subject to appropriate attribution.

Public procurement platform declaration for the publication of essential data.

BEA's Public Data Listing

This dataset contains data protocol used in a study "From the evolution of public data ecosystems to the evolving horizons of the forward-looking intelligent public data ecosystem empowered by emerging technologies" conducted by Anastasija Nikiforova, Martin Lnenicka, Petar Milic, Mariusz Luterek, Manuel Pedro Rodríguez Bolívar. It is being made public both to act as supplementary data for "From the evolution of public data ecosystems to the evolving horizons of the forward-looking intelligent public data ecosystem empowered by emerging technologies", IFIP EGOV-CeDEM-ePart2024, and in order for other researchers to use these data in their own work. The protocol is intended to empirically validate the six-generation model proposed in our previous research (Lnenicka et al., 2024)*, an expert assessment questionnaire with European national experts was conducted in sample countries, namely, Latvia, Czech Republic, Poland, Serbia, Spain. To this end, we developed a questionnaire / protocol in which national experts were asked (1) to examine the validity of the identified six generations by determining their existence and relevance of each generation in his/her country, (2) the start and end time of each generation as well as its duration constituting a temporal analysis, (3) their opinion on the potential influence of regional or local-level "generations" and how citizens at different levels interact with these generations of PDEs, (4) the potential additional country-specific generations their country's PDE can be characterized by and, finally (5) the existence and importance assessment of meta-characteristics of these generations in the selected country's PDEs. *Lnenicka, Martin and Nikiforova, Anastasija and Luterek, Mariusz and Milic, Petar and Rudmark, Daniel and Neumaier, Sebastian and Kević, Karlo and Zuiderwijk, Anneke and Rodríguez Bolívar, Manuel Pedro, Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems (November 17, 2023). Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4831881 Format of the file.docx (for the first spreadsheet only) Licenses or restrictionsCC-BY

Provides a list of all data assets maintained by the Social Security Administration. It consist of Public Data Listing in the Enterprise Data Inventory.

Telfair County and Cities Public Data

United States Department of Transportation Public Data Listing. The file is formatted to comply with project open data common core metadata requirements (http://project-open-data.github.io/schema/) and conforms to schema version 1.1

This statistic illustrates the number of public data processing centers in the Italian region of Trentino in 2013, broken down by region. According to data, the number of data processing centers of regional and local municipality was five.

Treutlen County and Cities Public Data

Due to Covid-19. Framework scores are not available for the 2020-2021 school year. Each year, all parents, teachers, and students in grades 6-12 take the NYC School Survey. The survey is aligned to the DOE's Framework for great schools. It is designed to collect important information about each school's ability to support student success. This report is created to understand the perceptions of families, students, and teachers regarding their school. Please note: The larger complete data file is downloadable under the Other Attachments Section

2017 NYC School Survey Student data for all schools; To understand the perceptions of families, students, and teachers regarding their school. School leaders use feedback from the survey to reflect and make improvements to schools and programs. Also, results from the survey used to help measure school quality. Each year, all parents, teachers, and students in grades 6-12 take the NYC School Survey. The survey is aligned to the DOE's Framework for Great Schools. It is designed to collect important information about each school's ability to support student success.

Map of Public datasets from California State Parks. Park Boundaries, Districts, Buildings, Facilities, and Roads & Trails.

Data collected from CSR production system.
Data begins 01/03/2014 and is refreshed daily at 8:00am.

A public dataset from ChEMBL (v25) for MELLODDY TUNER release v3. Data extracted from ChEMBL (LICENSE attached), and processed with https://github.com/melloddy/MELLODDY-TUNER release v3. Data can be used for technical tests, template for your own dataset and machine learning with SparseChem (https://github.com/melloddy/SparseChem).

The PREDICT Consortium strengthened global preparedness for emerging threats, in particular to detect viruses that may have the potential to spillover from animal hosts to people. PREDICT-2, implemented from October 2014 through September 2020 as part of USAID’s Emerging Pandemic Threats program, was led by the UC Davis One Health Institute as a multi-institutional cross-disciplinary consortium with numerous global , implementing and government partners in 30 countries (see https://ohi.vetmed.ucdavis.edu/programs-projects/predict-project/authorship for a list of contributors). This project pioneered a One Health approach to emerging infectious virus surveillance and risk communication at high risk human-wildlife interfaces. This data asset and related datasets contain the data collected for China only.

This dataset contains data collected during a study "Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems" conducted by Martin Lnenicka (University of Hradec Králové, Czech Republic), Anastasija Nikiforova (University of Tartu, Estonia), Mariusz Luterek (University of Warsaw, Warsaw, Poland), Petar Milic (University of Pristina - Kosovska Mitrovica, Serbia), Daniel Rudmark (Swedish National Road and Transport Research Institute, Sweden), Sebastian Neumaier (St. Pölten University of Applied Sciences, Austria), Karlo Kević (University of Zagreb, Croatia), Anneke Zuiderwijk (Delft University of Technology, Delft, the Netherlands), Manuel Pedro Rodríguez Bolívar (University of Granada, Granada, Spain).

As there is a lack of understanding of the elements that constitute different types of value-adding public data ecosystems and how these elements form and shape the development of these ecosystems over time, which can lead to misguided efforts to develop future public data ecosystems, the aim of the study is: (1) to explore how public data ecosystems have developed over time and (2) to identify the value-adding elements and formative characteristics of public data ecosystems. Using an exploratory retrospective analysis and a deductive approach, we systematically review 148 studies published between 1994 and 2023. Based on the results, this study presents a typology of public data ecosystems and develops a conceptual model of elements and formative characteristics that contribute most to value-adding public data ecosystems, and develops a conceptual model of the evolutionary generation of public data ecosystems represented by six generations called Evolutionary Model of Public Data Ecosystems (EMPDE). Finally, three avenues for a future research agenda are proposed.

This dataset is being made public both to act as supplementary data for "Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems ", Telematics and Informatics*, and its Systematic Literature Review component that informs the study.

***Description of the data in this data set***

PublicDataEcosystem_SLR.docx provides the structure of the protocol

PDEtypes.png provides a typology of public data ecosystems

PDE_conceptual_model.png provides a conceptual model of elements and formative characteristics that contribute most to value-adding public data ecosystems

PublicDataEcosystem_SLR.xlsx, Spreadsheet#1 provides the list of results after the search over three indexing databases and filtering out irrelevant studies

Spreadsheets #2 provides the protocol structure.

Spreadsheets #3 provides the filled protocol for relevant studies.

The information on each selected study - presented in PublicDataEcosystem_SLR.xlsx - was collected in four categories:
(1) descriptive information,
(2) approach- and research design- related information,
(3) quality-related information,
(4) HVD determination-related information

Descriptive Information

• Article number
• A study number, corresponding to the study number assigned in an Excel worksheet
• Complete reference
• The complete source information to refer to the study (in APA style), including the author(s) of the study, the year in which it was published, the study's title and other source information.
• Year of publication
• The year in which the study was published.
• Journal article / conference paper / book chapter
• The type of the paper, i.e., journal article, conference paper, or book chapter.
• Journal / conference / book
• Journal article, conference, where the paper is published.
• DOI / Website
• A link to the website where the study can be found.
• Number of words
• A number of words of the study.
• Number of citations in Scopus and WoS
• The number of citations of the paper in Scopus and WoS digital libraries.
• Availability in Open Access
• Availability of a study in the Open Access or Free / Full Access.
• Keywords
• Keywords of the paper as indicated by the authors (in the paper).
• Relevance for our study (high / medium / low)
• What is the relevance level of the paper for our study

Approach- and research design-related information

• Approach- and research design-related information
• Objective / Aim / Goal / Purpose & Research Questions
• The research objective and established RQs.
• Research method (including unit of analysis)
• The methods used to collect data in the study, including the unit of analysis that refers to the country, organisation, or other specific unit that has been analysed such as the number of use-cases or policy documents, number and scope of the SLR etc.
• Study’s contributions
• The study’s contribution as defined by the authors
• Qualitative / quantitative / mixed method
• Whether the study uses a qualitative, quantitative, or mixed methods approach?
• Availability of the underlying research data
• Whether the paper has a reference to the public availability of the underlying research data e.g., transcriptions of interviews, collected data etc., or explains why these data are not openly shared?
• Period under investigation
• Period (or moment) in which the study was conducted (e.g., January 2021-March 2022)
• Use of theory / theoretical concepts / approaches? If yes, specify them
• Does the study mention any theory / theoretical concepts / approaches? If yes, what theory / concepts / approaches? If any theory is mentioned, how is theory used in the study? (e.g., mentioned to explain a certain phenomenon, used as a framework for analysis, tested theory, theory mentioned in the future research section).

Quality-related information

• Quality concerns
• Whether there are any quality concerns (e.g., limited information about the research methods used)?

Public Data Ecosystem-related information

• Public data ecosystem definition
• How is the public data ecosystem defined in the paper and any other equivalent term, mostly infrastructure. If an alternative term is used, how is the public data ecosystem called in the paper?
• Public data ecosystem evolution / development
• Does the paper define the evolution of the public data ecosystem? If yes, how is it defined and what factors affect it?
• What constitutes a public data ecosystem?
• What constitutes a public data ecosystem (components & relationships) - their "FORM / OUTPUT" presented in the paper (general description with more detailed answers to further additional questions).
• Components and relationships
• What components does the public data ecosystem consist of and what are the relationships between these components? Alternative names for components - element, construct, concept, item, helix, dimension etc. (detailed description).
• Stakeholders
• What stakeholders (e.g., governments, citizens, businesses, Non-Governmental Organisations (NGOs) etc.) does the public data ecosystem involve?
• Actors and their roles
• What actors does the public data ecosystem involve? What are their roles?
• Data (data types, data dynamism, data categories etc.)
• What data do the public data ecosystem cover (is intended / designed for)? Refer to all data-related aspects, including but not limited to data types, data dynamism (static data, dynamic, real-time data, stream), prevailing data categories / domains / topics etc.
• Processes / activities / dimensions, data lifecycle phases
• What processes, activities, dimensions and data lifecycle phases (e.g., locate, acquire, download, reuse, transform, etc.) does the public data ecosystem involve or refer to?
• Level (if relevant)
• What is the level of the public data ecosystem covered in the paper? (e.g., city, municipal, regional, national (=country), supranational, international).
• Other elements or relationships (if any)
• What other elements or relationships does the public data ecosystem consist of?
• Additional comments
• Additional comments (e.g., what other topics affected the public data ecosystems and their elements, what is expected to affect the public data ecosystems in the future, what were important topics by which the period was characterised etc.).
• New papers
• Does the study refer to any other potentially relevant papers?
• Additional references to potentially relevant papers that were found in the analysed paper (snowballing).

***Format of the file***
.xls, .csv (for the first spreadsheet only), .docx

***Licenses or restrictions***
CC-BY

For more info, see README.txt

null This dataset was created on Tue, 28 Jun 2022 20:28:44 GMT.

ORCID Public Data File 2024These files contain a snapshot of all public data in the ORCID Registry associated with an ORCID record that was created or claimed by an individual as of September 23, 2024. ORCID publishes this file once per year under a Creative Commons CC0 1.0 Universal public domain dedication. This means that, to the extent possible under law, ORCID has waived all copyright and related or neighbouring rights to the Public Data File. For more information on the file, see https://info.orcid.org/public-data-file-use-policy/The file contains the public information associated with each user's ORCID record. The data is available in XML format and is further divided into separate files for easier management. One file contains the full record summary for each record. The rest of the data is divided into 11 files which contain the activities for each record including full work data.Below is a more complete description of how the data is structured.Summaries file:ORCID_2024_10_summaries.tar.gzUncompressed size: 730,009 MBDescription: Contains all the existing summaries, when extracted, it will generate the following file structure: summaries/[3 digits checksum]/[iD].xmlExample: If you are looking for the summary of iD '0000-0002-7869-831X', decompress the file and you will find the summary under 'summaries/31X/0000-0002-7869-831X.xml'.Activities files:ORCID_2024_10_activities_0.tar.gzORCID_2024_10_activities_1.tar.gzORCID_2024_10_activities_2.tar.gzORCID_2024_10_activities_3.tar.gzORCID_2024_10_activities_4.tar.gzORCID_2024_10_activities_5.tar.gzORCID_2024_10_activities_6.tar.gzORCID_2024_10_activities_7.tar.gzORCID_2024_10_activities_8.tar.gzORCID_2024_10_activities_9.tar.gzORCID_2024_10_activities_X.tar.gzTotal uncompressed size: 3,141,554 MBDescription: Consists of 11 .tar.gz files, each file contains the public activities that belongs to an iD that contains a given checksum. The file hierarchy is as follows:[checksum]/[3 digits checksum]/[iD]/[activity type]/[iD]_[activity_type]_[putcode].xmlExamples:If you are looking for the public activities that belong to `0000-0002-7869-831X:Decompress the file 'ORCID_2024_10_activities_X.tar.gz'.You will find all the public activities under 'X/31X/0000-0002-7869-831X/' which are then sub-divided in folders for each activity type.If you are looking for all the employments that belong to '0000-0002-7869-831X':Decompress the file 'ORCID_2024_10_activities_X.tar.gz'Navigate to 'X/31X/0000-0002-7869-831X/employments'.If you are looking for the employment with put-code '7923980' that belongs to '0000-0002-7869-831X' :Decompress the file 'ORCID_2024_10_activities_X.tar.gz'.You will find that employment under 'X/31X/0000-0002-7869-831X/employments/0000-0002-7869-831X_employments_7923980.xml'.Companion Resources:ORCID Data Model2023 ORCID Public Data File2022 ORCID Public Data File2021 ORCID Public Data File2020 ORCID Public Data File2019 ORCID Public Data File2018 ORCID Public Data File2017 ORCID Public Data File2016 ORCID Public Data File2015 ORCID Public Data File2014 ORCID Public Data File2013 ORCID Public Data File

Data represents feedback on learning environment from families. Aids in facilitating the understanding of families perceptions of students, teachers, environment of their school. The survey is aligned to the DOE's framework for great schools. It is designed to collect important information about each schools ability to support success.