Results 151 to 160 of about 6,427,696 (199)
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ACM SIGGROUP Bulletin, 2003
Data are a fundamental component of science and engineering work, and the ability to share data is critical to the validation and progress of science. Data sharing and reuse in some fields, however, has proven to be a difficult problem. This paper argues that the development of effective CSCW systems to support data sharing in work groups requires a ...
Jeremy P. Birnholtz, Matthew J. Bietz
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Data are a fundamental component of science and engineering work, and the ability to share data is critical to the validation and progress of science. Data sharing and reuse in some fields, however, has proven to be a difficult problem. This paper argues that the development of effective CSCW systems to support data sharing in work groups requires a ...
Jeremy P. Birnholtz, Matthew J. Bietz
openaire +2 more sources
2019
Machine learning applications run on data. One of the main activities when building a machine learning application is to collate from different data sources, store in an effective format, and transform of raw data into formats that are appropriate for the machine learning app. Data can come in different formats.
Paul D. McNicholas, Peter A. Tait
+4 more sources
Machine learning applications run on data. One of the main activities when building a machine learning application is to collate from different data sources, store in an effective format, and transform of raw data into formats that are appropriate for the machine learning app. Data can come in different formats.
Paul D. McNicholas, Peter A. Tait
+4 more sources
2002
Vector data model is used for representation of geographic phenomena as geometric objects composed of points, lines and areas. Lines are used for roads, railroads, streams, or utility networks, while areas can represent soil types, land use categories, lakes, or zoning in urban areas. Vector data are stored using their coordinates.
Markus Neteler, Helena Mitasova
openaire +1 more source
Vector data model is used for representation of geographic phenomena as geometric objects composed of points, lines and areas. Lines are used for roads, railroads, streams, or utility networks, while areas can represent soil types, land use categories, lakes, or zoning in urban areas. Vector data are stored using their coordinates.
Markus Neteler, Helena Mitasova
openaire +1 more source
2002
Raster data, stored in GRASS as a matrix of values, represent either a continuous field (surface), an image, or geometric objects (points, lines, areas) corresponding to discrete fields (Figure 5.1). For surfaces, the values in the matrix are assigned to the center points of grid cells.
Markus Neteler, Helena Mitasova
openaire +1 more source
Raster data, stored in GRASS as a matrix of values, represent either a continuous field (surface), an image, or geometric objects (points, lines, areas) corresponding to discrete fields (Figure 5.1). For surfaces, the values in the matrix are assigned to the center points of grid cells.
Markus Neteler, Helena Mitasova
openaire +1 more source
2007
Software applications deal with data in a wide array of forms: single values such as integers or strings; composite values paired together as tuples, records, or objects; collections of smaller pieces of data represented as lists, sets, arrays, or sequences; XML strings with tags describing the shape and kind of data; or data coming from relational or ...
Don Syme +2 more
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Software applications deal with data in a wide array of forms: single values such as integers or strings; composite values paired together as tuples, records, or objects; collections of smaller pieces of data represented as lists, sets, arrays, or sequences; XML strings with tags describing the shape and kind of data; or data coming from relational or ...
Don Syme +2 more
openaire +2 more sources
2011
Data is the starting point for all data mining—without it there is nothing to mine. In today's world, there is certainly no shortage of data, but turning that data into information, knowledge, and, eventually, wisdom is not a simple matter. We often think of data as being numbers or categories.
+5 more sources
Data is the starting point for all data mining—without it there is nothing to mine. In today's world, there is certainly no shortage of data, but turning that data into information, knowledge, and, eventually, wisdom is not a simple matter. We often think of data as being numbers or categories.
+5 more sources
2013
Data handling techniques in applications have evolved over the years. You have the traditional set up of posting the form data to the server and loading a new page with data as response. With the advent of AJAX, you can send the request and load raw data as response.
David Hows +3 more
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Data handling techniques in applications have evolved over the years. You have the traditional set up of posting the form data to the server and loading a new page with data as response. With the advent of AJAX, you can send the request and load raw data as response.
David Hows +3 more
openaire +2 more sources
2020
This text is designed to give you insight into real-world statistical methods. Unlike many “classroom-ready” examples, real-world data often require advance work before any statistics ever occurs. In this chapter, you will learn how to use the data.table [9] and extraoperators [20] packages to create the data sets you need for applying statistical ...
Matt Wiley, Joshua F. Wiley
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This text is designed to give you insight into real-world statistical methods. Unlike many “classroom-ready” examples, real-world data often require advance work before any statistics ever occurs. In this chapter, you will learn how to use the data.table [9] and extraoperators [20] packages to create the data sets you need for applying statistical ...
Matt Wiley, Joshua F. Wiley
openaire +1 more source