This dataset documents results of the academic workshop "Data as a Material for Design: Alternative Narratives, Divergent Pathways, and Future Directions" co-located and hosted with the ACM CHI Conference on Human Factors in Computing Systems in Hamburg, Germany from April 23-28, 2023. In the dataset, we have collected the mapping of examples of data in design research and practice in the spectrum of "conventional" and "evocative", which was realized pre-workshop in an asynchronous manner. The second item in the dataset is visual combination of all workshop posters that were created during the workshop on the different tables. Finally, participants in the workshop worked on designing data-inspired artifacts and presented them in the last part of the workshop (recorded in a video). The resulting artifacts are listed in a Word document with each a still image. This dataset does not include the full video to protect individuals who do not want to appear in an archived video.

IntroductionData-enabled design (DED) is a design approach where research data is integrated with design praxis in an iterative and hands-on fashion, and it has been successfully applied to design for people in the healthcare domain. However, how to utilise DED as a more broadly applicable approach that facilitates design for larger populations in semi-public spaces remains an open question. Understanding the advantages and challenges of applying DED in various contexts is crucial to guide design researchers further and prevent methodological mismatch.MethodsIn this article, we report on applying DED in an open, semi-public context with a large population of visitors. Here, DED was applied in projects with student design researchers who had limited control over the data gathered from people in the context.ResultsWe share the results of a two-week design workshop that involved sixteen student design researchers and was organised in collaboration with Särkänniemi, one of Finland’s largest theme parks. Using design proposals and reflections from five teams, we investigate the use of DED in this context, reporting on perceived challenges, barriers, successes and future directions for taking the DED approach into similar (semi-)public contexts.DiscussionsWe conclude with reflections from the workshop organisers’ point of view and share the feedback from our industry collaborator, highlighting challenges and opportunities in translating the DED approach to a new domain.

We present an experimental approach to design an over-the-air (OTA) millimeter-wave system for measuring error vector magnitude (EVM) with associated uncertainties that include correlations and nonlinearities. Our approach uses a variable waveguide attenuator at the output of a modulated-signal source at 44 GHz and provides traceable measurements on a calibrated equivalent-time sampling oscilloscope. The conductor-based EVM measurements and associated uncertainties presented here serve as a baseline for the eventual OTA-based EVM. We also discuss a noise based EVM estimation technique as a simple tool for planning OTA EVM measurements, but without a complete knowledge of measurement uncertainties.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Even in the best-designed experiment, noncompliance can complicate analysis. While the intent-to-treat effect remains identified, randomization alone no longer identifies the complier average causal effect (CACE). Instrumental variables (IV) approaches, which rely on the exclusion restriction, can suffer from high variance, particularly when the experiment has a low compliance rate. We provide a framework which broadens the set of design and analysis techniques political science researchers can use when addressing noncompliance. Building on the growing literature about the advantages of ex-ante design decisions to improve precision, we show blocking on variables related to both compliance and the outcome can greatly improve all the estimators we propose. Drawing on work in statistics, we introduce the principal ignorability assumption and a class of principal score weighting estimators, which can exhibit large gains in precision in low compliance settings. We then combine principal ignorability and blocking with a simple estimation strategy to derive a more efficient estimation strategy for the CACE. In a re-evaluation of a study on the effect of GOTV on turnout, we find that the principal ignorability approaches result in confidence intervals roughly half the size of traditional instrumental variable approaches.

Semi-structured interviews with Gig Workers in the USA were conducted remotely over a three-year period (2020-2022). Participants were recruited through in-person and online, and worked for a variety of task-based, delivery, and ride-hail companies that organize labor through a digital platform. Interview participants were recruited through a survey posted to Craigslist, Facebook groups, and Reddit forums for gig workers by platform. The research team acquired permission from forum moderators prior to posting. Survey respondents were contacted by email or text message to schedule an interview and were sent an informed consent document. The consent document included contact information for the PI and the University of Washington Institutional Review Board. Consent and permission to record were established verbally at the start of each interview. In the second phase of data collection, participants from the 2020 interviews and participants from focus groups conducted by the research team in 2019 were re-recruited over email for follow-up interviews. Eligible participants had worked on an app or platform within the last year, and were over the age of 18. Anonymized data include transcripts of interviews, data analysis protocols, and the questionnaire used to guide interviews. Complete study data available upon request (this repository only includes a sample of participant interviews). Note that you must be a registered and credentialed user of Dataverse to access this data.

This book has been prepared for the purpose of assisting engineers in the work of bridge design. It contains a collection of notes on various aspects of bridge design, together with necessary tables and diagrams, included also are certain standard forms relating to design and relevant specifications which the designer finds it necessary to conssult from time to time in preparing bridge designs, caluclating quantities and compling estimates of cost. The data book is not intended as a complete treatise on bridge design nor is it intended to replace “Technical instructions” but rather to supplement these instructions and to assist in the everyday application of the standards.

This repository contains code and data related to the underlying PhD thesis: Data-driven methods to design, learn, and interpret complex materials across scales. The repository is divided into the individual codes and datasets of each chapter. Chapter 2 explores the inverse design of 2D metamaterials for elastic properties, utilizing machine learning techniques to optimize material structure and performance. Chapter 3 focuses on learning hyperelastic material models without relying on stress data, employing data-driven approaches to predict material behavior under large strains. Chapter 4 extends this by developing interpretable hyperelastic material models, ensuring both accuracy and physical consistency without stress data. Chapter 5 explores the inverse design of 3D metamaterials under finite strains and applies novel ML frameworks to design these complex material structures. Chapter 6 investigates the use of deep learning to uncover key predictors of thermal conductivity in covalent organic frameworks (COFs) and reveals new insights into the relationship between molecular structure and thermal transport. Chapter 7 introduces a graph grammar-based approach for generating novel polymers in data-scarce settings, thus combines computational design with minimal data.

Study information Design ideation study (N = 24) using eye tracking technology. Participants solved a total of twelve design problems while receiving inspirational stimuli on a monitor. Their task was to generate as many solutions to each problem and explain their solution briefly by thinking aloud. The study allows for getting further insight into how inspirational stimuli improve idea fluency during design ideation. This dataset features processed data from the experiment. Eye tracking data includes gaze data, fixation data, blink data, and pupillometry data for all participants. The study is based on the following research paper and follows the same experimental setup: Goucher-Lambert, K., Moss, J., & Cagan, J. (2019). A neuroimaging investigation of design ideation with and without inspirational stimuli—understanding the meaning of near and far stimuli. Design Studies, 60, 1-38. DOI Dataset Most files in the dataset are saved as CSV files or other human readable file formats. Large files are saved in Hierarchical Data Format (HDF5/H5) to allow for smaller file sizes and higher compression. All data is described thoroughly in 00_ReadMe.txt. The following processed data is included in the dataset: Concatenated annotations file of experimental flow for all participants (CSV). All eye tracking raw data in concatenated files. Annotated with only participant ID. (CSV/HDF5) Annotated eye tracking data for ideation routines only. A subset of the files above. (CSV/HDF5) Audio transcriptions from Google Cloud Speech-to-Text API of each recording with annotations. (CSV) Raw API response for each transcription. These files include time offset for each word in a recording. (JSON) Data for questionnaire feedback and ideas generated during the experiment. (CSV) Data for the post-experiment survey, including demographic information (TSV). Python code used for the open-source experimental setup and dataset construction is hosted at GitHub. Repository also includes code of how the dataset has been further processed.

This dataset captures the results from the Jump-start Questionnaire collected by the Futures by Design Project. This refers to SMEs digital capabilities across six counties in the North Sea basin.Please contact the authors for access to the dataset.

These data are in support of report DS 456 (Arnold and others, 2009). 30 equal-area polygons generated using techniques described in Scott (1990). Polygons include areas overlying the High Plains Aquifer in Colorado having a depth to water less than 180 feet, a saturated thickness greater than 50 feet, and underlying irrigated agricultural lands. Described in Arnold and others (2009). Input saturated thickness and depth to water data from V.L. McGuire, written communication, 2008. Irrigated agricultural lands from Bauder and others (2004).

The selection of a food packaging requires taking multiple criteria into account . Decision Support Systems (DSS) are elaborated numerical tools designed to help users in such decision-making processes that help users in such decision processes. The main role of packaging is to protect food, so food needs must guide the decision process. However, this knowledge is not always available, or is scattered across the scientific literature and industry. The aim of this study was to provide an innovative new DSS relying on a structured database that allows the collection and compilation of food and packaging material data for an easier, simpler and more comprehensive food requirement driven approach. It also relies on queries that allow this data to be combined to suggest optimal packaging materials for a food product. The novelty of this DSS relies also on the possibility to be used in a reverse mode, to provide food packaging applications for a material with given properties. The DSS was validated on three case studies: strawberries and processed spreadable cheese, as food case studies for which optimal packaging materials were provided, and a polymer-coated cardboard, as packaging material, for which food applications were found. This dataset comprises: - the Microsoft Access prototype - a demonstration video - excel files showing the calculations for the study cases: - strawberry, - processed fresh cheese

Data is designed to be used in Solid works or other common digital human modeling software systems. Data is used to model spatial consumption in determination of accessible seating area designs for passenger rail cars

This exploratory study explores the potential contexts and opportunities for emerging visual data in urban forest design. Forestry experts deploy drone-mounted digital sensors to capture detailed visual and spatial data urban vegetation. These sensors generate point clouds that not only inform ecological analysis but also visually construct urban environments from a pedestrian perspective. Even though many data sources and visualisation tools such as GIS are available, how visualised data should be integrated into design practice is still unclear. Using a prototype multi-sourced data visualisation, we conducted eight semi-structured interviews with urban forestry experts to elicit reflections of the analytical and cultural roles of data visualisations in the domain. Thematic analysis of the interview transcripts revealed three design-oriented themes: (1) design analysis, (2) public engagement, and (3) sustainability. By analysing expert reflections, this paper considers potential research directions for visualising social and ecological data as a design material in the built environment. We discuss the implications of such visualisations for the broader community of spatial planning research including urban designers and communication scholars, proposing future research directions that leverage visual data to better design evolving urban landscapes.

This dataset contains data collected during a study "Transparency of open data ecosystems in smart cities: Definition and assessment of the maturity of transparency in 22 smart cities" (Sustainable Cities and Society (SCS), vol.82, 103906) conducted by Martin Lnenicka (University of Pardubice), Anastasija Nikiforova (University of Tartu), Mariusz Luterek (University of Warsaw), Otmane Azeroual (German Centre for Higher Education Research and Science Studies), Dandison Ukpabi (University of Jyväskylä), Visvaldis Valtenbergs (University of Latvia), Renata Machova (University of Pardubice).

This study inspects smart cities’ data portals and assesses their compliance with transparency requirements for open (government) data by means of the expert assessment of 34 portals representing 22 smart cities, with 36 features.

It being made public both to act as supplementary data for the paper and in order for other researchers to use these data in their own work potentially contributing to the improvement of current data ecosystems and build sustainable, transparent, citizen-centered, and socially resilient open data-driven smart cities.

Purpose of the expert assessment The data in this dataset were collected in the result of the applying the developed benchmarking framework for assessing the compliance of open (government) data portals with the principles of transparency-by-design proposed by Lněnička and Nikiforova (2021)* to 34 portals that can be considered to be part of open data ecosystems in smart cities, thereby carrying out their assessment by experts in 36 features context, which allows to rank them and discuss their maturity levels and (4) based on the results of the assessment, defining the components and unique models that form the open data ecosystem in the smart city context.

Methodology Sample selection: the capitals of the Member States of the European Union and countries of the European Economic Area were selected to ensure a more coherent political and legal framework. They were mapped/cross-referenced with their rank in 5 smart city rankings: IESE Cities in Motion Index, Top 50 smart city governments (SCG), IMD smart city index (SCI), global cities index (GCI), and sustainable cities index (SCI). A purposive sampling method and systematic search for portals was then carried out to identify relevant websites for each city using two complementary techniques: browsing and searching. To evaluate the transparency maturity of data ecosystems in smart cities, we have used the transparency-by-design framework (Lněnička & Nikiforova, 2021)*. The benchmarking supposes the collection of quantitative data, which makes this task an acceptability task. A six-point Likert scale was applied for evaluating the portals. Each sub-dimension was supplied with its description to ensure the common understanding, a drop-down list to select the level at which the respondent (dis)agree, and a comment to be provided, which has not been mandatory. This formed a protocol to be fulfilled on every portal. Each sub-dimension/feature was assessed using a six-point Likert scale, where strong agreement is assessed with 6 points, while strong disagreement is represented by 1 point. Each website (portal) was evaluated by experts, where a person is considered to be an expert if a person works with open (government) data and data portals daily, i.e., it is the key part of their job, which can be public officials, researchers, and independent organizations. In other words, compliance with the expert profile according to the International Certification of Digital Literacy (ICDL) and its derivation proposed in Lněnička et al. (2021)* is expected to be met. When all individual protocols were collected, mean values and standard deviations (SD) were calculated, and if statistical contradictions/inconsistencies were found, reassessment took place to ensure individual consistency and interrater reliability among experts’ answers. *Lnenicka, M., & Nikiforova, A. (2021). Transparency-by-design: What is the role of open data portals?. Telematics and Informatics, 61, 101605 *Lněnička, M., Machova, R., Volejníková, J., Linhartová, V., Knezackova, R., & Hub, M. (2021). Enhancing transparency through open government data: the case of data portals and their features and capabilities. Online Information Review.

Test procedure (1) perform an assessment of each dimension using sub-dimensions, mapping out the achievement of each indicator (2) all sub-dimensions in one dimension are aggregated, and then the average value is calculated based on the number of sub-dimensions – the resulting average stands for a dimension value - eight values per portal (3) the average value from all dimensions are calculated and then mapped to the maturity level – this value of each portal is also used to rank the portals.

Description of the data in this data set Sheet#1 "comparison_overall" provides results by portal Sheet#2 "comparison_category" provides results by portal and category Sheet#3 "category_subcategory" provides list of categories and its elements

Format of the file .xls

Licenses or restrictions CC-BY

For more info, see README.txt

New Privately Owned Housing Completions in the United States by Design Type, Attached One-Family Units was 43.00000 Thous. of Units in January of 2025, according to the United States Federal Reserve. Historically, New Privately Owned Housing Completions in the United States by Design Type, Attached One-Family Units reached a record high of 62.00000 in July of 2006 and a record low of 10.00000 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for New Privately Owned Housing Completions in the United States by Design Type, Attached One-Family Units - last updated from the United States Federal Reserve on June of 2025.

Datasets present text data stemming from academic articles (Scopus and WoS) and Policy documents collected from EU institutional repositories (European Commission, European Parliament, Council of the European Union). The data was collected from January to May 2023, as part of the "Digital Sovereignty by Design" research project framework. The primary purpose of this data collection is to conduct topic modelling, namely Latent Dirichlet Allocation (LDA), in order to identify current debates on digital sovereignty through international relations and political science lenses.

We seek to identify and demonstrate the state-of-the-art with revealing trends and insights, mapping complex research and the political landscape of digital sovereignty issues in the EU. The objectives are (1) to identify the role played by the concept of digital sovereignty in different fields of studies; (2) to highlight recent trends in the study of digital sovereignty; (3) to identify, within those trends, the most common topics related to digital sovereignty and to trace their development over time; and (4) to explore how those trends and topics related to political regulation and governance within the digital sovereignty sphere.

We present five datasets. One dataset contained academic articles data on digital sovereignty, and four other datasets collected policy documents from EU institutions. The academic articles' datasets contain complete bibliographic information, abstract and keywords (if available) from 2013 to 2023 with a total N of 156 texts. The datasets for the policy documents include the document's title and its complete text: European Commission from 2009 to 2023 with a total N of 2019 texts (61 from Register; 158 from Commonly used documents); European Parliament from 2011 to 2023 with total N of 368 texts; and Council of the European Union from 2001 to 2023 with total N of 221 texts.

This dataset contains the coding scheme reports in detail, which were used for the thematic analysis of the prototype evaluation.

o Content: 7 files:

For the RESEARCH CLARIFICATION:

a) Coding Scheme factors multidisciplinary design.xlsx --> This shows the list of references used in Chapter 3 for the research clarification phase, as well as example snippets that show how the abstracts were coded to identify measurements of success, influencing factors, and solution strategies.

b) Prisma ScR Checklist --> The filled checklist used for the abstracts review.

FOR THE PROTOTYPE EVALUATION:

a) Coding Report - Thematic Analysis.xlsx --> Quotation reports for each of the seven themes identified for the evaluation of the prototype. The info tab contains the description of the coded themes.

b) Preliminary Thematic Map.pdf --> Shows the relationships between the lower level/sub-themes that conform that evolved into the final seven themes.

c) INFORMED CONSENT FORM _ EPLM 3-5_revised.docx --> Form that participants were given to sign in order to join our study.

d) psdm-api-main(1).zip --> Server Configuration Apache for the prototype

e) psdm-spa-main(1).zip --> Project setup for the front end developed in Vue

New Privately Owned Housing Completions by Design Type, Attached One-Family Units in the Midwest Census Region was 4.00000 Thous. of Units in January of 2025, according to the United States Federal Reserve. Historically, New Privately Owned Housing Completions by Design Type, Attached One-Family Units in the Midwest Census Region reached a record high of 18.00000 in July of 2004 and a record low of 2.00000 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for New Privately Owned Housing Completions by Design Type, Attached One-Family Units in the Midwest Census Region - last updated from the United States Federal Reserve on June of 2025.

Neighborhood design guidelines direct designers and project reviewers to look closely at the neighborhood and its character to design new buildings that enhance their surroundings. Each record links to neighborhood specific design guidelines.Published from DPD.DR_Guideline_Areas with a definition query of NSDRGA = 1 to omit incomplete records. Symbolized on the NSDRGA_NAM attribute field.For more information, visit the SDCI Design Review Program webpage.Updated as needed, last updated October 2023.