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Temporal Database in Hindi
 
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A temporal database is a database with built-in support for handling data involving time, being related to the slowly changing dimension concept, for example a temporal data model and a temporal version of Structured Query Language (SQL). More specifically the temporal aspects usually include valid time and transaction time. These attributes can be combined to form bitemporal data. Valid time is the time period during which a fact is true in the real world. Transaction time is the time period during which a fact stored in the database was known. Bitemporal data combines both Valid and Transaction Time. It is possible to have timelines other than Valid Time and Transaction Time, such as Decision Time, in the database. In that case the database is called a multitemporal database as opposed to a bitemporal database. However, this approach introduces additional complexities such as dealing with the validity of (foreign) keys. Temporal databases are in contrast to current databases (at term that doesn't mean, currently available databases, some do have temporal features, see also below), which store only facts which are believed to be true at the current time. Temporal databases supports System-maintained transaction time. With the development of SQL and its attendant use in real-life applications, database users realized that when they added date columns to key fields, some issues arose. For example, if a table has a primary key and some attributes, adding a date to the primary key to track historical changes can lead to creation of more rows than intended. Deletes must also be handled differently when rows are tracked in this way. In 1992, this issue was recognized but standard database theory was not yet up to resolving this issue, and neither was the then-newly formalized SQL-92 standard. Richard Snodgrass proposed in 1992 that temporal extensions to SQL be developed by the temporal database community. In response to this proposal, a committee was formed to design extensions to the 1992 edition of the SQL standard (ANSI X3.135.-1992 and ISO/IEC 9075:1992); those extensions, known as TSQL2, were developed during 1993 by this committee.[3] In late 1993, Snodgrass presented this work to the group responsible for the American National Standard for Database Language SQL, ANSI Technical Committee X3H2 (now known as NCITS H2). The preliminary language specification appeared in the March 1994 ACM SIGMOD Record. Based on responses to that specification, changes were made to the language, and the definitive version of the TSQL2 Language Specification was published in September, 1994[4] An attempt was made to incorporate parts of TSQL2 into the new SQL standard SQL:1999, called SQL3. Parts of TSQL2 were included in a new substandard of SQL3, ISO/IEC 9075-7, called SQL/Temporal.[3] The TSQL2 approach was heavily criticized by Chris Date and Hugh Darwen.[5] The ISO project responsible for temporal support was canceled near the end of 2001. As of December 2011, ISO/IEC 9075, Database Language SQL:2011 Part 2: SQL/Foundation included clauses in table definitions to define "application-time period tables" (valid time tables), "system-versioned tables" (transaction time tables) and "system-versioned application-time period tables" (bitemporal tables). A substantive difference between the TSQL2 proposal and what was adopted in SQL:2011 is that there are no hidden columns in the SQL:2011 treatment, nor does it have a new data type for intervals; instead two date or timestamp columns can be bound together using a PERIOD FOR declaration. Another difference is replacement of the controversial (prefix) statement modifiers from TSQL2 with a set of temporal predicates. For illustration, consider the following short biography of a fictional man, John Doe: John Doe was born on April 3, 1975 in the Kids Hospital of Medicine County, as son of Jack Doe and Jane Doe who lived in Smallville. Jack Doe proudly registered the birth of his first-born on April 4, 1975 at the Smallville City Hall. John grew up as a joyful boy, turned out to be a brilliant student and graduated with honors in 1993. After graduation he went to live on his own in Bigtown. Although he moved out on August 26, 1994, he forgot to register the change of address officially. It was only at the turn of the seasons that his mother reminded him that he had to register, which he did a few days later on December 27, 1994. Although John had a promising future, his story ends tragically. John Doe was accidentally hit by a truck on April 1, 2001. The coroner reported his date of death on the very same day.
Views: 12422 Introtuts
Introduction to Temporal Databases
 
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Subject:Computer Science Paper: Database management system
Views: 1059 Vidya-mitra
An Introduction to Temporal Databases
 
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Check out http://www.pgconf.us/2015/event/83/ for the full talk details. In the past manipulating temporal data was rather ad hoc and in the form of simple solutions. Today organizations strongly feel the need to support temporal data in a coherent way. Consequently, there is an increasing interest in temporal data and major database vendors recently provide tools for storing and manipulating temporal data. However, these tools are far from being complete in addressing the main issues in handling temporal data. The presentation uses the relational data model in addressing the subtle issues in managing temporal data: comparing database states at two different time points, capturing the periods for concurrent events and accessing to times beyond these periods, sequential semantics, handling multi-valued attributes, temporal grouping and coalescing, temporal integrity constraints, rolling the database to a past state and restructuring temporal data, etc. It also lays the foundation in managing temporal data in NoSQL databases as well. Having ranges as a data type PostgresSQL has a solid base in implementing a temporal database that can address many of these issues successfully. About the Speaker Abdullah Uz Tansel is professor of Computer Information Systems at the Zicklin School of Business at Baruch College and Computer Science PhD program at the Graduate Center. His research interests are database management systems, temporal databases, data mining, and semantic web. Dr. Tansel published many articles in the conferences and journals of ACM and IEEE. Dr. Tansel has a pending patent application on semantic web. Currently, he is researching temporality in RDF and OWL, which are semantic web languages. Dr. Tansel served in program committees of many conferences and headed the editorial board that published the first book on temporal databases in 1993. He is also one the editors of the forth coming book titled Recommendation and Search in Social Networks to be published by Springer. He received BS, MS and PhD degrees from the Middle East Technical University, Ankara Turkey. He also completed his MBA degree in the University of Southern California. Dr. Tansel is a member of ACM and IEEE Computer Society.
Views: 4942 Postgres Conference
Introduction Spatial Data
 
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Excel Maps, applied to MS Power BI Course curriculum - http://bitly.com/Agenda-BI Cloud Hound website http://www.cloudhound.co.uk
Views: 2581 Cloud Hound
11. Temporal Data Visualization
 
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11. Temporal Data Visualization slides by niklas elmqvist
Views: 343 jengolbeck
Temporal database
 
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Syracuse University IST659 Group Presentation
Views: 266 Minyang Wang
Spatial Data
 
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Views: 6136 UWFGISMOOC
A Unifying Framework of Mining Trajectory Patterns of Various Temporal Tightness
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 124 Clickmyproject
A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data
 
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Hetero-ConvLSTM: A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data Authors: Zhuoning Yuan (University of Iowa); Xun Zhou (University of Iowa); Tianbao Yang (University of Iowa) Abstract: Predicting traffic accidents is a crucial problem to improving transportation and public safety as well as safe routing. The problem is also challenging due to the rareness of accidents in space and time and spatial heterogeneity of the environment (e.g., urban vs. rural). Most previous research on traffic accident prediction conducted by domain researchers simply applied classical prediction models on limited data without addressing the above challenges properly, thus leading to unsatisfactory performance. A small number of recent works have attempted to use deep learning for traffic accident prediction. However, they either ignore time information or use only data from a small and homogeneous study area (a city), without handling spatial heterogeneity and temporal auto-correlation properly at the same time. In this paper we perform a comprehensive study on the traffic accident prediction problem using the Convolutional Long Short-Term Memory (ConvLSTM) neural network model. A number of detailed features such as weather, environment, road condition, and traffic volume are extracted from big datasets over the state of Iowa across 8 years. To address the spatial heterogeneity challenge in the data, we propose a Hetero-ConvLSTM framework, where a few novel ideas are implemented on top of the basic ConvLSTM model, such as incorporating spatial graph features and spatial model ensemble. Extensive experiments on the 8-year data over the entire state of Iowa show that the proposed framework makes reasonably accurate predictions and significantly improves the prediction accuracy over baseline approaches. More on http://www.kdd.org/kdd2018/
Views: 1523 KDD2018 video
Teradata Temporal Data by Martin Willcox
 
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Martin Willcox, Director for Products and Solutions Marketing for Teradata Corporation in EMEA will discuss about the Temporal feature included in the latest release of the Teradata DBMS. Temporal adds the time dimension to data allowing richer and more meaningful analysis reflecting business and environment changes over time. It eliminates complexity that increases development costs, delays applications and complicates ETL and data maintenance.
Views: 1348 TeradataEMEA
Visualizing spatiotemporal models with virtual reality … - Data visualization (part 1)
 
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Speaker: Stefano Castruccio - University of Notre Dame, USA Recent advances in computing hardware and software present an unprecedented opportunity for statisticians who work with data indexed in space and time to visualize, explore and assess the structure of the data and to improve resulting statistical models. We present results of a 3-year collaboration with a team of visualization experts on the use of stereoscopic view and virtual reality (VR) to visualize spatiotemporal data with animations on non-trivial manifolds. We first present our experience with fully immersive VR with motion tracking devices that enable users to explore global three-dimensional time–temperature fields on a spherical shell interactively. We then introduce a suite of applications with VR mode, freely available for smartphones, to port a visualization experience to any interested people. We also discuss recent work with head-mounted devices such as a VR headset with motion tracking sensors. Watch part 2 here: https://www.youtube.com/watch?v=E8vdXoJId8M
Views: 356 RoyalStatSoc
Jeff Davis: Temporal Database Demo
 
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Walk through creating a temporal database in PostgreSQL, based on a true story! We'll use the latest features in 9.2 to represent some typical business needs with time as a central focus. The speaker will try to adapt to some reasonable change requests from the audience, so some chaos may ensue. Managing time effectively is a crucial business need, but basic SQL doesn't provide the necessary tools. Timestamps by themselves aren't good enough, we need ranges of time (available in PostgreSQL 9.2) to tame the complexity. Even more important is the need to adapt to changing requirements quickly without cascading consequences. Temporal constraints and simpler temporal queries can increase confidence when adapting.
Views: 1687 Postgres Open SV 2018
Spatial Business Intelligence at DigitalGlobe
 
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Jason Horner is with DigitalGlobe, a global provider of earth imagery used for mapping and analysis, environmental monitoring, oil and gas exploration, as well as defense, civilian, and intelligence agencies. "So Digital Globe provides commercial and government satellite imagery. We run a constellation of 5 satellites and produce imagery for various governmental industries and other countries and commercial providers such as Bing and Google. Oh we captured the inauguration of Barack Obama, we have got pictures of that, gosh I can't remember the name, the thing in Dubai, the tower where they did the Ghost Protocol movie and we use it for emergency response, so for hurricanes, natural events, a lot of interesting uses. Yeah, so the cameras orbit the earth and they take imagery and we downlink it down through our ground terminals and we produce images and send them out either electronically or on hard physical media. So what happens in the image collection process is that the satellite gets tasks, we capture the image and then we as the satellite goes across the ground terminal we downlink it, we back hard over our data connections to our production facility in Thornton. The operators produce the imagery perform any post capture image processing algorithms and then we burn it to media or ship it electronically to our end users and in my role with the data warehouse team, what I do is provide business matrix on how fast we are doing that, how accurately we are doing it, how much revenue we are bringing in what expenses we are running into and basically allows the executives insight into how they can optimize resources and revenue."
Views: 191 DesignMind
Spatio-Temporal Networks: Analyzing Change Across Time and Place
 
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Organizations are generating powerful insights by analyzing change in spatio-temporal networks in many applications, such as weather risk analysis. The rapid growth in size, variety and update rate of spatio-temporal data is creating new challenges and opportunities to efficiently store, validate, process and analyze spatio-temporal networks with large time-series data. Join us for a review of the challenges and trends in big data analytics for spatio-temporal networks. You will see a proof-of-concept application for historical tornado event risk analysis that is implemented using the Pitney Bowes® Spectrum™ Technology Platform software for configuring and running batch job and real-time web services integrated with R Density based Spatial Clustering and SQL Server Spatial. Pitney Bowes Spectrum™ Spatial for Business Intelligence software is used to provide a web-based map viewer to analyze and visualize tornado event spatial clusters over time, as well as the magnitude of and property damage caused by tornado events through surface density mapping.
Views: 2273 Pitney Bowes
Geospatial Analysis with Python
 
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Data comes in all shapes and sizes and often government data is geospatial in nature. Often times data science programs & tutorials ignore how to work with this rich data to make room for more advanced topics. Our MinneMUDAC competition heavily utilized geospatial data but was processed to provide students a more familiar format. But as good scientists, we should use primary sources of information as often as possible. Come to this talk to get a basic understanding of how to read, write, query and perform simple geospatial calculations on Minnesota Tax shapefiles with Python. As always data & code will be provided. https://github.com/SocialDataSci/Geospatial_Data_with_Python @dreyco676 https://www.linkedin.com/in/johnhogue/
Views: 12762 Rogue Hogue
Geospatial Big Data: Leveraging Location Analytics
 
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Organizations that collect and maintain geospatial data relating to their operations can benefit from location analytics. By applying advanced spatial analysis to these data sets, organizations can answer complex location-specific questions relating to nearly every aspect of their daily operations, and in some cases, predict the likelihood of future events.
Introduction to Datawarehouse in hindi | Data warehouse and data mining Lectures
 
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#datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 298819 Last moment tuitions
Improving Traffic Prediction Using Weather Data - Ramya Raghavendra
 
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"As common sense would suggest, weather has a definite impact on traffic. But how much? And under what circumstances? Can we improve traffic (congestion) prediction given weather data? Predictive traffic is envisioned to significantly impact how driver’s plan their day by alerting users before they travel, find the best times to travel, and over time, learn from new IoT data such as road conditions, incidents, etc. This talk will cover the traffic prediction work conducted jointly by IBM and the traffic data provider. As a part of this work, we conducted a case study over five large metropolitans in the US, 2.58 billion traffic records and 262 million weather records, to quantify the boost in accuracy of traffic prediction using weather data. We will provide an overview of our lambda architecture with Apache Spark being used to build prediction models with weather and traffic data, and Spark Streaming used to score the model and provide real-time traffic predictions. This talk will also cover a suite of extensions to Spark to analyze geospatial and temporal patterns in traffic and weather data, as well as the suite of machine learning algorithms that were used with Spark framework. Initial results of this work were presented at the National Association of Broadcasters meeting in Las Vegas in April 2017, and there is work to scale the system to provide predictions in over a 100 cities. Audience will learn about our experience scaling using Spark in offline and streaming mode, building statistical and deep-learning pipelines with Spark, and techniques to work with geospatial and time-series data. Session hashtag: #EUent7"
Views: 1408 Databricks
An Extensibility Approach for Spatio-temporal Stream Processing using Microsoft StreamInsight
 
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This video demonstrates how we leveraged the extensibility framework of Microsoft StreamInsight to implement spatial queries (KNN and range query) over streaming geographic data.
Views: 412 jeremiahdmiller
Geospatial Imagery, Feature and Elevation Data Products
 
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Harris is a leader in providing Geospatial products and analysis.
Views: 1134 Harris Corporation
Range Types and Temporal: Past, Present, and Future
 
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Range Types and Temporal: Past, Present, and Future Range Types didn't exist before, why do we need them now? How do they work? Why is "Temporal" important if we already have timestamps? How do we apply these concepts before deploying PostgreSQL 9.2? What's left to be done, and what solutions are in the works? I'll be asking the audience these questions, so -- Err... I mean: I will be answering these questions during the talk. Extensions, changes to core postgresql, and future ideas will be described in the context of solving a simple use case from 2006. These ideas build up to the larger point that powerful types are important, and database systems should do more to support them.
Views: 875 Andrea Ross
Interactive Data Visualization for Spatial Analysis
 
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Data visualization helps us explore and summarize data, interpret and investigate analysis results, and communicate interesting findings. This video  illustrates just a few ways that we can use various data visualization techniques to explore, analyze, and display our spatial data. This video is featured in The ArcGIS Book, 2nd edition found online at thearcgisbook.com.
Views: 1592 ArcGIS
Clustering using OPTICS by MAQ Software - Power BI Visual Introduction
 
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Download free on AppSource: https://appsource.microsoft.com/en-us/product/power-bi-visuals/WA104381463 Clustering using OPTICS by MAQ Software analyzes and identifies data clusters. The algorithm relies on density-based clustering, allowing users to identify outlier points and closely-knit groups within larger groups. This visual includes adjustable clustering parameters to control hierarchy depth and cluster sizes. R package dependencies (auto-installed): Dbscan, plotly, ggplot2. Key features: • Data is scaled and pre-processed automatically, eliminating the need to do so externally. • Hover tooltips and zoom effects. • Capability to manually adjust the parameters of the clustering model. For any feature requests or questions about this visual, please send an e-mail to our team at [email protected]
25c3: Mining social contacts with active RFID
 
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Speakers: Ciro Cattuto, Milosch Meriac, aestetix We describe the implementation of a distributed proximity detection firmware for the OpenBeacon RFID platform. We report on experiments performed during conference gatherings, where the new feature of proximity detection was used to mine and expose patterns of social contact. We discuss some properties of the networks of social contact, and show how these networks can be analyzed, visualized, and used to infer the underlying social structure. The SocioPatterns project aims to shed light on patterns and statistical regularities in social dynamics. To date, little quantitative information is available about these patterns, and measuring real-world dynamics is indispensable for obtaining a complete picture. In this talk we focus on social contact between people and describe how the OpenBeacon active RFID platform was used to gather experimental data on social contact at a few conference gatherings. In a variety of contexts, spatial proximity is a good proxy for social interaction. Spatial proximity of persons wearing active RFID tags can be inferred by tracking the location of the tags, and using the position information to decide whether two tags are located nearby. However, locating the tags requires several receiving stations, and contact inference is subjected to errors that limit both its spatial and temporal accuracy. Because of this, we decided to move from contact inference to direct contact detection. We rewrote the firmware of the OpenBeacon tags specifically targeting proximity detection. We are now able to detect proximity between persons with a very good spatial (~1 m) and temporal (~10 s) resolution. We achieve this by operating the RFID devices in a bi-directional fashion, over multiple radio channels. Tags no longer act as simple beacons, emitting signals for the receiving infrastructure. They exchange messages in a peer-to-peer fashion, to sense their neighborhood and assess contact with other tags. The contact events detected by the RFID network are then relayed to the monitoring infrastructure and post-processed. On suitably tuning the system parameters we achieve reliable detection of face-to-face interaction within about 1 m. This allows, for example, to discriminate who is talking with whom in a small crowded room. In this talk we discuss our implementation of the contact detection firmware for OpenBeacon tags. We provide some details on data analysis and on the visualization of the longitudinal contact networks we measure. We report the results of an experiment involving about 100 people at a conference, and discuss some interesting statistical regularities of social contact. We also discuss how contact information and trajectory similarity can be used to infer the structure of the social network underlying the community of monitored persons, and how background information can be integrated into this picture. We close by pointing to future directions for research as well as to mashups with social networking services. More information about the 25th Chaos Communication Congress can be found via the Chaos Communication Congress website: http://bit.ly/25c3_program Source: http://bit.ly/25c3_videos
Views: 968 Christiaan008
International Journal of Database Management Systems ( IJDMS )
 
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ISSN : 0975-5705 (Online); 0975-5985 (Print) http://airccse.org/journal/ijdms/index.html ******************************************************************* Scope & Topics The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Database management systems. Topics of interest include, but are not limited to, the following . Constraint Modelling and Processing . Data and Information Integration & Modelling . Data and Information Networks . Data and Information Privacy and Security . Data and Information Quality . Data and Information Semantics . Data and Information Streams . Data Management in Grid and P2P Systems . Data Mining Algorithms . Data Mining Systems, Data Warehousing, OLAP . Data Structures and Data Management Algorithms . Database and Information System Architecture and Performance . DB Systems & Applications . Digital Libraries . Distributed, Parallel, P2P, and Grid-based Databases . Electronic Commerce and Web Technologies . Electronic Government & eParticipation . Expert Systems and Decision Support Systems . Expert Systems, Decision Support Systems & applications . Information Retrieval and Database Systems . Information Systems . Interoperability . Knowledge Acquisition, discovery & Management . Knowledge and information processing . Knowledge Modelling . Knowledge Processing . Metadata Management . Mobile Data and Information . Multi-databases and Database Federation . Multimedia, Object, Object Relational, and Deductive Databases . Pervasive Data and Information . Process Modelling . Process Support and Automation . Query Processing and Optimization . Semantic Web and Ontologies . Sensor Data Management . Statistical and Scientific Databases . Temporal, Spatial, and High Dimensional Databases . Trust, Privacy & Security in Digital Business . User Interfaces to Databases and Information Systems . Very Large Data Bases . Workflow Management and Databases . WWW and Databases . XML and Databases Paper Submission: Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. Important Dates: Submission Deadline : May 06, 2018 Acceptance Notification : June 06, 2018 Final Manuscript Due : June 14, 2018 Publication Date: Determined by the Editor-in-Chief For other details please visit http://airccse.org/journal/ijdms/index.html
Views: 5 ijsc journal
Andre Panisson: Exploring temporal graph data with Python
 
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PyData NYC 2015 We will see how tensor decompositions can be carried out using Python, how to obtain latent components and how they can be interpreted, and what are some applications in the academy and industry. We will see a use case where tensor decomposition was used to extract structural and temporal signatures from a time-varying social network collected from wearable proximity sensors. Tensor decompositions have gained a steadily increasing popularity in data mining applications. Data sources from sensor networks and Internet-of-Things applications promise a wealth of interaction data that can be naturally represented as multidimensional structures such as tensors. For example, time-varying social networks collected from wearable proximity sensors can be represented as 3-way tensors. By representing this data as tensors, we can use tensor decomposition to extract community structures with their structural and temporal signatures. The current standard framework for working with tensors, however, is Matlab. We will show how tensor decompositions can be carried out using Python, how to obtain latent components and how they can be interpreted, and what are some applications of this technique in the academy and industry. We will see a use case where a Python implementation of tensor decomposition is applied to a dataset that describes social interactions of people, collected using the SocioPatterns platform. This platform was deployed in different settings such as conferences, schools and hospitals, in order to support mathematical modelling and simulation of airborne infectious diseases. Tensor decomposition has been used in these scenarios to solve different types of problems: it can be used for data cleaning, where time-varying graph anomalies can be identified and removed from data; it can also be used to assess the impact of latent components in the spreading of a disease, and to devise intervention strategies that are able to reduce the number of infection cases in a school or hospital. These are just a few examples that show the potential of this technique in data mining and machine learning applications. Slides available here: http://www.slideshare.net/panisson/exploring-temporal-graph-data-with-python-a-study-on-tensor-decomposition-of-wearable-sensor-data Github repo: https://github.com/panisson/ntf-school
Views: 1565 PyData
24 Hours of PASS: EDP 2016 - Temporal Tables and Their Role in ETL and Data Warehouse
 
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Presenter: Reza Rad Moderator: Joseph Barth
Views: 424 PASStv
Making Sense of Temporal Queries with Interactive Visualization
 
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To help analysts better understand temporal queries, we developed StreamTrace, an interactive visualization tool that breaks down how a temporal query processes a given dataset, step-by-step. We demonstrate that StreamTrace can help users to verify that queries behave as expected and to isolate the regions of a query that may be causing unexpected results. http://research.microsoft.com/
Views: 116 Microsoft Research
Big Data and ArcGIS: Large Scale Batch Analytics for Feature and Tabular Data
 
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We will discuss what is being developed to complete batch analysis of feature and tabular data, with a description of the new analytic capabilities, as well as an in-depth discussion on how the solutions were implemented. We will present real world examples and briefly discuss integrated technology components such as underlying storage technology.
Views: 1860 Esri Events
International Journal of Database Management Systems ( IJDMS )
 
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International Journal of Database Management Systems ( IJDMS ) ISSN : 0975-5705 (Online); 0975-5985 (Print) http://airccse.org/journal/ijdms/index.html Scope & Topics The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Database management systems. Topics of interest include, but are not limited to, the following . Constraint Modelling and Processing . Data and Information Integration & Modelling . Data and Information Networks . Data and Information Privacy and Security . Data and Information Quality . Data and Information Semantics . Data and Information Streams . Data Management in Grid and P2P Systems . Data Mining Algorithms . Data Mining Systems, Data Warehousing, OLAP . Data Structures and Data Management Algorithms . Database and Information System Architecture and Performance . DB Systems & Applications . Digital Libraries . Distributed, Parallel, P2P, and Grid-based Databases . Electronic Commerce and Web Technologies . Electronic Government & eParticipation . Expert Systems and Decision Support Systems . Expert Systems, Decision Support Systems & applications . Information Retrieval and Database Systems . Information Systems . Interoperability . Knowledge Acquisition, discovery & Management . Knowledge and information processing . Knowledge Modelling . Knowledge Processing . Metadata Management . Mobile Data and Information . Multi-databases and Database Federation . Multimedia, Object, Object Relational, and Deductive Databases . Pervasive Data and Information . Process Modelling . Process Support and Automation . Query Processing and Optimization . Semantic Web and Ontologies . Sensor Data Management . Statistical and Scientific Databases . Temporal, Spatial, and High Dimensional Databases . Trust, Privacy & Security in Digital Business . User Interfaces to Databases and Information Systems . Very Large Data Bases . Workflow Management and Databases . WWW and Databases . XML and Databases Paper Submission: Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdms/index.html
Views: 7 Ijdms Journal
Configuring and Installing Spatial Warehouse (MS SQL)
 
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Learn how to install and configure GeoSpatial Analysis Spatial Warehouse based on a simple example
Data Visualization Essentials: Identifying Interactivity in the Data Visualizations
 
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This video is a sample from Skillsoft's video course catalog. After watching it, you will be able to identify the types of interactivity and if they are required in the data visualization. Joe Khoury is a Professional Engineer, IT Consultant, and Entrepreneur. As a professional engineer, he has logged over 8000 hours managing projects. Driven by entrepreneurial motivation, Mr. Khoury has founded and sold two IT-based businesses and has been involved in the elearning market for the better part of 12 years. Mr. Khoury writes for an IT-based elearning blog and is a published author for the IEEE. He often speaks at IT conferences on technology-based subjects globally. Skillsoft is a pioneer in the field of learning with a long history of innovation. Skillsoft provides cloud-based learning solutions for our customers worldwide, who range from global enterprises, government and education customers to mid-sized and small businesses. Learn more at http://www.skillsoft.com. https://www.linkedin.com/company/skillsoft http://www.twitter.com/skillsoft https://www.facebook.com/skillsoft
Views: 11522 Skillsoft YouTube
International Journal of Database Management Systems ( IJDMS )
 
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International Journal of Database Management Systems ( IJDMS ) ISSN : 0975-5705 (Online); 0975-5985 (Print) http://airccse.org/journal/ijdms/index.html ******************************************************************* Scope & Topics The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Database management systems. Topics of interest include, but are not limited to, the following . Constraint Modelling and Processing . Data and Information Integration & Modelling . Data and Information Networks . Data and Information Privacy and Security . Data and Information Quality . Data and Information Semantics . Data and Information Streams . Data Management in Grid and P2P Systems . Data Mining Algorithms . Data Mining Systems, Data Warehousing, OLAP . Data Structures and Data Management Algorithms . Database and Information System Architecture and Performance . DB Systems & Applications . Digital Libraries . Distributed, Parallel, P2P, and Grid-based Databases . Electronic Commerce and Web Technologies . Electronic Government & eParticipation . Expert Systems and Decision Support Systems . Expert Systems, Decision Support Systems & applications . Information Retrieval and Database Systems . Information Systems . Interoperability . Knowledge Acquisition, discovery & Management . Knowledge and information processing . Knowledge Modelling . Knowledge Processing . Metadata Management . Mobile Data and Information . Multi-databases and Database Federation . Multimedia, Object, Object Relational, and Deductive Databases . Pervasive Data and Information . Process Modelling . Process Support and Automation . Query Processing and Optimization . Semantic Web and Ontologies . Sensor Data Management . Statistical and Scientific Databases . Temporal, Spatial, and High Dimensional Databases . Trust, Privacy & Security in Digital Business . User Interfaces to Databases and Information Systems . Very Large Data Bases . Workflow Management and Databases . WWW and Databases . XML and Databases Paper Submission: Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdms/index.html
Bitemp 2.0 - The hype, the barriers and the actions to take
 
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Craig Baumunk from BitemporalData.com speaks about second generation bitemporal data solutions at the STAC(r) Analytics Technology Conference on June 13, 2011 in New York (www.STACresearch.com/june13atc). STAC (the Securities Technology Analysis Center) facilitates the STAC Benchmark Council, a group of financial trading firms and technology vendors (www.STACresearch.com/members) that defines standard performance benchmarks for high-performance technology and otherwise facilitates substantive information exchange between technology providers and users. Video is posted with the permission of STAC.
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Performing Text Analytics in OBIEE using Oracle Database (V309)
 
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How to consume Oracle Database's text processing capabilities to deliver powerful analytical capabilities in OBIEE.
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International Journal of Database Management Systems ( IJDMS )
 
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International Journal of Database Management Systems ( IJDMS ) ISSN : 0975-5705 (Online); 0975-5985 (Print) http://airccse.org/journal/ijdms/index.html ******************************************************************* Scope & Topics The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Database management systems. Topics of interest include, but are not limited to, the following . Constraint Modelling and Processing . Data and Information Integration & Modelling . Data and Information Networks . Data and Information Privacy and Security . Data and Information Quality . Data and Information Semantics . Data and Information Streams . Data Management in Grid and P2P Systems . Data Mining Algorithms . Data Mining Systems, Data Warehousing, OLAP . Data Structures and Data Management Algorithms . Database and Information System Architecture and Performance . DB Systems & Applications . Digital Libraries . Distributed, Parallel, P2P, and Grid-based Databases . Electronic Commerce and Web Technologies . Electronic Government & eParticipation . Expert Systems and Decision Support Systems . Expert Systems, Decision Support Systems & applications . Information Retrieval and Database Systems . Information Systems . Interoperability . Knowledge Acquisition, discovery & Management . Knowledge and information processing . Knowledge Modelling . Knowledge Processing . Metadata Management . Mobile Data and Information . Multi-databases and Database Federation . Multimedia, Object, Object Relational, and Deductive Databases . Pervasive Data and Information . Process Modelling . Process Support and Automation . Query Processing and Optimization . Semantic Web and Ontologies . Sensor Data Management . Statistical and Scientific Databases . Temporal, Spatial, and High Dimensional Databases . Trust, Privacy & Security in Digital Business . User Interfaces to Databases and Information Systems . Very Large Data Bases . Workflow Management and Databases . WWW and Databases . XML and Databases Paper Submission: Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. Important Dates: Submission Deadline : January 06, 2018 Acceptance Notification : February 06, 2018 Final Manuscript Due : February 08, 2018 Publication Date: Determined by the Editor-in-Chief For other details please visit http://airccse.org/journal/ijdms/index.html
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Interactive 3D Visual Analytics - Victorian Road Accident Data
 
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The passed few months, a development team at Deakin University has been constructing a new way to approach visualization. Using Road Accident data from Victoria, Australia, the team have been able to represent the data in a three-dimensional environment, using dynamic methods to display and navigate the data. ****** All music in the video is completely accredited to the named artists *****
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International Journal of Database Management Systems ( IJDMS )
 
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International Journal of Database Management Systems ( IJDMS ) ISSN : 0975-5705 (Online); 0975-5985 (Print) http://airccse.org/journal/ijdms/index.html Scope & Topics The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Database management systems. Topics of interest include, but are not limited to, the following . Constraint Modelling and Processing . Data and Information Integration & Modelling . Data and Information Networks . Data and Information Privacy and Security . Data and Information Quality . Data and Information Semantics . Data and Information Streams . Data Management in Grid and P2P Systems . Data Mining Algorithms . Data Mining Systems, Data Warehousing, OLAP . Data Structures and Data Management Algorithms . Database and Information System Architecture and Performance . DB Systems & Applications . Digital Libraries . Distributed, Parallel, P2P, and Grid-based Databases . Electronic Commerce and Web Technologies . Electronic Government & eParticipation . Expert Systems and Decision Support Systems . Expert Systems, Decision Support Systems & applications . Information Retrieval and Database Systems . Information Systems . Interoperability . Knowledge Acquisition, discovery & Management . Knowledge and information processing . Knowledge Modelling . Knowledge Processing . Metadata Management . Mobile Data and Information . Multi-databases and Database Federation . Multimedia, Object, Object Relational, and Deductive Databases . Pervasive Data and Information . Process Modelling . Process Support and Automation . Query Processing and Optimization . Semantic Web and Ontologies . Sensor Data Management . Statistical and Scientific Databases . Temporal, Spatial, and High Dimensional Databases . Trust, Privacy & Security in Digital Business . User Interfaces to Databases and Information Systems . Very Large Data Bases . Workflow Management and Databases . WWW and Databases . XML and Databases Paper Submission: Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdms/index.html
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Nathalie Henry Riche: Researchers developing new ways to visualize complex data
 
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Data-driven storytelling is becoming more pervasive with the help of sophisticated visualization tools. Tools that allow us to visualize complex data add more than decoration to our work, says Microsoft researcher Nathalie Riche. “Visualization helps you answer questions you did not even know you had. So it’s about generating hypotheses,” Riche said during her presentation at this year’s Women in Data Science conference at Stanford University. “Of course, you still need statistics and all those complex algorithms to actually answer those questions and really know if this is significant or not. The pattern is in the data,” she says. As an example, Riche showed a table containing four series of numbers. When computing basic statistics about the numbers using measures like standard deviation and regression, they appear to be equivalent and it would appear that the x and y coordinates are essentially the same. Yet when plugged into a basic visualization tool, it’s apparent that they are not. The tool Riche used in her demonstration is decades old. But her research is aimed at laying the groundwork for the development of advanced visualization applications that are simple enough to include in programs like Excel or the more sophisticated Power BI, she says. A tool in Excel called Power Map allows users to plot geographic and temporal data on a representation of a 3D globe or a custom map. A new custom visualization tool in Power BI lets a user animate each data point in a set of data. And Microsoft researchers are currently exploring ways to use virtual reality to visualize data in 3D, Riche says. Data visualization is a powerful way to tell stories, Riche says. “You can actually communicate a message very effectively with visualization. And in fact, those stories with data are everywhere.” As part of their research, Riche and her colleagues look for the most effective way to tell a story with visualization.
International Journal of Database Management Systems ( IJDMS )
 
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International Journal of Database Management Systems ( IJDMS ) ISSN : 0975-5705 (Online); 0975-5985 (Print) http://airccse.org/journal/ijdms/index.html Scope & Topics The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Database management systems. Topics of interest include, but are not limited to, the following . Constraint Modelling and Processing . Data and Information Integration & Modelling . Data and Information Networks . Data and Information Privacy and Security . Data and Information Quality . Data and Information Semantics . Data and Information Streams . Data Management in Grid and P2P Systems . Data Mining Algorithms . Data Mining Systems, Data Warehousing, OLAP . Data Structures and Data Management Algorithms . Database and Information System Architecture and Performance . DB Systems & Applications . Digital Libraries . Distributed, Parallel, P2P, and Grid-based Databases . Electronic Commerce and Web Technologies . Electronic Government & eParticipation . Expert Systems and Decision Support Systems . Expert Systems, Decision Support Systems & applications . Information Retrieval and Database Systems . Information Systems . Interoperability . Knowledge Acquisition, discovery & Management . Knowledge and information processing . Knowledge Modelling . Knowledge Processing . Metadata Management . Mobile Data and Information . Multi-databases and Database Federation . Multimedia, Object, Object Relational, and Deductive Databases . Pervasive Data and Information . Process Modelling . Process Support and Automation . Query Processing and Optimization . Semantic Web and Ontologies . Sensor Data Management . Statistical and Scientific Databases . Temporal, Spatial, and High Dimensional Databases . Trust, Privacy & Security in Digital Business . User Interfaces to Databases and Information Systems . Very Large Data Bases . Workflow Management and Databases . WWW and Databases . XML and Databases Paper Submission Authors are invited to submit papers for this journal through e-mail [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdms/index.html
Views: 17 Ijdms Journal
GSTAT Software Solutions
 
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GSTAT software solutions enable B2C companies (Banks, Telecom companies, Retailers) to maximize their revenues from their customers, by identifying for each customer the right Next Best Offers/Actions and most optimal retention offers. GSTAT software solutions are based on fully automatic data management and predictive analytics processes, which marketers can operate in minutes, instead of weeks to months (using classic data-mining tools in the market) for developing and deploying up to hundreds of cross/up-sell, churn prediction and retention optimization predictive analytics models. For more information, contact us at www.g-stat.com .
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Big Spatial Data seminar Part 1 - Rahul Ramachandran
 
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Big Spatial Data seminar - Rahul Ramachandran - University of Alabama - July 25th 2013. Rahul discusses their NASA ACCESS funded online tool: Curated Data Albums, an online tool for gathering and presenting relevant data and information from distributed sources. These Data Albums are complied collections of information related to events with links to relevant data files (granular) from different instruments
International Journal of Database Management Systems ( IJDMS )
 
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International Journal of Database Management Systems ( IJDMS ) ISSN : 0975-5705 (Online); 0975-5985 (Print) http://airccse.org/journal/ijdms/index.html Scope & Topics The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Database management systems. Topics of interest include, but are not limited to, the following . Constraint Modelling and Processing . Data and Information Integration & Modelling . Data and Information Networks . Data and Information Privacy and Security . Data and Information Quality . Data and Information Semantics . Data and Information Streams . Data Management in Grid and P2P Systems . Data Mining Algorithms . Data Mining Systems, Data Warehousing, OLAP . Data Structures and Data Management Algorithms . Database and Information System Architecture and Performance . DB Systems & Applications . Digital Libraries . Distributed, Parallel, P2P, and Grid-based Databases . Electronic Commerce and Web Technologies . Electronic Government & eParticipation . Expert Systems and Decision Support Systems . Expert Systems, Decision Support Systems & applications . Information Retrieval and Database Systems . Information Systems . Interoperability . Knowledge Acquisition, discovery & Management . Knowledge and information processing . Knowledge Modelling . Knowledge Processing . Metadata Management . Mobile Data and Information . Multi-databases and Database Federation . Multimedia, Object, Object Relational, and Deductive Databases . Pervasive Data and Information . Process Modelling . Process Support and Automation . Query Processing and Optimization . Semantic Web and Ontologies . Sensor Data Management . Statistical and Scientific Databases . Temporal, Spatial, and High Dimensional Databases . Trust, Privacy & Security in Digital Business . User Interfaces to Databases and Information Systems . Very Large Data Bases . Workflow Management and Databases . WWW and Databases . XML and Databases Paper Submission: Authors are invited to submit papers for this journal through e-mail [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdms/index.html
Views: 14 Ijdms Journal
International Journal of Database Management Systems ( IJDMS )
 
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International Journal of Database Management Systems ( IJDMS ) ISSN : 0975-5705 (Online); 0975-5985 (Print) http://airccse.org/journal/ijdms/index.html Scope & Topics The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Database management systems. Topics of interest include, but are not limited to, the following • Constraint Modelling and Processing • Data and Information Integration & Modelling • Data and Information Networks • Data and Information Privacy and Security • Data and Information Quality • Data and Information Semantics • Data and Information Streams • Data Management in Grid and P2P Systems • Data Mining Algorithms • Data Mining Systems, Data Warehousing, OLAP • Data Structures and Data Management Algorithms • Database and Information System Architecture and Performance • DB Systems & Applications • Digital Libraries • Distributed, Parallel, P2P, and Grid-based Databases • Electronic Commerce and Web Technologies • Electronic Government & eParticipation • Expert Systems and Decision Support Systems • Expert Systems, Decision Support Systems & applications • Information Retrieval and Database Systems • Information Systems • Interoperability • Knowledge Acquisition, discovery & Management • Knowledge and information processing • Knowledge Modelling • Knowledge Processing • Metadata Management • Mobile Data and Information • Multi-databases and Database Federation • Multimedia, Object, Object Relational, and Deductive Databases • Pervasive Data and Information • Process Modelling • Process Support and Automation • Query Processing and Optimization • Semantic Web and Ontologies • Sensor Data Management • Statistical and Scientific Databases • Temporal, Spatial, and High Dimensional Databases • Trust, Privacy & Security in Digital Business • User Interfaces to Databases and Information Systems • Very Large Data Bases • Workflow Management and Databases • WWW and Databases • XML and Databases Paper submission: Authors are invited to submit papers for this journal through e-mail [email protected] or [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdms/index.html
Views: 115 Ijdms Journal
International Journal of Database Management Systems IJDMS
 
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International Journal of Database Management Systems ( IJDMS ) ISSN : 0975-5705 (Online); 0975-5985 (Print) http://airccse.org/journal/ijdms/index.html Scope & Topics The International Journal of Database Management Systems (IJDMS) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the database management systems & its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern developments in this filed, and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Database management systems. Topics of interest include, but are not limited to, the following . Constraint Modelling and Processing . Data and Information Integration & Modelling . Data and Information Networks . Data and Information Privacy and Security . Data and Information Quality . Data and Information Semantics . Data and Information Streams . Data Management in Grid and P2P Systems . Data Mining Algorithms . Data Mining Systems, Data Warehousing, OLAP . Data Structures and Data Management Algorithms . Database and Information System Architecture and Performance . DB Systems & Applications . Digital Libraries . Distributed, Parallel, P2P, and Grid-based Databases . Electronic Commerce and Web Technologies . Electronic Government & eParticipation . Expert Systems and Decision Support Systems . Expert Systems, Decision Support Systems & applications . Information Retrieval and Database Systems . Information Systems . Interoperability . Knowledge Acquisition, discovery & Management . Knowledge and information processing . Knowledge Modelling . Knowledge Processing . Metadata Management . Mobile Data and Information . Multi-databases and Database Federation . Multimedia, Object, Object Relational, and Deductive Databases . Pervasive Data and Information . Process Modelling . Process Support and Automation . Query Processing and Optimization . Semantic Web and Ontologies . Sensor Data Management . Statistical and Scientific Databases . Temporal, Spatial, and High Dimensional Databases . Trust, Privacy & Security in Digital Business . User Interfaces to Databases and Information Systems . Very Large Data Bases . Workflow Management and Databases . WWW and Databases . XML and Databases Paper Submission: Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Sequence 014 1 mining
 
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