The data provides a summary of the state of development practice for Geographic Information Systems (GIS) software (as of August 2017). The summary is based on grading a set of 30 GIS products using a template of 56 questions based on 13 software qualities. The products range in scope and purpose from a complete desktop GIS systems, to stand-alone tools, to programming libraries/packages.

The template used to grade the software is found in the TabularSummaries.zip file. Each quality is measured with a series of questions. For unambiguity the responses are quantified wherever possible (e.g.~yes/no answers). The goal is for measures that are visible, measurable and feasible in a short time with limited domain knowledge. Unlike a comprehensive software review, this template does not grade on functionality and features. Therefore, it is possible that a relatively featureless product can outscore a feature-rich product.

A virtual machine is used to provide an optimal testing environments for each software product. During the process of grading the 30 software products, it is much easier to create a new virtual machine to test the software on, rather than using the host operating system and file system.

The raw data obtained by measuring each software product is in SoftwareGrading-GIS.xlsx. Each line in this file corresponds to between 2 and 4 hours of measurement time by a software engineer. The results are summarized for each quality in the TabularSummaries.zip file, as a tex file and compiled pdf file.

The primary intent of this workshop is to provide practical training in using Statistics Canada geography files with the leading industry standard software: Environmental Systems Research Institute, Inc.(ESRI) ArcGIS 9x. Participants will be introduced to the key features of ArcGIS 9x, as well as to geographic concepts and principles essential to understanding and working with geographic information systems (GIS) software. The workshop will review a range of geography and attribute files available from Statistics Canada, as well as some best practices for accessing this information. A brief overview of complementary data sets available from federal and provincial agencies will be provided. There will also be an opportunity to complete a practical exercise using ArcGIS9x. (Note: Data associated with this presentation is available on the DLI FTP site under folder 1873-221.)

In this blog I’ll share the workflow and tools used in the GIS part of this analysis. To understand where crashes are occurring, first the dataset had to be mapped. The software of choice in this instance was ArcGIS, though most of the analysis could have been done using QGIS. Heat maps are all the rage, and if you want to make simple heat maps for free and you appreciate good documentation, I recommend the QGIS Heatmap plugin. There are also some great tools in the free open-source program GeoDa for spatial statistics.

Update: We updated the data set in March 2022 by adding newly published papers and by providing more insights on how we analyzed them. Details can be found in the file " SEnti-SMS.xlsx".

Update: The updated version (-v2) contains the results of one more snowballing iteration and extracted information on the accuracy of the used methods.

In 2020, we conducted a systematic literature review to explore the development and application of sentiment analysis tools in software engineering.

Information on the execution of the SLR, its scope, the search string, etc. are presented in the paper linked below.

The USDA Long-Term Agroecosystem Research was established to develop national strategies for sustainable intensification of agricultural production. As part of the Agricultural Research Service, the LTAR Network incorporates numerous geographies consisting of experimental areas and locations where data are being gathered. Starting in early 2019, two working groups of the LTAR Network (Remote Sensing and GIS, and Data Management) set a major goal to jointly develop a geodatabase of LTAR Standard GIS Data Layers. The purpose of the geodatabase was to enhance the Network's ability to utilize coordinated, harmonized datasets and reduce redundancy and potential errors associated with multiple copies of similar datasets. Project organizers met at least twice with each of the 18 LTAR sites from September 2019 through December 2020, compiling and editing a set of detailed geospatial data layers comprising a geodatabase, describing essential data collection areas within the LTAR Network. The LTAR Standard GIS Data Layers geodatabase consists of geospatial data that represent locations and areas associated with the LTAR Network as of late 2020, including LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This geodatabase was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. The creation of the geodatabase began with initial requests to LTAR site leads and data managers for geospatial data, followed by meetings with each LTAR site to review the initial draft. Edits were documented, and the final draft was again reviewed and certified by LTAR site leads or their delegates. Revisions to this geodatabase will occur biennially, with the next revision scheduled to be published in 2023. Resources in this dataset:Resource Title: LTAR Standard GIS Data Layers, 2020 version, File Geodatabase. File Name: LTAR_Standard_GIS_Layers_v2020.zipResource Description: This file geodatabase consists of authoritative GIS data layers of the Long-Term Agroecosystem Research Network. Data layers include: LTAR site locations, LTAR site points of contact and street addresses, LTAR experimental boundaries, LTAR site "legacy region" boundaries, LTAR eddy flux tower locations, and LTAR phenocam locations.Resource Software Recommended: ArcGIS,url: esri.com Resource Title: LTAR Standard GIS Data Layers, 2020 version, GeoJSON files. File Name: LTAR_Standard_GIS_Layers_v2020_GeoJSON_ADC.zipResource Description: The contents of the LTAR Standard GIS Data Layers includes geospatial data that represent locations and areas associated with the LTAR Network as of late 2020. This collection of geojson files includes spatial data describing LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This dataset was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. Resource Software Recommended: QGIS,url: https://qgis.org/en/site/

This data corresponds to the information extracted from the studies of a systematic mapping in the adaptive monitoring topic, used for answering the research questions of the review. Data is grouped by study (or resource) and by approach.

Abstract Progress in software engineering requires (1) more empirical studies of quality, (2) increased focus on synthesizing evidence, (3) more theories to be built and tested, and (4) the validity of the experiment is directly related with the level of confidence in the process of experimental investigation. This paper presents the results of a qualitative and quantitative classification of the threats to the validity of software engineering experiments comprising a total of 92 articles published in the period 2001-2015, dealing with software testing of Web applications. Our results show that 29.4% of the analyzed articles do not mention any threats to validity, 44.2% do it briefly, and 14% do it judiciously; that leaves a question: these studies have scientific value?

Purpose: The mission of the Geometric Design Laboratory (GDL) is to support the Office of Safety Research and Development in research related to the geometric design of roadways and the impacts on safety. The GDL provides technical support to develop, maintain, and enhance tools for the safety evaluation of highway geometric design alternatives. This includes coordination of the Highway Safety Manual (HSM) with related tools, e.g., the Interactive Highway Safety Design Model (IHSDM) and SafetyAnalyst. The GDL supports the HSM through implementation of HSM methods in IHSDM software; by providing technical support to HSM users; by performing HSM-related technology facilitation; and by conducting HSM-related training and research.The GDL also contributes to Federal Highway Administration's (FHWA's) Roadway Safety Data Program (RSDP) initiatives to advance State and local safety data systems and safety data analyses by supporting the use of Geographic Information Systems (GIS) for advancing the quantification of highway safety (e.g., through the integration of GIS with highway safety analysis tools); and supports the Safety Training and Analysis Center (STAC) in its mission to assist the research community and State departments of transportation (DOTs) in using data from the second Strategic Highway Research Program's (SHRP2) Naturalistic Driving Study (NDS) and Roadway Information Database (RID).Laboratory Description: GDL staff focuses on the following tasks.Research: Support IHSDM, Highway Safety Manual, and other highway safety-related research efforts.Software Development: Support the full life cycle of IHSDM software development, including developing functional specifications; performing verification and validation of the models that are core IHSDM components; providing recommendations to the IHSDM software developer on all facets of the software (e.g., the graphical user interface, output/reporting); preparing IHSDM documentation; performing alpha testing of IHSDM software; and coordinating the beta testing of IHSDM software by end users. The GDL also helps coordinate the interaction of key players in IHSDM software development, including research contractors, software developers, end users, and commercial computer-aided design (CAD)/roadway design software vendors.Technology Facilitation: Support technology facilitation for the IHSDM and HSM. The GDL provides the sole source of technical support to IHSDM users and provides technical support to HSM users. GDL markets IHSDM and HSM to decisionmakers and potential end users, and participates in developing and delivering IHSDM/HSM training.Laboratory Capabilities: The staff of the GDL includes professionals with expertise in transportation engineering and familiarity with software development, which allows the GDL to support IHSDM development in various ways and to assume a unique coordination role. The GDL's transportation engineering expertise supports the laboratory's function of reviewing and assisting the development of the engineering models included in IHSDM for evaluating the safety of roadway designs. By combining transportation engineering and software development expertise, the GDL has the unique ability to evaluate software from both the software developer and end-user perspective.Communications and engineering skills help GDL staff to understand the needs of the audience (e.g., design engineers), thereby supporting effective technical assistance to end users.IHSDM development is a long-term effort, involving many research contractors, software developers, and FHWA staff. In addition, FHWA seeks input from end users and user organizations to help ensure that IHSDM is responsive to user needs. The staff of the GDL helps coordinate the interaction of all those involved with IHSDM development.Staff at the GDL participates in HSM development and technology facilitation. In addition, the IHSDM Crash Prediction Module is a faithful implementation of HSM Part C (Predictive Method). Therefore, GDL staff is well equipped to support HSM-related activities.Laboratory Equipment: The GDL is equipped with computer hardware and software typically employed by users of IHSDM, including commercial CAD/roadway design software.Laboratory Services: The GDL supports the HSM through implementation of HSM methods in IHSDM software; by providing technical support to HSM users; by performing HSM-related technology facilitation; and by conducting HSM-related research.To develop and promote IHSDM, GDL staff provides or has provided the following services:For all IHSDM safety evaluation modules (Crash Prediction, Design Consistency, Intersection Review, Policy Review, Traffic Analysis and Driver/Vehicle), the GDL conducts software testing to verify, validate, and evaluate the IHSDM software system and develops and/or finalizes the software's functional specifications.Participates in development and delivery of IHSDM training.Provides the sole source of technical assistance to IHSDM users ( ihsdm.support@dot.gov; 202-493-3407).Supports coordination and integration of IHSDM with civil design software packages.Develops, reviews, maintains, and enhances documentation for IHSDM users.Conducts technical reviews and prepares review comments on contract research deliverables.Provides technical support in the development, production, and dissemination of IHSDM-related marketing materials.Provides technical content for the IHSDM Web site.The GDL also contributes to FHWA Roadway Safety Data Program (RSDP) initiatives to advance State and local safety data systems and safety data analyses by supporting the use of GIS for advancing the quantification of highway safety; e.g., through the integration of GIS with highway safety analysis tools (including extraction of data from GIS for input to safety analyses and representation of safety analysis results in the GIS environment). Such contributions support efforts by State and local agencies to:Extract roadway geometrics from GIS/GPS data.Develop GIS-based tools for collecting roadway inventory data.Process data gathered using instrumented vehicles (e.g., LiDAR).Leverage GIS/GPS data for populating safety databases and performing safety analyses (e.g., safety management - HSM Part B, and crash prediction - HSM Part C). The GDL supports the Safety Training and Analysis Center (STAC) in assisting the research community and State DOTs in using data from the SHRP2 Naturalistic Driving Study (NDS) and Roadway Information Database (RID); e.g., by assessing analytical possibilities associated with GIS data linkages to the RID.

Replication package of the study "Grey Literature in Software Engineering: A Critical Review" published in Information and Software Technology (IST).

Context: Software defect prediction is a trending research topic, and a wide variety of the published papers focus on coding phase or after. A limited number of papers, however, includes the prior (early) phases of the software development lifecycle (SDLC). Objective: The goal of this study is to obtain a general view of the characteristics and usefulness of Early Software Defect Prediction (ESDP) models reported in scientific literature. Method: A systematic mapping and systematic literature review study has been conducted. We searched for the studies reported between 2000 and 2016. We reviewed 52 studies and analyzed the trend and demographics, maturity of state-of-research, in-depth characteristics, success and benefits of ESDP models. Results: We found that categorical models that rely on requirement and design phase metrics, and few continuous models including metrics from requirements phase are very successful. We also found that most studies reported qualitative benefits of using ESDP models. Conclusion: We have highlighted the most preferred prediction methods, metrics, datasets and performance evaluation methods, as well as the addressed SDLC phases. We expect the results will be useful for software teams by guiding them to use early predictors effectively in practice, and for researchers in directing their future efforts.

Online Reputation Management Software Market size was valued at USD 5.2 Billion in 2024 and is projected to reach USD 14.02 Billion by 2031, growing at a CAGR of 13.2% from 2024 to 2031.

The market for online reputation management software is propelled by the growing importance of customer trust and brand reputation in the digital age, as well as the growth of social media and online review sites. The demand for software solutions that can efficiently monitor, analyse, and manage online reputation is rising as companies become more aware of the effects that online reviews, comments, and mentions have on their reputation and financial performance. Businesses must actively manage their online presence as the democratisation of content creation and the expansion of social media platforms enable customers to freely express their thoughts and experiences. Furthermore, the growth of digital marketing and e-commerce has increased demand for reputation management solutions that can resolve unfavourable reviews, avert brand crises, and foster a pleasant online atmosphere. Furthermore, reputation management software with strong data protection capabilities is becoming more and more popular as a result of the growing emphasis on data privacy and compliance with laws like the GDPR.

description: Zoning district boundaries by type and classification. Chicago is divided into zoning districts that regulate land use activities across the city. Data is based on the Chicago Zoning Ordinance and Land Use Ordinance http://bit.ly/9eqawi. Zoning Types are defined in this ordinance. To view or use these files, compression software and special GIS software, such as ESRI ArcGIS, is required. For additional information about business uses, review the License/Zoning Reference (LZR) Guide http://bit.ly/vvGzne, which is based on the Municipal Code and is intended to assist business owners in determining the proper zoning district and primary business license for specific business types. Update Frequency: Data is updated monthly. Related Applications: Zoning Map https://gisapps.cityofchicago.org/zoning/; abstract: Zoning district boundaries by type and classification. Chicago is divided into zoning districts that regulate land use activities across the city. Data is based on the Chicago Zoning Ordinance and Land Use Ordinance http://bit.ly/9eqawi. Zoning Types are defined in this ordinance. To view or use these files, compression software and special GIS software, such as ESRI ArcGIS, is required. For additional information about business uses, review the License/Zoning Reference (LZR) Guide http://bit.ly/vvGzne, which is based on the Municipal Code and is intended to assist business owners in determining the proper zoning district and primary business license for specific business types. Update Frequency: Data is updated monthly. Related Applications: Zoning Map https://gisapps.cityofchicago.org/zoning/

Analysis of ‘Tulare County Land Use Survey 2007’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/24d8af24-fd48-4b6b-bd2a-f9aaed5bd880 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

--- Original source retains full ownership of the source dataset ---

Motivation: I describe the GIS that is based on a database of zooplankton collected by Juday net with 0.1 m^2 opening (0.168 mm mesh) Main types of variable contained The average density (mg/m3) of plankton and their different constituents in one-degree trapeziums

Location: Chukchi, Bering, Okhotsk, Japan/East seas, Pacific Ocean

Time period: 1984-2013

Taxa studied: All mesofauna – more than 214 species of holo- and meroplankton

Methods: GIS creation, data analysis and literature review

Software format: Any that is capable of working with shapefiles

Results: Maps of the spatial-temporal distribution of plankton with various taxonomic groups and dimensions were compiled and analysed. Based on these maps and on the literature, a supposition was made regarding the negative correlation of the zooplankton size with temperature. It was also revealed that some fluctuations in the abundance of plankton in the Bering Sea and the ocean are in phase, while in the Sea of Okhotsk and the Sea of Japan, the fluctuations are fully out of phase. In particular, during the transition from the light to dark time of the day in the Sea of Okhotsk and Sea of Japan, the density of plankton almost everywhere throughout the epipelagic zone increases; however, in the Bering Sea and the ocean, over large parts of the water area, it decreases. This means that the common practice employed by trophologists of attempting to replace the day-time catch in plankton nets with the night-time catches to assess the food reserves for fish will give significantly different results in these waters.

Main conclusion: This unique GIS could be useful for understanding patterns and drivers of plankton biomass variations at large scales. Unfortunately, due to lack of funding, it has not been brought to the levels of species and development stages that could be available in the final release