Browsing by Subject "database"

Sort by: Order: Results:

Now showing items 1-9 of 9
  • Veikkolainen, Toni H.; Biggin, Andrew John; Pesonen, Lauri J.; Evans, David A.; Jarboe, Nicholas A. (2017)
    State-of-the-art measurements of the direction and intensity of Earth’s ancient magnetic field have made important contributions to our understanding of the geology and palaeogeography of Precambrian Earth. The PALEOMAGIA and PINT(QPI) databases provide thorough public collections of important palaeomagnetic data of this kind. They comprise more than 4,100 observations in total and have been essential in supporting our international collaborative efforts to understand Earth's magnetic history on a timescale far longer than that of the present Phanerozoic Eon. Here, we provide an overview of the technical structure and applications of both databases, paying particular attention to recent improvements and discoveries.
  • Pfeifer, Marion; Lefebvre, Veronique; Gardner, Toby A.; Arroyo-Rodriguez, Victor; Baeten, Lander; Banks-Leite, Cristina; Barlow, Jos; Betts, Matthew G.; Brunet, Joerg; Cerezo, Alexis; Cisneros, Laura M.; Collard, Stuart; D'Cruze, Neil; da Silva Motta, Catarina; Duguay, Stephanie; Eggermont, Hilde; Eigenbrod, Felix; Hadley, Adam S.; Hanson, Thor R.; Hawes, Joseph E.; Scalley, Tamara Heartsill; Klingbeil, Brian T.; Kolb, Annette; Kormann, Urs; Kumar, Sunil; Lachat, Thibault; Lakeman Fraser, Poppy; Lantschner, Victoria; Laurance, William F.; Leal, Inara R.; Lens, Luc; Marsh, Charles J.; Medina-Rangel, Guido F.; Melles, Stephanie; Mezger, Dirk; Oldekop, Johan A.; Overal, William L.; Owen, Charlotte; Peres, Carlos A.; Phalan, Ben; Pidgeon, Anna M.; Pilia, Oriana; Possingham, Hugh P.; Possingham, Max L.; Raheem, Dinarzarde C.; Ribeiro, Danilo B.; Ribeiro Neto, Jose D.; Robinson, W. Douglas; Robinson, Richard; Rytwinski, Trina; Scherber, Christoph; Slade, Eleanor M.; Somarriba, Eduardo; Stouffer, Philip C.; Struebig, Matthew J.; Tylianakis, Jason M.; Tscharntke, Teja; Tyre, Andrew J.; Urbina Cardona, Jose N.; Vasconcelos, Heraldo L.; Wearn, Oliver; Wells, Konstans; Willig, Michael R.; Wood, Eric; Young, Richard P.; Bradley, Andrew V.; Ewers, Robert M. (2014)
  • Roberts, Sean G.; Killin, Anton; Deb, Angarika; Sheard, Catherine; Greenhill, Simon J.; Sinnemäki, Kaius; Segovia Martín, José; Nölle, Jonas; Berdicevskis, Aleksandrs; Humphreys-Balkwill, Archie; Little, Hannah; Opie, Kit; Jacques, Guillaume; Bromham, Lindell; Tinits, Peeter; Ross, Robert M.; Lee, Sean; Gasser, Emily; Calladine, Jasmine; Spike, Matthew; Mann, Stephen; Shcherbakova, Olena; Singer, Ruth; Zhang, Shuya; Benítez-Burraco, Antonio; Kliesch, Christian; Thomas-Colquhoun, Ewan; Skirgård, Hedvig; Tamariz, Monica; Passmore, Sam; Pellard, Thomas; Jordan, Fiona (2020)
    Language is one of the most complex of human traits. There are many hypotheses about how it originated, what factors shaped its diversity, and what ongoing processes drive how it changes. We present the Causal Hypotheses in Evolutionary Linguistics Database (CHIELD, https://chield.excd.org/), a tool for expressing, exploring, and evaluating hypotheses. It allows researchers to integrate multiple theories into a coherent narrative, helping to design future research. We present design goals, a formal specification, and an implementation for this database. Source code is freely available for other fields to take advantage of this tool. Some initial results are presented, including identifying conflicts in theories about gossip and ritual, comparing hypotheses relating population size and morphological complexity, and an author relation network.
  • Wu, Jiayao; Choi, Jaeyoung; Asiegbu, Fred O.; Lee, Yong-Hwan (2020)
    Abstract Laccases (EC 1.10.3.2), a group of multi-copper oxidases (MCOs), play multiple biological functions and widely exist in many species. Fungal laccases have been extensively studied for their industrial applications, however, there was no database specially focused on fungal laccases. To provide a comparative genomics platform for fungal laccases, we have developed a comparative genomics platform for laccases and MCOs (http://laccase.riceblast.snu.ac.kr/). Based on protein domain profiles of characterized sequences, 3,571 laccases were predicted from 690 genomes including 253 fungi. The number of putative laccases and their properties exhibited dynamic distribution across the taxonomy. A total of 505 laccases from 68 genomes were selected and subjected to phylogenetic analysis. As a result, four clades comprised of nine subclades were phylogenetically grouped by their putative functions and analyzed at the sequence level. Our work would provide a workbench for putative laccases mainly focused on the fungal kingdom as well as a new perspective in the identification and classification of putative laccases and MCOs.
  • Culina, Antica; Adriaensen, Frank; Bailey, Liam D.; Burgess, Malcolm D.; Charmantier, Anne; Cole, Ella F.; Eeva, Tapio; Matthysen, Erik; Nater, Chloe R.; Sheldon, Ben C.; Saether, Bernt-Erik; Vriend, Stefan J. G.; Zajkova, Zuzana; Adamik, Peter; Aplin, Lucy M.; Angulo, Elena; Artemyev, Alexandr; Barba, Emilio; Barisic, Sanja; Belda, Eduardo; Bilgin, Cemal Can; Bleu, Josefa; Both, Christiaan; Bouwhuis, Sandra; Branston, Claire J.; Broggi, Juli; Burke, Terry; Bushuev, Andrey; Camacho, Carlos; Campobello, Daniela; Canal, David; Cantarero, Alejandro; Caro, Samuel P.; Cauchoix, Maxime; Chaine, Alexis; Cichon, Mariusz; Cikovic, Davor; Cusimano, Camillo A.; Deimel, Caroline; Dhondt, Andre A.; Dingemanse, Niels J.; Doligez, Blandine; Dominoni, Davide M.; Doutrelant, Claire; Drobniak, Szymon M.; Dubiec, Anna; Eens, Marcel; Erikstad, Kjell Einar; Espin, Silvia; Farine, Damien R.; Figuerola, Jordi; Gulbeyaz, Pinar Kavak; Gregoire, Arnaud; Hartley, Ian R.; Hau, Michaela; Hegyi, Gergely; Hille, Sabine; Hinde, Camilla A.; Holtmann, Benedikt; Ilyina, Tatyana; Isaksson, Caroline; Iserbyt, Arne; Ivankina, Elena; Kania, Wojciech; Kempenaers, Bart; Kerimov, Anvar; Komdeur, Jan; Korsten, Peter; Kral, Miroslav; Krist, Milos; Lambrechts, Marcel; Lara, Carlos E.; Leivits, Agu; Liker, Andras; Lodjak, Jaanis; Magi, Marko; Mainwaring, Mark C.; Mand, Raivo; Massa, Bruno; Massemin, Sylvie; Martinez-Padilla, Jesus; Mazgajski, Tomasz D.; Mennerat, Adele; Moreno, Juan; Mouchet, Alexia; Nakagawa, Shinichi; Nilsson, Jan-Ake; Nilsson, Johan F.; Norte, Ana Claudia; van Oers, Kees; Orell, Markku; Potti, Jaime; Quinn, John L.; Reale, Denis; Reiertsen, Tone Kristin; Rosivall, Balazs; Russell, Andrew F.; Rytkonen, Seppo; Sanchez-Virosta, Pablo; Santos, Eduardo S. A.; Schroeder, Julia; Senar, Juan Carlos; Seress, Gabor; Slagsvold, Tore; Szulkin, Marta; Teplitsky, Celine; Tilgar, Vallo; Tolstoguzov, Andrey; Torok, Janos; Valcu, Mihai; Vatka, Emma; Verhulst, Simon; Watson, Hannah; Yuta, Teru; Zamora-Marin, Jose M.; Visser, Marcel E. (2021)
    The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long-term studies of birds, we have created the SPI-Birds Network and Database ()-a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community-derived data and meta-data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta-data language). The encouraging community involvement stems from SPI-Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much-needed large-scale ecological data integration.
  • Foster, Scott D.; Vanhatalo, Jarno; Trenkel, Verena M.; Schulz, Torsti; Lawrence, Emma; Przeslawski, Rachel; Hosack, Geoffrey (2021)
    Data are currently being used, and reused, in ecological research at an unprecedented rate. To ensure appropriate reuse however, we need to ask the question: "Are aggregated databases currently providing the right information to enable effective and unbiased reuse?" We investigate this question, with a focus on designs that purposefully favor the selection of sampling locations (upweighting the probability of selection of some locations). These designs are common and examples are those designs that have uneven inclusion probabilities or are stratified. We perform a simulation experiment by creating data sets with progressively more uneven inclusion probabilities and examine the resulting estimates of the average number of individuals per unit area (density). The effect of ignoring the survey design can be profound, with biases of up to 250% in density estimates when naive analytical methods are used. This density estimation bias is not reduced by adding more data. Fortunately, the estimation bias can be mitigated by using an appropriate estimator or an appropriate model that incorporates the design information. These are only available however, when essential information about the survey design is available: the sample location selection process (e.g., inclusion probabilities), and/or covariates used in their specification. The results suggest that such information must be stored and served with the data to support meaningful inference and data reuse.
  • de Guerre, Livia; Venermo, Maarit; Mani, Kevin; Wanhainen, Anders; Schermerhorn, Marc (2020)
    Abstract Abdominal aortic aneurysm (AAA) is a relatively common and potentially fatal disease. The management of AAA has undergone extensive changes in the last two decades. High quality vascular surgical registries were established early and have been found to be instrumental in the evaluation and monitoring of these changes, most notably the wide implementation of minimally invasive endovascular surgical technology. Trends over the years showed the increased use of endovascular aneurysm repair (EVAR) over open repair, the decreasing perioperative adverse outcomes and the early survival advantage of EVAR. Also, data from the early EVAR years changed the views on endoleak management and showed the importance of tracking the implementation of new techniques. Registry data complemented the randomized trials performed in aortic surgery by showing the high rate of laparotomy related reinterventions after open repair. Also, they are an essential tool for the understanding of outcomes in a broad patient population, evaluating the generalizability of findings from randomized trials and analyzing changes over time. By using large scale data over longer periods of time, the importance of centralization of care to high-volume centers was shown, particularly for open repair. Additionally, large-scale databases can offer an opportunity to assess practice and outcomes in patient subgroups (e.g. treatment of AAA in women and the elderly) as well as in rare aortic pathologies. In this review article, we point out the most important paradigm shifts in AAA management based on vascular registry data.
  • Niemi, Timo (2010)
    New media technology and software play an ever more important role in social practice. Yet software or the principles of new media have seemingly not been discussed in sociological theory. This study aims to provide new theory on the subject by suggesting that users exist in two different forms while using new media for social purposes. On the one hand the user is a social actor, following established social norms and structures, but on the other hand the user simultaneously exists as a digital entry in a database, subjected to a completely different set of rules based on new media technology. The study aims to explore the tensions that arise from this duality. The study proposes a morphological, conceptual analysis to explore the interaction between social practice and new media, but does not include an empirical part. Sociality is conceptually defined as Manuel Castells’s notion of networks, while new media technology is treated as the database, which Lev Manovich argues to be the central form of contemporary culture. These forms are complemented with their respective logics or patterns of action, network sociality and the principles of new media, respectively. The understanding of new media is further developed by exploring the academic field of software studies. The results of the conceptual analysis, formulated as a theoretical framework, suggest that networks and databases differ in their understanding of time and space, their functioning logic, and the basis on which their respective units react and reason. Lev Manovich’s notion of transcoding then implies that the technological and cultural levels in new media interact and modify each other. The results of the conceptual analysis are reflected upon through existing studies on social networking services and new media. The identified processes are then further formulated into suggestions on how social practices may change if they were to be more heavily aggregated through new media. These developments include trends of quantification and automation, changing rules of social space, and an increased emphasis on information exchange in both practice and theory. Lastly, the discussion chapter situates the findings next to earlier research, which has reflected upon the database as a form that defines social surveillance and the formation of identity. The capability to conceptually separate social norms from the affordances suggested by new media may be useful for a meaningful interpretation of everyday social practice. Central references: For new media: Manovich, Lev: The Language of New Media (2001); Fuller, Matthew (ed.): Software Studies - A Lexicon (2009). Beer, David: Power through the algorithm? Participatory web cultures and the technological unconscious (2009); Boyd, Danah: Facebook's Privacy Trainwreck. Exposure, Invasion, and Social Convergence (2008). For networks: Castells, Manuel: The internet Galaxy (2001), The Network Society: A Cross-cultural Perspective (2004); Stalder, Felix: Manuel Castells: The Theory of the Network Society (2004); Wittel, Andreas: Toward a Network Sociality (2001); Miller, Vincent: New Media, Networking and Phatic Culture (2008).
  • Xu, Pengfei; Lu, Jiaheng (2019)
    A similarity join aims to find all similar pairs between two collections of records. Established algorithms utilise different similarity measures, either syntactic or semantic, to quantify the similarity between two records. However, when records are similar in forms of a mixture of syntactic and semantic relations, utilising a single measure becomes inadequate to disclose the real similarity between records, and hence unable to obtain high-quality join results. In this paper, we study a unified framework to find similar records by combining multiple similarity measures. To achieve this goal, we first develop a new similarity framework that unifies the existing three kinds of similarity measures simultaneously, including syntactic (typographic) similarity, synonym-based similarity, and taxonomy-based similarity. We then theoretically prove that finding the maximum unified similarity between two strings is generally NP-hard, and furthermore develop an approximate algorithm which runs in polynomial time with a non-trivial approximation guarantee. To support efficient string joins based on our unified similarity measure, we adopt the filter-and-verification framework and propose a new signature structure, called pebble, which can be simultaneously adapted to handle multiple similarity measures. The salient feature of our approach is that, it can judiciously select the best pebble signatures and the overlap thresholds to maximise the filtering power. Extensive experiments show that our methods are capable of finding similar records having mixed types of similarity relations, while exhibiting high efficiency and scalability for similarity joins. The implementation can be downloaded at https://github.com/HY-UDBMS/AU-Join.