

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Provenance Data in Social Media. Morgan & Claypool Publishers, 2013.

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Konstan, David. Comedy and the Athenian Ideal. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198748472.003.0006.

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New Comedy was a Panhellenic phenomenon. It may be that a performance in Athens was still the acme of a comic playwright’s career, but Athens was no longer the exclusive venue of the genre. Yet Athens, or an idealized version of Athens, remained the setting or backdrop for New Comedy, whatever its provenance or intended audience. New Comedy was thus an important vehicle for the dissemination of the Athenian polis model throughout the Hellenistic world, and it was a factor in what has been termed ‘the great convergence’. The role of New Comedy in projecting an idealized image of the city-state may be compared to that of Hollywood movies in conveying a similarly romanticized, but not altogether false, conception of American democracy to populations around the world.
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Data Provenance And Data Management In Escience. Springer, 2012.

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Seneviratne, Oshani W., Leslie F. Sikos, and Deborah L. McGuinness. Provenance in Data Science: From Data Models to Context-Aware Knowledge Graphs. Springer International Publishing AG, 2021.

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Book chapters on the topic "Model of provenance"

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Taylor, Kerry, Robert Woodcock, Susan Cuddy, Peter Thew, and David Lemon. "A Provenance Maturity Model." In IFIP Advances in Information and Communication Technology, 1–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15994-2_1.

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Schreiber, Andreas, Miriam Ney, and Heinrich Wendel. "The Provenance Store prOOst for the Open Provenance Model." In Lecture Notes in Computer Science, 240–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34222-6_26.

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Sultana, Salmin, and Elisa Bertino. "A Comprehensive Model for Provenance." In Lecture Notes in Computer Science, 243–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34222-6_27.

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Sultana, Salmin, and Elisa Bertino. "A Comprehensive Model for Provenance." In Lecture Notes in Computer Science, 121–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33999-8_15.

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Zhao, Yong, Michael Wilde, and Ian Foster. "Applying the Virtual Data Provenance Model." In Provenance and Annotation of Data, 148–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11890850_16.

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Buneman, Peter, Adriane Chapman, James Cheney, and Stijn Vansummeren. "A Provenance Model for Manually Curated Data." In Provenance and Annotation of Data, 162–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11890850_17.

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Zhong, Han, Jianhui Chen, Taihei Kotake, Jian Han, Ning Zhong, and Zhisheng Huang. "Developing a Brain Informatics Provenance Model." In Lecture Notes in Computer Science, 439–49. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02753-1_44.

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Curcin, Vasa, Roxana Danger, Wolfgang Kuchinke, Simon Miles, Adel Taweel, and Christian Ohmann. "Provenance Model for Randomized Controlled Trials." In Data Provenance and Data Management in eScience, 3–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-29931-5_1.

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Moreau, Luc, Juliana Freire, Joe Futrelle, Robert E. McGrath, Jim Myers, and Patrick Paulson. "The Open Provenance Model: An Overview." In Lecture Notes in Computer Science, 323–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89965-5_31.

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Bowers, Shawn, Timothy McPhillips, Bertram Ludäscher, Shirley Cohen, and Susan B. Davidson. "A Model for User-Oriented Data Provenance in Pipelined Scientific Workflows." In Provenance and Annotation of Data, 133–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11890850_15.

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Conference papers on the topic "Model of provenance"

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Reynolds, Owen, Antonio García-Domínguez, and Nelly Bencomo. "Automated provenance graphs for models@run.time." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3417990.3419503.

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Groth, Paul, Ewa Deelman, Gideon Juve, Gaurang Mehta, and Bruce Berriman. "Pipeline-centric provenance model." In the 4th Workshop. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1645164.1645168.

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Leschert, Duane, and Pamela Mclean. "Power system model data provenance." In 2015 IEEE/IAS 51st Industrial & Commercial Power Systems Technical Conference (I&CPS). IEEE, 2015. http://dx.doi.org/10.1109/icps.2015.7266421.

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Liu, Yong, Joe Futrelle, James Myers, Alejandro Rodriguez, and Rob Kooper. "A provenance-aware virtual sensor system using the Open Provenance Model." In 2010 International Symposium on Collaborative Technologies and Systems. IEEE, 2010. http://dx.doi.org/10.1109/cts.2010.5478496.

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Campagna, Daniel Prett, Altigran Soares Da Silva, and Vanessa Braganholo. "Achieving GDPR Compliance through Provenance: An Extended Model." In XXXV Simpósio Brasileiro de Banco de Dados. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/sbbd.2020.13621.

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The approval of the General Data Protection Regulation (GDPR) brought a revolution in the way we treat data produced in digital media. The GDPR increases individuals’ participation in the treatment of their data, and it also introduces technical challenges, whose failure can lead to a fine of 4% of the organization’s annual revenue. Among many approaches that aim to contribute to the solutions of challenges introduced by GDPR, there is a research branch promoting the use of data provenance as a means to make transparent the increasingly complex workflows of systems. However, existing provenance models are not fully compliant with the GDPR. In this paper, we aim to contribute to the evolution of the GDPR data provenance model proposed by Ujcich et al.. We suggest eleven new changes that make the model more apparent and more compatible with the GDPR text. We also present two design patterns that should guide us in using these changes in real contexts.
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Park, Jaehong, Dang Nguyen, and Ravi Sandhu. "A provenance-based access control model." In 2012 Tenth Annual International Conference on Privacy, Security and Trust (PST). IEEE, 2012. http://dx.doi.org/10.1109/pst.2012.6297930.

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Mei, Songzhu, Cong Liu, Qinglin Wang, and Huayou Su. "Model Provenance Management in MLOps Pipeline." In ICCDE 2022: 2022 The 8th International Conference on Computing and Data Engineering. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3512850.3512861.

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Butt, Anila, Nicholas Car, and Peter Fitch. "Towards Ontology Driven Provenance in Scientific Workflow Engine." In 8th International Conference on Model-Driven Engineering and Software Development. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0008963701050115.

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Cao, Bin, Beth Plale, Girish Subramanian, Ed Robertson, and Yogesh Simmhan. "Provenance Information Model of Karma Version 3." In 2009 IEEE Congress on Services (SERVICES). IEEE, 2009. http://dx.doi.org/10.1109/services-i.2009.54.

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Mohy, Noha Nagy, Hoda M. O. Mokhtar, and Mohamed E. El-Sharkawi. "Delegation enabled provenance-based access control model." In 2015 Science and Information Conference (SAI). IEEE, 2015. http://dx.doi.org/10.1109/sai.2015.7237321.

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Reports on the topic "Model of provenance"

1

Roberts, Andrew, Elizabeth Hunke, Bonnie Brown, and Nicole Jeffery. Arctic Domain Awareness Center (ADAC) Marine Spill Modeling Working Group: Sea Ice Model Provenance. Office of Scientific and Technical Information (OSTI), January 2021. http://dx.doi.org/10.2172/1762724.

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