The Open Information and Open Data Policy provides a framework to establish the operational responsibilities, organization, processes, tools and other resources required for a single approach to the open data and open information programs. The policy also provides foundational assurance and guidance to staff from across the Government of Alberta with respect to identifying, preparing, and publishing data and information through the open data and open information portals on a routine basis going forward.

The City's Open Data Policy outlines the purpose, principles, and major mechanics of Rochester, NY's Open Data Program.This policy was created by the City's Data Governance Committee and was formally adopted by the City's Senior Management Team on March 1st, 2020.For more information on the Data Governance Committee, please see its charter document here.

Filtered dataset containing results of a discrete-choice stated-preference survey, conducted amongst academic researchers and PhD-candidates of the faculty of Technology, Policy and Management of the Delft University of Technology.

Choices concern packages of stimuli and support measures to incentivize researchers to publish metadata and research data (where possible) in 'accessible' format, according to the FAIR guidelines for data management.

Data, lately, has received a lot of attention from various circles such as government officials, the community, businesses, law enforcement, and also civil society. The reason is actually very simple, because credible data is the key to the quality of development and good governance. Public policy, public services, law enforcement, government performance monitoring, and business opportunities all require credible data. Unfortunately, in practice, data is still often not managed seriously. There are still many cases where there are data that not only have various versions, but often also contradict each other. The One Data Initiative, or commonly called One Data Indonesia, is one of the Indonesian government's initiatives that tries to fix problems in the implementation and management of government data. The development of this initiative is also overseen by the Open Government Indonesia Action Plan. Along with welcoming International Open Data Day which falls on March 4, 2017, As an initiative that is being promoted by the central government regarding data governance reform within the Indonesian government, One Data Indonesia is an initiative that is expected to help the integration of planning, implementation, monitoring, evaluation, and control of development between the central government and the regions, and at the next level is the disclosure of government data that can be used by the community. In addition, the implementation of One Data is also expected to accelerate the implementation of the Electronic-Based Government System (SPBE/E-government) which is being prepared, both in terms of regulations and operational stages, by a number of related agencies involving the Presidential Staff Office, the Ministry of National Development Planning/Bappenas, the Ministry of PAN & RB, the Ministry of Communication and Informatics, and the State Administration Institution. In principle, Satu Data Indonesia strives to encourage better government data governance. Good data governance is highly dependent on quality and consistency in data management. For this reason, Satu Data Indonesia defines good data governance into three main principles. The three main principles that will be encouraged through the One Data Indonesia policy are: (i) a single standard data standard, (ii) one standard metadata, and (iii) data interoperability. With the application of these principles, it is hoped that the One Data policy will be able to realize an accountable, accurate, integrated, up-to-date, and open data management system. These three principles will be implemented through the Presidential Regulation on One Data that we are currently compiling. Currently, the initiation of One Data has reached the finalization stage of the preparation of the Presidential Regulation on One Data Indonesia. If it has been passed, the Presidential Regulation on One Data Indonesia is expected to stimulate efforts to improve government data governance in Indonesia. This means that the use of data will be more structured and will improve the quality of policies and public services in Indonesia as well. In addition, to ensure the smooth implementation later, pilot activities are also being carried out in seven ministries, institutions and also seven local governments. At the central government level, the One Data Initiative is currently being pilotedn in several Ministries, including the Ministry of National Development Planning/Bappenas and the Ministry of Maritime Affairs and Fisheries. At the local government level, the implementation of One Data Indonesia has been piloted in several pilot areas, including DKI Jakarta Province, Demak Regency, Bojonegoro Regency, Semarang City, Banda Aceh City, Mojokerto City, and Pontianak City. There are actually several priorities that can be resolved in order to facilitate the implementation of One Data Indonesia. First, harmonization between the role of Presidential Regulations (Perpres) and Regional Regulations (Perda). Second, finding a clear business process for the implementation of One Data Indonesia both in the Ministries/Institutions of a region. Third, the integration of other Ministries/Institutions data portals in one portal, to facilitate access and use of data by the public. There are several things that are still challenges for the implementation of One Data in Indonesia. One of them is the process of ratifying the Presidential Regulation on One Data Indonesia which requires coordination with various stakeholders which takes a long time. In addition, there are several policies related to statistics, which need to be adjusted to the context of data governance reform within the current government. One of them is Law No. 16 of 1997 concerning Statistics which still defines data only in the form of numbers, so that other forms of data such as spatial data are not included in it. In addition, the reluctance of many parties to integrate cross-sectoral data management within the government is also an obstacle. Where there are various types of data in each sector, but without any integration with other sectors. Finally, one of the things that hinders the implementation of this initiative according to the One Data Indonesia team is the existence of non-tax state revenue (PNPB) collected from data requests. This severely limits access to open data that should be easily and free of charge accessible to the public.

Principles and rules for purchasing supplies and executing works in the Aqaba Special Economic Zone Authority

As part of the EOSC project family the FAIRsFAIR - Fostering Fair Data Practices in Europe - project aims to supply practical solutions for the use of the FAIR data principles throughout the research data life cycle. The work package "WP2 FAIR Practices: Semantics, Interoperability, and Services" will produce three reports on FAIR requirements for persistence and interoperability to identify domain-specific standards and practices in use. These will review and document commonalities and possible gaps regarding semantic interoperability, and the use of metadata and persistent identifiers across infrastructures. They will also look into differences in terms of standards, vocabularies and ontologies. The collected information will be updated during the course of the project in cooperation with other tasks and EOSC projects.

This survey was done to complement and validate the information from desk research for the first of these reports. It was aimed at data managers and data support experts. We hoped to get information about tools and services we might have missed, but also some reflections on the thinking around identifiers and ontologies and other semantic artefacts. The information was also collected to support preparing workshops on semantics and interoperability that are forthcoming in the project, as well as the work on software and services. The survey covers questions about metadata, use of persistent identifiers, use of semantic artefacts and handling research software.

The survey was conducted as a joint effort with WP3, FAIR Policy and Practice and its open consultation, and was disseminated on the fairsfair.eu web pages, social media channels and via email lists. We received 66 answers during the period the survey was open, that is between 15 July to 2 October 2019.

The CDO annual report documents accomplishments and the Enterprise Dataset Inventory results of the previous calendar year. It assess current progress and shares the District's progress with Open Data and the Data Policy. Mayor Bowser is “making our local government one of the most accessible systems in the country.” To that end, the Mayor issued Executive Order 2017-115, District of Columbia Data Policy, on April 27, 2017, with the stated goal of leading the District of Columbia government toward more open and efficient use and sharing of government data. The policy established these principles acknowledging the value of data to the District and the inherent need to balance openness with other concerns:Data are valuable assets independent of the information systems in which the data reside.The greatest value from those assets is realized when freely shared to the extent consistent with the protection of safety, privacy, and security.

Policies are statements that guide the course of action the County must take to achieve the goals outlined in the three guidance documents, Consensus Planning principles, Vision and General Plan Principles.

This dataset is about books. It has 1 row and is filtered where the book is Business law : principles, cases, and policy. It features 7 columns including author, publication date, language, and book publisher.

Regional data has usefulness and value beyond the business purpose for which it was created.This policy enables value creation, innovation, partnership and engagement through the sharing of Regional data to the public and promotes transparency, accountability and good privacy practices. This policy aligns to the six principles in the International Open Data Charter.

This research employed a mixed methods online survey to investigate research software funders’ perspectives.

All participants gave informed consent at the start of the online survey. The University of Illinois Urbana-Champaign Institutional Review Board (no. 24374) reviewed the study and determined it exempt.

Data collection took place from December 2023 to May 2024. The mean completion time for the detailed survey was 28 minutes and 13 seconds. The data were cleaned and prepared for analysis by removing any identifiable respondent details.

Survey design

The survey began by collecting profile information, including institutional affiliation and job title. The survey primarily gathered detailed information about initiatives, policies, or programs to support research software but also included a much smaller set of questions about additional topics, such as strategic funding priorities and awareness of key concepts. The data generated from this survey are too extensive to report in a single manuscript. Here, we focus on the results generated via the set of questions asking about FAIR and FAIR4RS, specifically, the following survey items:

In addition, an open-ended question asked for further detail about the respondents’ assessments of FAIR4RS’s relevance to their work.

Sampling

The survey targeted international research funders, including governmental and non-governmental (e.g., philanthropic) organizations. An initial contact list was created based on participation in the Research Software Association (ReSA) and known responsibilities for research software funding among the authors' networks. This list was refined by removing individuals who had moved to unrelated professional roles or were unavailable long-term due to personal issues.

The final contact list comprised 71 people at 37 funding organizations. After excluding individuals when a member of their organization had already provided a complete response or when the person was no longer working on a relevant topic or was otherwise unavailable (total of n=30), 41 people remained. Of these, five did not complete the survey, while 36 individuals (representing 30 research funding organizations) did, yielding a response rate of 87.8% (and representing 81% of the original organizations). Fully completed survey responses were not required for inclusion in the sample, resulting in varied sample sizes across different survey questions.

The respondents represented governmental (n=26), philanthropic (n=6), and corporate (n=1) research funders.

Respondents’ job titles spanned the following categories: Senior Leadership and Executive (e.g., Vice President of Strategy); Program and Project Management (e.g., Senior Program Manager); Planning and Business Development; and Scientific, Technical, and IT roles (e.g., Scientific Information Lead).

Most respondents, 72.7% (n=24), answered “Yes” to the question, “Has your organization established any policies, initiatives, or programs aimed at supporting research software?” Meanwhile, 18.2% (n=6) said “No,” and 9.1% (n=3) were “Unsure.”

Regarding geographic distribution in the achieved sample, most survey respondents were from North America and Europe, with 15 and 12 participants, respectively. The sample also comprised 4 participants from South America, 3 from Oceania, and 1 from Asia, reflecting a global but uneven representation across continents. Some participating funders covered a broad spectrum of disciplines, while others focused on specific domains such as social sciences, health, environment, physical sciences, or humanities.

This dataset is about books. It has 1 row and is filtered where the book is The ebbing tide : policy and principles of Catholic education. It features 7 columns including author, publication date, language, and book publisher.

Aggregate exposure and risk assessments involve the analysis of exposure to a single chemical by multiple pathways and routes of exposure. The pathways of exposure considered in this general principles document include the potential for pesticide residues in food and drinking water, as well as residues from pesticide use in residential, non-occupational environments.

The open science movement produces vast quantities of openly published data connected to journal articles, creating an enormous resource for educators to engage students in current topics and analyses. However, educators face challenges using these materials to meet course objectives. I present a case study using open science (published articles and their corresponding datasets) and open educational practices in a capstone course. While engaging in current topics of conservation, students trace connections in the research process, learn statistical analyses, and recreate analyses using the programming language R. I assessed the presence of best practices in open articles and datasets, examined student selection in the open grading policy, surveyed students on their perceived learning gains, and conducted a thematic analysis on student reflections. First, articles and datasets met just over half of the assessed fairness practices, but this increased with the publication date. There was a..., Article and dataset fairness To assess the utility of open articles and their datasets as an educational tool in an undergraduate academic setting, I measured the congruence of each pair to a set of best practices and guiding principles. I assessed ten guiding principles and best practices (Table 1), where each category was scored ‘1’ or ‘0’ based on whether it met that criteria, with a total possible score of ten. Open grading policies Students were allowed to specify the percentage weight for each assessment category in the course, including 1) six coding exercises (Exercises), 2) one lead exercise (Lead Exercise), 3) fourteen annotation assignments of readings (Annotations), 4) one final project (Final Project), 5) five discussion board posts and a statement of learning reflection (Discussion), and 6) attendance and participation (Participation). I examined if assessment categories (independent variable) were weighted (dependent variable) differently by students using an analysis of ..., , # Data for: Integrating open education practices with data analysis of open science in an undergraduate course

Author: Marja H Bakermans Affiliation: Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA 01609 USA ORCID: https://orcid.org/0000-0002-4879-7771 Institutional IRB approval: IRB-24–0314

Data and file overview

The full dataset file called OEPandOSdata (.xlsx extension) contains 8 files. Below are descriptions of the name and contents of each file. NA = not applicable or no data available

1. BestPracticesData.csv
   • Description: Data to assess the adherence of articles and datasets to open science best practices.
   • Column headers and descriptions:
     • Article: articles used in the study, numbered randomly
     • F1: Findable, Data are assigned a unique and persistent doi
     • F2: Findable, Metadata includes an identifier of data
     • F3: Findable, Data are registered in a searchable database
     • A1: ...

The ���Guidelines for handling research data at the University of Hildesheim Foundation��� were adopted on February 5, 2020 by the extended university management and offer all researchers at the SUH an orientation framework that creates transparency, clarity and support in dealing with research data. In the spirit of Open Science and Open Access, the new guidelines for handling research data promote transparency in science and research. They help to implement the Sorbonne declaration on access to research data, recently signed by 160 international universities, based on the FAIR principle (findable, accessible, interoperable, reusable) at the SUH.

The dataset was made in an attempt to investigate the state of information policy - the sum of principles guiding decisions about information - in archaeology and related areas. The aim of the study was to shed light on how information policy directs practice in archaeology, and to show that analysis of such policies is therefore vital.

Information policy in legislation and guidelines in Swedish archaeology serves as a case study, and examples from development-led archaeology and the museum sector illustrate how information policies have varied roles across different heritage sectors. There are historical and local trajectories in the policy documents specific to Sweden, but the discussion shows that the emergence of Swedish policies have many parallels with processes in other countries. The article provides recommendations for information policy development for archaeology and related areas.

See article "Information Policy for (Digital) Information in Archaeology: current state and suggestions for development" by Börjesson et al (2015) for further information.

The dataset was originally published in DiVA and moved to SND in 2024.

Data prepared for the publication "Evaluating Institutional Commitments to Open Scholarly Infrastructure: A Review of Open Access Collection Development Policies."

oa-cd-policies.csv

Scope: This data represents collection development policies that contain substantial mention of open access.

Data collection: The policies were sourced using an Advanced Google Search for "open access" AND "collection development policy" at ".edu" domains.

Variables:

institution: Free text, name of the institution.

carnegie_class: One of these options; the Carnegie classification of the institution.

institution_type: One of public or private; the funding source of the institution.

policy_name: Free text; the title of the policy.

supplemental_policy: Link to a supplemental open access policy if linked in the collection development policy.

cd_policy_link: Link to the policy.

infrastructure: TRUE or FALSE; whether the policy includes a commitment to open access scholarly infrastructure development, including open source platforms, locally hosted platforms, consortia, or an institutional repository.

excerpt: Free text; text from the policy that mentions infrastructure.

principles-policies.csv

Scope: This data represents those collection development policies from oa-cd-policies.csv that contain commitments in line with the Principles for Open Scholarly Infrastructure.

Variables:

institution: Free text, name of the institution.

carnegie_class: One of these options; the Carnegie classification of the institution.

institution_type: One of public or private; the funding source of the institution.

policy_name: Free text; the title of the policy.

supplemental_policy: Link to a supplemental open access policy if linked in the collection development policy.

cd_policy_link: Link to the policy.

principle: One of the three main Principles.

sub_principle: One of the Sub-Principles.

excerpt: Free text; text from the policy that illustrates the sub_principle.

The OAIC commissioned ORIMA Research to conduct a dual survey - the PSI survey, together with a survey of Australian Government agencies on compliance with their obligations under the Information Publication Scheme. The PSI survey was structured around the eight "http://www.oaic.gov.au/publications/agency_resources/principles_on_psi%0A_short.html">Principles on open public sector infor mation (Open PSI principles) that were published by the OAIC in 2011.

The IPS/PSI survey was carried out by ORIMA Research in April and May 2012. It was completed by 191 agencies (78%) of the 245 that were approached. The OAIC complemented the PSI survey by conducting focus group discussions with a variety of Australian Government agencies.

The data has been compiled by ORIMA Research from their Data Pack Report for the PSI Survey.

Please refer to the PSI survey (PDF, 1.09MB) on the OAIC website.

Please refer to the Data Pack Report for the PSI survey (PDF, 1.72MB) on the OAIC website.

The OAIC has released two reports examining the issues encountered by agencies in implementing the Open PSI principles, drawn from the survey results and focus group discussions.

The interim report of the PSI survey and focus group discussions, "http://www.oaic.gov.au/information-policy/information-policy-resources/information-policy-reports/open-public-sector-information-government-in-transition">Open public sector information: government in transition, is available on the OAIC website.

The full report of the PSI survey and focus group discussions, "http://www.oaic.gov.au/public%0Aations/reports/open_psi_principle_to_practice_february2013.html">Open Public Sector Information: from principles to practice, is available on the OAIC website.

The ExPaNDS project is the European Open Science Cloud (EOSC) Photon and Neutron Data Service: a collaboration, funded by the Horizon 2020 programme, between ten national Photon and Neutron Research Infrastructures as well as EGI, an e-infrastructure that provides advanced computing services for research. These research infrastructures are exemplars of “facilities science”, providing specialised instruments and techniques for use by researchers from a wide range of fields. One strand of work in the project is on “Enabling FAIR data for photon and neutron national research infrastructures”, and includes development of a data policy framework to allow the facilities to adopt a coherent approach to FAIRness of the data that they generate. The activity examined here concerns revisions to the ExPaNDS data policy framework presented in the project’s Final data policy framework for Photon and Neutron RIs. The earlier draft policy framework (ExPaNDS deliverable D2.1: Draft extended data policy framework for photon and neutron RIs) had been published in September 2020, and drew on the FAIRsFAIR Policy enhancement recommendations. Before that, there had been joint work with the PaNOSC project, which had produced its own data policy deliverable in May 2020. However it became apparent that ExPaNDS partners were keen to explore the various themes of the data policy framework in more depth, especially with a view to providing greater flexibility in approach, so a programme of consultations with each of the ten ExPaNDS partner facilities was undertaken.

In 2019, the Global Indigenous Data Alliance (GIDA) developed and published the CARE Principles for Indigenous Data Governance (Collective Benefit, Authority to Control, Responsibility, Ethics) to complement the FAIR principles for open scientific data management (Findable, Accessible, Interoperable, Reusable) (Wilkinson et al., 2016; Carroll et al., 2020, Carroll S. R. et al., 2021). FAIR are data-centric, focusing on the attributes of data objects themselves. The CARE Principles serve as high-level guidance toward more equitable creation, collection, use, and storage of Indigenous data that focuses on the people to whom data relate, and the purpose for which those data are collected, analyzed, and used. In the six years since their original publication, the CARE Principles have garnered significant interest and induced uptake, informing policy and processes across many institutions, governments, organizations, communities, Tribal Nations, and other data-related entities. There has also been interest in applying the principles and framework beyond Indigenous contexts (Lipphardt et al 2021; Suchikova and Nazarovets 2025).