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This paper presents the history, internal processes, and finalized report of the Trans Metadata Collective (TMDC), founded to address the lack of attention paid to trans and gender diverse issues in galleries, archives, libraries, museums, and special collections (GLAMS). The TMDC, an ad‐hoc group of nearly a hundred information professionals, developed best practices for the description and classification of trans and gender diverse information resources. These guidelines prioritize transparency, cultural sensitivity, correct identification, explicit descriptions of transphobia, and regular assessment of trans‐related content. It examines the effects of commonly used standards and controlled vocabularies such as Resource Description and Access (RDA) and Library of Congress Subject Headings (LCSH) on trans and gender diverse people and critiques the inadequacy of these standards' representation of those communities. The TMDC provides guidance for using existing LCSHs, recommends alternative subject vocabularies, and proposes revisions to improve representation. The paper advocates individual agency in naming and gender identification, with recommendations on contacting creators and documenting their preferences. The TMDC emphasizes the importance of minimizing potential harm and protecting privacy in metadata creation. Overall, the report aims to enhance the representation and inclusion of trans and gender diverse communities in GLAMS institutions. [ABSTRACT FROM AUTHOR]

Large amounts of samples have been collected and stored by different institutions and collections across the world. However, even the most carefully curated collections can appear incomplete when aggregated. To solve this problem and support the increasing multidisciplinary science conducted on these samples, we propose a method to support the FAIRness of the aggregation by augmenting the metadata of source records. Using a pipeline that is a combination of rule‐based and machine learning‐based procedures, we predict the missing values of the metadata fields of 4,388,514 samples. We use these inferred fields in our user interface to improve the reusability. [ABSTRACT FROM AUTHOR]

Given the size of digital library collections and the inconsistencies in their genre‐related bibliographic metadata, as digital libraries grow and their contents are opened for computational analysis, finding materials of interest becomes a major challenge. This challenge increases for sub‐genres and other categories of text data that are less distinct from the whole. This project pilots machine learning methods and word feature analysis for identifying Black Fantastic genre texts within the HathiTrust Digital Library. These texts are sometimes referred to as "Afrofuturism" but more commonly today described as "Black Fantastic," in which African Diaspora artists and creators engage with the intersections of race and technology in their works with a primary focus on world‐building. Black Fantastic texts pose a challenge to genre classification, as they incorporate aspects of science fiction and fantasy with typical characteristics of African Diaspora‐produced literature. This paper presents and reports on results from a pilot predictive modeling process to computationally identify Black Fantastic texts using curated word feature sets for each class of data: general English‐language fiction, Black‐authored fiction, and Black Fantastic fiction. [ABSTRACT FROM AUTHOR]

Along with the development of the data‐driven research paradigm, there are exponentially increasing datasets, which bring challenges to researchers in the efficient retrieval of relevant datasets. Previous studies mainly focused on query expansion methods based on sparse retrieval models to improve the accuracy and recall in retrieval. We investigated the use of semantically rich information to retrieve relevant datasets and the benefits of using domain‐specific dense vector representation as opposed to general representation. First, we used pairs of metadata fields that have semantic relevance to construct the domain‐specific weakly supervised training data. Then, a pre‐trained transformer‐based deep learning model is fine‐tuned on the training data using the contrastive learning method. Finally, dense vector representations of the queries and datasets are obtained based on the fine‐tuned model. The relevance of a dataset to a query is measured by the similarity between the vectors. To evaluate the performance of the proposed model, we collected 104,683 datasets from 13 research data repositories, recruited volunteers to design research‐oriented queries, and annotated the retrieval results. The experimental results show that compared with the domain‐independent fine‐tuned model, our proposed method can improve the NDCG@10 score by about 5%. [ABSTRACT FROM AUTHOR]

This paper reports on the application of entification to collections of archival metadata. Entification refers to the identification of the entities described in information objects and associated metadata records. The process presents issues about whether existing records‐style metadata records are suitable and how entification will affect user access and interaction with metadata and information objects. In this study, we developed an entification workflow that includes the following steps: data cleaning, entity reconciliation to create linked data through metadata enrichment, accuracy selection, and developing knowledge graphs to communicate the semantic relationships among entities. Additionally, we discuss the implications of entification for practitioners in the field of information science, especially current limitations in the process. [ABSTRACT FROM AUTHOR]

Science is increasingly carried out through scientific collaborations, allowing researchers pool their experience, knowledge, and skills. In this work we identify factors related to a scientist's collaboration capacity, their ability accumulate new collaborations over their career. To do this offer a new collaboration capacity framework and begin the work of validating it empirically by testing a number of hypotheses. We use data from GenBank, a cyberinfrastructure (CI)‐enabled data repository that stores and manages scientific data. The data allow us to construct longitudinal networks, thereby giving us yearly scientific collaboration maps. We find that a scientist's network position at an early stage is related to their capacity to build new collaborations and that researchers who manage an upward trend in productivity tend to have higher collaboration capacity. Our work makes a contribution to science of science studies by offering a collaboration capacity framework and providing partial empirical support for it. [ABSTRACT FROM AUTHOR]

A proper news tagging is essential for a suitable search and retrieval of information by news libraries users, as well as for a suitable web SEO positioning of these media outlets, what is an aspect to take increasingly into account in digital journalism. Through a case study, we carried out a comparative exploratory analysis on how the most read Spanish online newspapers assign the tags which identify the informational content of their news, given the scarcity of this kind of empirical studies and the enormous importance of this task in the field of news librarianship. The resulting data demonstrate the need for specific training in news librarianship for journalists and the importance of educating media outlets in using controlled vocabularies to ensure an efficient retrieval of news in databases a posteriori. [ABSTRACT FROM AUTHOR]

In response to the rising calls for transparency in displaying collections information, an ongoing research project is developing and studying provenance research methods in four domains, which cross museum and archive settings and their legal oversight in the United States: art collections (furthermore colonial era and Nazi‐looted era), special collections and manuscripts, Native and Indigenous research, and local or rural history collections. We illustrate three resilient values underpinning successful or at least informative provenance research: transparency, due diligence, and digital inclusion. Together the values, when practiced further, will guide information professionals towards researching collections provenance more effectively according to internal and public‐facing goals. [ABSTRACT FROM AUTHOR]

Processes and practices—and in general, informational doings and their diverse constellations—are pertinent elements of the information landscape. This panel presents research on documentation and description of processes and practices in the information field addressing: 1) how different conceptualisations of processes and practices influence how they emerge as describable entities; 2) what different approaches to document and describe processes and practices exist and have been proposed in information science and technology research; 3) what aspects of processes and practices different documentation approaches capture, make visible and invisible; and 4) what novel insights from the current state‐of‐the‐art research can be drawn to support practitioners in different areas of the information field, including knowledge organisation, information management, information literacy instruction, and development of information systems and services. [ABSTRACT FROM AUTHOR]

Study reported in this paper analyzed over twenty thousand machine‐readable library metadata records in MARC 21 bibliographic format that are based on Resource Description and Access (RDA) standard. The focus of this analysis is on change in subject metadata—data elements designed for representing the aboutness of information objects—over a 6‐year period between 2014 and 2020. The analyzed dataset is the entire population of the records representing English‐language video recordings in DVD format in WorldCat database as of one year after official transition to RDA data content standard in library metadata creation. Analysis of metadata representing audiovisual materials is needed as audiovisual metadata practices tend to differ from those for other materials due to high occurrence of unique resources. The study includes quantitative and qualitative analyses into the change in the application of data elements (fields and subfields) over time and categorizes the observed change. [ABSTRACT FROM AUTHOR]

Representing archival metadata as linked data can increase the findability and usability of items, and linked data sources such as Wikidata can be used to further enrich existing collection metadata. However, a central challenge to this process is the named entity disambiguation or entity linking that is required to ensure that the named entities in a collection are being properly matched to Wikidata entities so that any additional metadata is applied correctly. This paper details our experimentation with one entity linking system called OpenTapioca, which was chosen for its use of Wikidata and its accessibility to librarians and archivists with minimal technical intervention. We discuss the results of using OpenTapioca for named entity disambiguation on the Belfer Cylinders Collection from the Special Collections Research Center at Syracuse University, highlighting the successes and limitations of the system and of using Wikidata as a knowledge base. [ABSTRACT FROM AUTHOR]

This paper describes a method for improved access to publisher references in linked data RDF editors using data mining techniques and a large corpus of library metadata encoded in the MARC21 standard. The corpus is comprised of clustered sets of publishers and publisher locations from the library MARC21 records found in the Platform for Open Data (POD). POD is a data aggregation project involving member institutions of the IvyPlus Library Confederation and contains seventy million MARC21 records, forty million of which are unique. The discovery of publisher entity sets described forms the basis for the streamlined description of BIBFRAME Instance entities. The result of this work includes a database of association rules and RDF editor improvements. The association rules are the basis of a prototype autosuggestion feature of BIBFRAME Instance entity description properties designed specifically to support the auto‐population of publisher entities in linked data RDF editors. [ABSTRACT FROM AUTHOR]

On March 16, 2021, six Asian women were killed in Atlanta, US, possibly out of racist motivations. This tragic event, now known as the 2021 Atlanta Spa Shootings, precipitated a massive increase in the volume of counter‐anti‐Asian declarations and discussion on social media platforms such as Twitter. In a pilot study to chronicle and profile public opinions, social movements and patterns in the global Twitter discourse we scraped the Twitter API using the query term "StopAsianHate", obtaining more than 5.5 million tweets and their metadata. By using social movement analytical frameworks to analyze traffic peaks and the use of hashtags, we identified a set of more than 300 frequently used hashtags that can serve as specific query words in future archival ingest activities, as well as the dimensions of and current problems with this social movement. This suggests the utility of this approach for both archiving applications and social‐political analyses of emerging topics and concerns. [ABSTRACT FROM AUTHOR]

This paper reports on the development of a metadata application profile (AP), MetaFAIR, designed to support research data management (RDM) to make research data findable, accessible, interoperable, and reusable. The development of MetaFAIR followed a three‐step process that included learning about the characteristics of datasets from researchers to establish their context and requirements, as well as iterative design and testing with researchers' feedback. Guided by the FAIR principles (Findability, Accessibility, Interoperability, and Reusability), MetaFAIR focuses on accommodating description needs particular to computational social science datasets while seeking to provide general enough elements to describe data collections across many different domains. In this paper, MetaFAIR is placed in the context of historical and recent developments in the areas of RDM and application profile creation; following this contextualization, the paper describes the central considerations and challenges of the MetaFAIR development process and discusses its significance for future work in RDM. [ABSTRACT FROM AUTHOR]

Achieving the potential of widespread sharing of open research data requires that sharing data is straightforward, supported, and well‐understood; and that data is discoverable by researchers. Our literature review and environment scan suggest that while substantial effort is dedicated to structured descriptions of research data, unstructured fields are commonly available (title, description) yet poorly understood. There is no clear description of what information should be included, in what level of detail, and in what order. These human‐readable fields, routinely used in indexing and search features and reliably federated, are essential to the research data user experience. We propose a set of high‐level best practices for unstructured description of datasets, to serve as the essential starting point for more granular, discipline‐specific guidance. We based these practices on extensive review of literature on research article abstracts; archival practice; experience in supporting research data management; and grey literature on data documentation. They were iteratively refined based on comments received in a webinar series with researchers, data curators, data repository managers, and librarians in Canada. We demonstrate the need for information research to more closely examine these unstructured fields and provide a foundation for a more detailed conversation. [ABSTRACT FROM AUTHOR]

Publishing research data is widely expected to increase its reuse and to inspire new research. In the social sciences, data from surveys, interviews, polls, and statistics are primary resources for research. There is a long tradition to collect and offer research data in data archives and online repositories. Researchers use these systems to identify data relevant to their research. However, especially in data search, users' complex information needs seem to collide with the capabilities of data search systems. The search capabilities, in turn, depend to a high degree upon the metadata schemes used to describe the data. In this research, we conducted an online survey with 72 social science researchers who expressed their individual information needs for research data like they would do when asking a colleague for help. We analyzed these information needs and attributed their different components to the categories: topic, metadata, and intention. We compared these categories and their content to existing metadata models of research data and the search and filter opportunities offered in existing data search systems. We found a mismatch between what users have as a requirement for their data and what is offered on metadata level and search system possibilities. [ABSTRACT FROM AUTHOR]

This study discusses the properties of research data repositories and explores metadata about 2,646 entries in the Registry of Research Data Repositories (re3data.org) to identify the characteristics attributed to infrastructures they exhibit. The results reveal how research data repositories function as information infrastructure for scientific community members and contribute to the small body of literature that examines data repositories through a socio‐technical lens. [ABSTRACT FROM AUTHOR]

As archiving became a priority in documentary linguistics only in the 1990's, existing research indicates that language archives are not yet up to date on best practices in information organization. As a result, metadata in language archives varies substantially, depending on the depositor, self‐upload procedures, and metadata creation guidelines. Focusing on free‐text metadata, known to provide rich information, this study analyzes item‐level metadata in three language archives: the Endangered Language Archive, Pacific Regional Archive for Digital Sources in Endangered Cultures, and the Archive of the Indigenous Languages of Latin America. The study identified categories of information included in Description metadata fields and the relative distribution of these categories. The most commonly occurring categories of information observed in this study can serve as a basis for the development of best practice guidelines for item‐level metadata in language archives. [ABSTRACT FROM AUTHOR]

In 2018 the HathiTrust Research Center built an experimental triplestore of BIBFRAME RDF from the HathiTrust Digital Library's MARC metadata catalog. This poster describes processes used to convert from MARC to BIBFRAME, to enrich descriptions with links, and to visualize worksets using RDF created. [ABSTRACT FROM AUTHOR]

This research explores visualisation of data for working with personal digital archives (PDA). Large scale PDAs, comprising content from several personal hard disk drive images, are not receptive to "open the box and take a look" approaches to appraisal traditionally adopted by analogue archives. By employing a Sunburst visualisation to represent file directory structures, this paper demonstrates that it is possible to gain an "at a glance" comprehension of content organisation and date distribution, whilst concurrently allowing for the dynamic and interactive exploration of information such as usage patterns, content metadata and original order relevant to archival appraisal processes. [ABSTRACT FROM AUTHOR]

Data and how that data are organized, accessed, and used, remain central to the advancement of science, as evidenced through calls for reproducibility and demands to enable re‐use. Data management plans describe the roles, responsibilities, and activities for managing data during and after research. This paper presents the development of a data management plan scorecard. The assessment of data management plans provides one measure to evaluate how data are planned to be shared and a first step down the road towards shareable data. The scorecard provides a widely‐applicable, scalable, and simple tool to assess completeness and quality of 15 data elements commonly required in all data management plans. [ABSTRACT FROM AUTHOR]

Context—"the complex web of social relations which [the individual] inhabits" (Spratt & Florian, Teaching and Teacher Education, 2015, 49, 89–96, p. 90) touches everything, including individual and group circumstances, positionalities, feelings, experiences, and environments. Context shapes not only how we communicate information in the field and in the classroom, but also several significant processes: searching for information, accessing information, and the interpretation and use of information (Encheva, Journal of Library Administration, 2016, 56, 595–602; Mitchell, Technical Services Quarterly, 2017, 34, 283–296; Yeo et al., The Annals of the American Academy of Political and Social Science, 2015, 658, 172–191). Furthermore, such contexts affect how information scientists teach and conduct their research and how information (in a classroom setting or otherwise) can be delivered to individuals and communities for action. How we, as information scholars and professionals, take individual and community contexts into account will affect our work. Issues of context will be thoroughly interrogated from a number of different perspectives by both the panelists and audience members in this interactive and participation‐based session. [ABSTRACT FROM AUTHOR]

Studies typically use publication‐based authorship data to study the relationships between collaboration networks and knowledge diffusion. However, collaboration in research often starts long before publication with data production efforts. In this project we ask how collaboration in data production networks affects and contributes to knowledge diffusion, as represented by patents, another form of knowledge diffusion. We drew our data from the metadata associated with genetic sequence records stored in the National Institutes of Health's GenBank database. After constructing networks for each year and aggregating summary statistics, regressions were used to test several hypotheses. Key among our findings is that data production team size is positively related to the number of patents each year. Also, when actors on average have more links, we tend to see more patents. Our study contributes in the area of science of science by highlighting the important role of data production in the diffusion of knowledge as measured by patents. [ABSTRACT FROM AUTHOR]

New technologies are challenging traditional notions and practices of attribution, or how creative responsibility is understood and expressed. A prominent example is the recreation of deceased or unavailable actors in new film performances. Manufactured through the use of doubles, CGI, and reference footage, these performances are the result of complex, shared creative responsibilities. This study looks to the credits for these films as a means of exploring attribution in such cases. Researchers identified 19 feature films utilizing recreated performances and conducted a content analysis of the films' closing credits, focusing on attributive statements associated with recreated actors and their roles. Results show that, even with minimal or no active involvement, deceased actors tend to receive the major acting credit, while doubles receive lesser or no credit at all. As such, film credits do not serve as traditional descriptive metadata per se, but must negotiate a number of functions simultaneously, highlighting their role as paratexts that use attribution to blur the lines between narrative and external realities. Attribution is used to support the authenticity of these performances, downplaying or obscuring complex creative responsibilities in the process. [ABSTRACT FROM AUTHOR]

Video game users have shown strong interests in having subject metadata to find games. However, creating and maintaining subject metadata is costly and difficult. This study explores the utility of an automated approach for generating subject metadata for video games, focusing on plot and narrative. By comparing two methods to analyze the reviews—qualitative analysis conducted by a human researcher vs. automated text analysis using topic modeling—the researchers investigate if an automated method can generate subject terms that are comparable to the ones generated by qualitative analysis. Findings suggest that even with a smaller set of sample dataset, qualitative analysis could create a better set of terms than automated text analysis. However, terms generated from the automated text analysis indicate that its capability to retrieve themes of the video game may be useful in future libraries. [ABSTRACT FROM AUTHOR]

The pursuit of truth in research should be both an ideal in aspiration and also a reality in practice. The PORTAL‐DOORS Project (PDP) strives to promote creative authenticity, fair citation, and adherence to integrity and ethics in scholarly research publishing using the FAIR family of quantitative metrics with acronym FAIR for the phrases Fair Attribution to Indexed Reports and Fair Acknowledgment of Information Records, and the DREAM principles with acronym DREAM for the phrase Discoverable Data with Reproducible Results for Equivalent Entities with Accessible Attributes and Manageable Metadata. This report presents formalized definitions for idea‐laundering plagiarism by authors, idea‐bleaching censorship by editors, and proposed assertion claims for authors, reviewers, editors, and publishers in ethical peer‐reviewed publishing to support integrity in research. All of these principles have been implemented in version 2 of the PDP‐DREAM ontology written in OWL 2. This PDP‐DREAM ontology will serve as the model foundation for development of a software‐guided workflow process intended to manage the ethical peer‐reviewed publishing of web‐enabled open access journals operated online with PDP software. [ABSTRACT FROM AUTHOR]

Studying, designing, and implementing linked data is becoming an increasingly important part of many information settings. Whether taking part in high‐profile grant funded collaborations, local exploratory projects, or adopting a "wait and see" approach, institutions such as libraries, archives, and enterprise organizations will need professionals versed in linked data technologies and practices. In recent years, many advances have been made toward the establishment of an educational foundation for information professionals in this area, through both the incorporation of linked data topics into formal course curricula as well as the establishment of community‐driven, open access learning resources online. However, questions and challenges remain. In this panel, presenters will explore the past, current, and future states of linked data education and training while addressing ongoing challenges and opportunities for preparing metadata professionals in this area. [ABSTRACT FROM AUTHOR]

The growth of text mining and corpus analytic scholarship over large digital libraries brings to light the issues created by text duplication and variation within collections that are not adequately addressed in metadata practices. The SaDDL project was a study examining text duplication and similarity in massive digital library collections. Using the HathiTrust Digital Library, this project aims to reduce the bias that duplication gives rise to. We present the content‐based methods of the project, employing a convolutional neural network classification approach, as well as SaDDL's outcomes. The datasets provided by the project will assist in improving cataloging practice and aid scholars in using large text corpora in research. [ABSTRACT FROM AUTHOR]

While well‐established standards for encoding date metadata exist, Before Common Era (BCE) dates, previously referred to as Before Christ (BC) dates, are a challenge. Libraries, archives, and museums have a rich variety of artifacts from this era. However, the lack of encoding or underuse of available standards hinders the ability to search and browse for this content. While several metadata standards support encoding of BCE dates, the full capability is often not exploited. By analyzing metadata in the Digital Public Library of America (DPLA, https://dp.la/), the authors examine the benefits and limitations of the Extended Date Time Format (EDTF) and related interoperability issues. [ABSTRACT FROM AUTHOR]

Twitter serves as a platform for librarians to connect with each other and discuss, debate, and find consensus around professional issues. Using Social Network Analysis and participant interviews, the Twitter conversations that coalesced around the hashtags #NoHateALA and #IStandWithALA, with particular attention to the role of central actors, are examined. Findings reveal that five Twitter accounts were responsible for 75.5% of all posts under these hashtags out of 1693 posters. In interviews, some of the central actors indicated that their centrality in these networks was deliberate and part of a larger activist agenda. Understanding the depth and breadth of the online network, alongside an understanding of how and why the central actors took on such important roles in the network sheds light on how librarians use online tools to connect and debate professional issues and effect important professional changes. [ABSTRACT FROM AUTHOR]

With the increase in Anti‐Asian hate crimes in the United States in 2020, it is essential for information institutions to reflect on how they are confronting the oppression of Asian communities. Guided by the concept of radical empathy, we conducted an analysis on how historical Chinese students at the University of Illinois were documented and described in the university's archives. Relevant archival materials, descriptive metadata, and additional archives‐generated materials were examined to identify potential representation issues. The preliminary findings include: (1) Chinese students are mostly visible in registers and yearbooks, with some well‐known alumni also appearing in newspapers and correspondence; (2) Some culturally insensitive terms occasionally appeared in historical student newspaper articles; (3) Name variations related to Chinese "courtesy names" and hyphenations can lead to challenges in creating descriptive metadata and affect the discoverability of Chinese students in the archives. [ABSTRACT FROM AUTHOR]

This study investigates whether socially discussed book reviews would help understand the characteristics and features of books in selecting books for children. The study identifies users' interests in discussing books by analyzing the frequency of words used in their book reviews on a social networking site. This study also examines whether the patterns of word frequency would help understand the features of books. The findings of this study identify the aspects of a book that users are concerned about in reviewing the books. The results also reveal that online book reviews help us understand the specific features of books and user behavior in discussing books on a social networking site. This study has implications for providing practical insights into the intrinsic values of users' book reviews in discovering a pattern of social discussion. [ABSTRACT FROM AUTHOR]

This study explores six projects in mapping Knowledge Organization Systems (schemas, taxonomies, ontologies), and examines the data models used in these projects. We discuss (1) the two most common data models presented in these projects, namely tabular model, and tree model; (2) the implicit and explicit information shown in the data models; and (3) the information gains and losses of each model. We found that though the tree model maintains the hierarchical structure of the KOS while a tabular model flattens out the structure, both models can potentially obscure the information of the original KOS. This makes it problematic if we want to reconstruct a mapping project based on the outcomes manifested in either model. Our findings contribute to the Knowledge Organization literature by showing how choices of data models can impact the results in mapping schemas, taxonomies, and ontologies. [ABSTRACT FROM AUTHOR]

Ovarian cancer (OvCa) patients and caregivers have constant and evolving information needs. To meet their needs, they seek information from various resources, including online health information. Although about 60% of cancer patients are now using the Internet to meet their information needs, little is known about online health information seeking (OHIS) among OvCa patients and caregivers. To address this gap, we interviewed 18 OvCa patients and 2 family caregivers of OvCa patients and conducted content analysis on the transcribed data. We identified three challenges of OHIS: (1) lack of OvCa‐related knowledge, (2) poor quality of online information, and (3) inherent characteristics of OvCa, such as the high complexity and aggressive progression of the disease. The findings deepen the understanding of OvCa patients and caregivers and provide insights to better support their OHIS experience. [ABSTRACT FROM AUTHOR]

A national census enables a government to comprehend its population. Questions concerning race and ethnicity are often included in census forms. We examined the racial category options provided in 35 countries' historical census forms over multiple decadal censuses. Analysis of these metadata options can help in understanding the way that official measures of race are socially constructed and reconstructed over place and time according to changing circumstances. [ABSTRACT FROM AUTHOR]

Data sharing and reuse practices in social sciences have changed in the past few decades with the continuing development of cyber‐infrastructures. However, little is known about how such practices chronically change over time. Via the lens of 35 years' worth of archived data on the world's largest social science data infrastructure, ICPSR, this study aims to reveal data characteristics (e.g., archived data themes and temporal distribution) that shape and represent the trend of social science data sharing and reuse. After a preliminary analysis on metadata of 10,362 studies and 159,616 associated citation records, an upward trend is found regarding the number of studies archived on ICPSR and their citation counts. We also report problems with metadata standards and the challenges of reusing data derived from these studies. Our results can be a cornerstone to investigate the roles of ICPSR as a research data infrastructure within the context of open science. [ABSTRACT FROM AUTHOR]

Retraction removes seriously flawed papers from the scientific literature. However, even papers retracted for scientific fraud continue to be cited and used as valid after their retraction. Retracted papers are inadequately identified on publisher pages and in scholarly databases, and scholars' personal libraries frequently contain retracted papers. To address this, we are developing a tool called ReTracker (https://github.com/nikolausn/ReTrackers) that automatically checks a user's Zotero library for retracted articles, and adds retraction status as a new metadata field directly in the library. In this paper, we present the current version of ReTracker, which automatically flags retracted articles from PubMed. We describe how we have iteratively improved ReTracker's matching performance through its initial two versions. Our tests show that the current version of ReTracker is able to flag retracted articles from PubMed with high precision and recall, and to distinguish retracted articles from articles about retraction. In its current state, ReTracker can actively and automatically bring retraction metadata into Zotero, and in future work we will test its usability with scholars. [ABSTRACT FROM AUTHOR]

This submission reports preliminary results of the first stage of a research project that seeks to identify the information organization methods and techniques currently offered in the language data archives and the gaps between the tools and techniques available and the needs of actual and potential users of language data archives. We conducted an exploratory content analysis of the websites of the language archives (LAs) hosted by the institutions located in the United States and several other countries. The focus of our exploratory content analysis is on the information organization, including documentation on metadata standards, displaying of individual metadata records and availability of harvesting sets of metadata records, provision of advanced discovery and navigation options powered by metadata such as availability of adaptive and personalized search or social tagging functionality. Here, we report our preliminary findings and describe our plan for Stage 2 of the. [ABSTRACT FROM AUTHOR]

Digitization offers an opportunity to expand access to unique historical materials in community archives but requires determining the copyright of items shared in digital collections. The copyright status of cultural heritage materials in community archives is difficult to evaluate because of limited documentation on authorship and creation date. This poster presents the findings from the study that analyzed the distribution of standardized rights statements assigned to the digitized objects in the Park County Local History Digital Archive. The process involved evaluating copyright status of published and unpublished materials and assigning standardized rights statements from RightsStatements.org. The types of applied rights statements and their frequency were analyzed using a Python script. The findings indicate the implementation of six different standardized rights statements and frequent use of the statements "Copyright not evaluated," "Copyright undetermined," and "In copyright—rights‐holder(s) unlocatable or unidentifiable." Relatively few items were identified as being in public domain. [ABSTRACT FROM AUTHOR]

This poster reports upon a case study of the linking mechanisms in the NCBI BioSample database and its immediate connections, examining the types of links, their functions, and implications according to the FAIR data principles. The study allowed the authors to conduct a more detailed analysis of one area of data management by focusing on one database's linking mechanisms, providing a glimpse into the role of linking mechanisms to support biomedical research and discovery and serving as a model for future studies. [ABSTRACT FROM AUTHOR]

Open government data (OGD) is a valuable resource for both policy transparency and government accountability. All levels of the United States government are working hard to promote open data and its portals. However, there is still a lack of studies on local‐level OGD portals in the United States, particularly on the quality of metadata adopted by these portals. By examining 200 US cities, a list of 112 local‐level portals is sampled and we investigate the current usages of open data platforms for building local‐level OGD portals. This study further investigates and discusses the adoption and potential issues of metadata on those OGD portals. Our result findings discuss the platform distributions among US local‐level OGD portals, and also highlight several critical issues associated with metadata on the portals. We anticipate the results will inspire further studies on identifying solutions to improve the metadata and enhance the usability of open government data portals. [ABSTRACT FROM AUTHOR]

Information community creates, maintains and shares authority data through large‐scale databases of standardized digital records that describe persons, institutions, places, events, and works, as well as relations between them. This submission presents some results of the content analysis study that explores the authority data change over time in response to change in standards. We analysed over 400 thousand of authority records that comply to the new standard, Resource Description and Access (RDA) and are available through the OCLC database. Records were obtained at two data collection points, with an interval of 22 months. Our analysis identified RDA‐based authority data elements that are widely applied and the ones that need more attention by record creators. Findings reveal a significant increase over time in the level of application of some data elements, including several of the Linked Data‐enabling elements. This study contributes to the understanding of metadata change and its relation to functionality of authority records and improved information access. Directions for future research are suggested. [ABSTRACT FROM AUTHOR]

Data discovery and re‐use remain challenging, particularly for interdisciplinary research, but visual representations of data may have potential to better support these tasks than text‐only metadata records. Our multi‐stage exploratory study used think‐aloud and intercept interviews to evaluate how scientists across multiple disciplines interpret the content and evaluate the credibility of climate indicators designed for general audiences as a way to understand the potential of visual representations for supporting interdisciplinary research. Climate indicators provided a convenient alternate representation for describing a data set, featuring a visualization of the data along with vernacular textual description. Our contributions include (i) findings on the preferences of scientists from multiple disciplines for establishing the credibility and assessing the content of data for re‐use, (ii) the unexpected observation that a minimal set of core metadata was considered adequate by researchers examining data from outside of their specialties, and (iii) discussion of the implications for the design of data discovery interfaces and future research to support data discovery and re‐use by increasingly diverse scientific data consumers. [ABSTRACT FROM AUTHOR]

This paper reports a usability and user experience research study of PBCore.org, a WGBH website supporting the PBCore metadata dictionary. Usability testing was conducted with 53 participants who worked in audiovisual processing and archiving. Significant differences in task performances and interaction experiences among user groups were found, most notably between broadcast and information professionals, archivists/librarians and other staff, and participants who had an LIS degree and those who did not. Qualitative observations afforded a deeper understanding of the difficulties that non‐LIS participants encountered. Recommendations for designing a more inclusive technical website include providing contextual and practical information on the homepage, delivering technical content visually and interactively, offering understandable definitions of terminology, and building a vibrant user community. Further research documenting users' knowledge gaps would be valuable. The paper concludes with a call for developing specific usability requirements for technical websites to create an inclusive and accessible user experience. [ABSTRACT FROM AUTHOR]

An accurate and timely assessment of mental health of individuals is an important building block toward healthy well‐functioning societies. Traditional methods for assessing mental health and wellbeing are surveys administered by health‐care professionals. Such surveys are labor intensive, costly, and typically intermittent. With the growth in mobile sensing, health informatics, and data science, this work argues a case for using mobile phone meta‐data and data analytics to automatically infer an individual's mental health. Specifically, based on a clinically utilized health measure as ground truth (MHI‐5) and ten‐week phone usage metadata corpus for 45 participants we report that automated machine learning algorithms utilizing phone based features can achieve reasonable accuracy (around 80%) at automatically classifying the level of mental health of an individual. Results could pave way for cheaper, automated, health assessments with timely escalations to mental health professionals and interventions when required. [ABSTRACT FROM AUTHOR]

Scholarly resources, including publications, software, data sets, and instruments, are created in an iterative and interrelated fashion. Managing the relationships that exist among and between such resources is a central requirement for information systems. Practically, however, many scholarly resources exist online as discrete entities, divorced from other resources to which they are intimately related. A robust system for linking scholarly resources in a broad and sustainable fashion will have to navigate a set of complex and interrelated requirements. This paper presents results and insights from three different projects that focused on supporting more robust linkages among scholarly resources. The discussion details key technical and institutional challenges looking forward and backward in time across what might be considered to be a "relationship life cycle": identifying, validating, characterizing, and preserving relationships. The goal of the paper is to help guide new research initiatives and operational services focused on integrating relationship information into the scholarly record. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper uses boundary work theory (Gieryn, 1983, among others) to analyze the differences in organizational participation in the creation and maintenance of the Data Documentation Initiative (DDI) standard. The Data Documentation Initiative is a global consensus standard created to describe social science research data. Specifically, the paper addresses how two key social science data archives (SSDA) - the Interuniversity Consortium of Political and Social Research (ICPSR) and the United Kingdom Data Archive (UKDA) - mobilized their differences as resources to create DDI. This paper describes the collaborative activities of the two organizations. It also analyzes how those differences in collaboration resulted in boundary or 'juncture' activities and the role those activities played in organizational maintenance. Our study compares how one organization, ICPSR, engaged in translating and aligning activities related to the development of the standard, while the other data archive, UKDA, engaged in decentering activities. The paper uses this case of standards work to reflect on the role of boundaries as resources for organizational resilience over the long-term. [ABSTRACT FROM AUTHOR]

ABSTRACT Despite efforts and attempts on preserving cultural heritages around the world, few studies have been conducted on metadata schema of murals and stone cave temples which are often high value heritages dating from ancient times. The literature is also scarce in user-centered evaluation of metadata schema of this kind. This study therefore aims to offer insights on developing and evaluating a drafted metadata schema for digitizing and preserving historic murals and stone cave temples. In-depth interviews were conducted with 15 scholars and professionals whose work was related to murals and stone cave temples. A coding framework was designed to analyze the interview transcripts. Initial findings show that users' seeking behaviors for cultural heritage information corroborated with their perceived importance of specific metadata elements. The coding schema developed in this study can serve as a framework for follow-up evaluations of metadata schemas of this kind, contributing to the ongoing development of cultural heritage metadata. [ABSTRACT FROM AUTHOR]

ABSTRACT Large cyberinfrastructure-enabled data repositories generate massive amounts of metadata, enabling big data analytics to leverage on the intersection of technological and methodological advances in data science for the quantitative study of science. This paper introduces a definition of big metadata in the context of scientific data repositories and discusses the challenges in big metadata analytics due to the messiness, lack of structures suitable for analytics and heterogeneity in such big metadata. A methodological framework is proposed, which contains conceptual and computational workflows intercepting through collaborative documentation. The workflow-based methodological framework promotes transparency and contributes to research reproducibility. The paper also describes the experience and lessons learned from a four-year big metadata project involving all aspects of the workflow-based methodologies. The methodological framework presented in this paper is a timely contribution to the field of scientometrics and the science of science and policy as the potential value of big metadata is drawing more attention from research and policy maker communities. [ABSTRACT FROM AUTHOR]

ABSTRACT Art images are characterized by affective properties that are rarely captured by current classification practices. We conducted a study to test three methods for developing affect descriptors for art images. The first method relied on affect tags derived from analysis of an image's subject matter and colors. The second method involved affect tags derived from analysis of a viewer's facial expressions of emotions associated with each image. The third method relied on affect tags assigned to an image by viewers. The strengths, limitations, and potential of each affect tagging method for art images are discussed. [ABSTRACT FROM AUTHOR]