Recent ucla_knowledge_infrastructures items

From Data Creator to Data Reuser: Distance Matters

Fri, 12 Apr 2024 00:00:00 +0000

From Data Creator to Data Reuser: Distance Matters

New models of privacy for the university

Fri, 12 Apr 2024 00:00:00 +0000

New models of privacy for the university

Data Governance Task Force: Final report and recommendations

Fri, 12 Apr 2024 00:00:00 +0000

Data Governance Task Force: Final report and recommendations

Knowledge Infrastructures: The Invisible Foundation of Research Data (Slides and Video)

Fri, 13 Oct 2023 00:00:00 +0000

Knowledge Infrastructures: The Invisible Foundation of Research Data (Slides and Video)

Meaningful Data Metrics for Whom?

Thu, 9 Jun 2022 00:00:00 +0000

Make Data Count (MDC) is a scholarly change initiative, made up of researchers and open infrastructure experts, building and advocating for evidence-based open data metrics. Throughout MDC’s tenure, various areas key to the development of research data assessment metrics have been identified. Please join a Spring seminar and discussion series centered around priority work areas, adjacent initiatives to learn from, and steps that can be taken immediately to drive diverse research communities towards assessment and reward for open data.The third and last webinar in our series “BEGIN: metadata for meaningful metrics” will look at next steps to develop responsible and fair data metrics that can reflect the use and impact of research datasets and help elevate them to first-class scholarly outputs. We’ll focus on necessary metadata to construct metrics that take into account characteristics and contexts of open data across disciplines.

"Meaningful Data Metrics for Whom?" is the...

Research Data Infrastructure: A Problem of Governance

Thu, 9 Jun 2022 00:00:00 +0000

5a sesión del Seminario de Estudios sobre el Futuro. Con la participación de Christine Borgman, Directora del Center fo Knowledge Infrastructures de la Universidad de California, Los Angeles (UCLA).

Big Data, Little Data, or No Data? Scholarship, Stewardship, and Humanities Research

Wed, 19 May 2021 00:00:00 +0000

While the humanities have caught the “big data” wave, “little data” remains the norm in those many domains where evidence is scarce and labor-intensive to acquire. Until recently, data was considered part of the process of scholarship, essential but largely invisible. In the “big data” era, data have become valuable products to be captured, shared, reused, and stewarded for the long term. They also have become contentious intellectual property to be protected, especially in the humanities. Public policy leans toward open access to research data, but rarely provides the public investment necessary to sustain access. Data practices are local, varying from field to field, individual to individual, and country to country. As the number and variety of research partners expands, so do the difficulties of sharing, reusing, and sustaining access to data. Until the larger questions of knowledge infrastructures and stewardship are addressed by research communities, “no data” may become...

Big Data, Little Data, or No Data? A Social Science Perspective on Data Science [Presentation slides]

Wed, 19 May 2021 00:00:00 +0000

One person’s signal is another’s noise. Data exist in the eye of the beholder; they are neither products nor commodities. This talk is based on two decades of studying how scientists collect, make, manage, use, reuse, and lose their data. Scientific communities have built large knowledge infrastructures that encompass observatories, telescopes, sensor networks, data archives, technical standards, software tools, institutions, and scholarly societies. These infrastructures evolve over long periods of time; no one is really in charge. Data practices are local, varying from field to field, individual to individual, and country to country. Many of the essential practices necessary for knowledge and data production are invisible, resulting in fragile infrastructures that are difficult to maintain. The ability to share, reuse, and sustain access to scientific data depends on these fragile systems and relationships. Data scientists tend to focus on “big data,” whereas “little data,”...

On the Legitimacy of Knowledge Infrastructures

Tue, 16 Feb 2021 00:00:00 +0000

On the Legitimacy of Knowledge Infrastructures

Thought pieces for UCLA KI workshop

Tue, 16 Feb 2021 00:00:00 +0000

Thought pieces for UCLA KI workshop

Thought piece for the Second Knowledge Infrastructures Workshop (Feb 2019)

Tue, 16 Feb 2021 00:00:00 +0000

Thought piece for the Second Knowledge Infrastructures Workshop (Feb 2019)

Thought Pieces for UCLA Knowledge Infrastructure Workshop 2020

Tue, 16 Feb 2021 00:00:00 +0000

Thought Pieces for UCLA Knowledge Infrastructure Workshop 2020

What the Knowledge in Knowledge Infrastructures Does

Tue, 16 Feb 2021 00:00:00 +0000

What the Knowledge in Knowledge Infrastructures Does

2nd Knowledge Infrastructure Workshop – question responses

Tue, 16 Feb 2021 00:00:00 +0000

2nd Knowledge Infrastructure Workshop – question responses

Open online communities as a type of knowledge infrastructure under threat

Tue, 16 Feb 2021 00:00:00 +0000

Open online communities as a type of knowledge infrastructure under threat

Private Platforms, Metadata, and the Enclosure of Data Access: Urgent Issues for Knowledge Infrastructure Research

Tue, 16 Feb 2021 00:00:00 +0000

Private Platforms, Metadata, and the Enclosure of Data Access: Urgent Issues for Knowledge Infrastructure Research

Thought Piece for 2020 Knowledge Infrastructure Workshop

Tue, 16 Feb 2021 00:00:00 +0000

Thought Piece for 2020 Knowledge Infrastructure Workshop

Thought Piece on (Global) Knowledge Infrastructures

Tue, 16 Feb 2021 00:00:00 +0000

Thought Piece on (Global) Knowledge Infrastructures

Collaborative Qualitative Research at Scale:Reflections on 20 years of Acquiring Global Data and Making Data Global

Tue, 15 Dec 2020 00:00:00 +0000

A 5-year project to study scientific data uses in geography, starting in 1999, evolved into 20 years of research on data practices in sensor networks, environmental sciences, biology, seismology, undersea science, biomedicine, astronomy, and other fields. By emulating the ‘team science’ approaches of the scientists studied, the UCLA Center for Knowledge Infrastructures accumulated a comprehensive collection of qualitative data about how scientists generate, manage, use, and reuse data across domains. Building upon Paul N. Edwards’s model of ‘making global data’ – collecting signals via consistent methods, technologies, and policies – to ‘make data global’ – comparing and integrating those data, the research team has managed and exploited these data as a collaborative resource. This article reflects on the social, technical, organizational, economic, and policy challenges the team has encountered in creating new knowledge from data old and new. We reflect on continuity over generations...

Institutional Dimensions of Data Curation:Astronomy, Research Libraries, and MultipleApproaches to Curation

Sat, 14 Nov 2020 00:00:00 +0000

Institutional Dimensions of Data Curation:Astronomy, Research Libraries, and MultipleApproaches to Curation

Metadata Realities for Cyberinfrastructure: Data Authors as Metadata Creators

Fri, 30 Oct 2020 00:00:00 +0000

As digital data creation technologies become more prevalent, data and metadata management are necessary to make data available, usable, sharable, and storable. Researchers in many scientific settings, however, have little experience or expertise in data and metadata management. In this dissertation, I explore the everyday data and metadata management practices of researchers through a multi-sited ethnographic study of metadata creation by researchers in the Center for Embedded Networked Sensing (CENS). In studying metadata practices, I focused on the ways that researchers document, describe, annotate, organize, and manage their data, both for their own use and the use of researchers outside of their project. This study illustrates how researchers within CENS rarely create documentation that is not directly tied to their own use of their data, and correspondingly, they rarely share data with users from outside of their immediate projects. From these observations, I develop a metadata...

Structure and Evolution of Scientific Collaboration Networks in a Modern Research Collaboratory

Fri, 30 Oct 2020 00:00:00 +0000

This dissertation is a study of scientific collaboration at the Center for Embedded Networked Sensing (CENS), a modern, multi-disciplinary, distributed laboratory involved in sensor network research. By use of survey research and network analysis, this dissertation examines the collaborative ecology of CENS in terms of three networks of interaction: coauthorship of scholarly publications, communication activity on mailing lists, and interpersonal acquaintanceship. This study exposes the topology, structure, and evolution of these networks in relation with the disciplinary and institutional arrangements of CENS. Findings indicate that CENS collaboration networks have fluid, non-cliquish, small-world topologies, and are free of prestige-based mechanisms. Further analysis reveals that structural communities in the coauthorship and acquaintanceship networks overlap considerably. They also exhibit little disciplinary and institutional diversity locally, although CENS becomes more inter-disciplinary...

Building Values into the Design of Pervasive Mobile Technologies

Fri, 30 Oct 2020 00:00:00 +0000

Corporations, governments, and individuals can increasingly collect new forms of personal data using pervasive technologies such as mobile tablets and phones. These always-on, always-present devices carried by billions can capture and transmit users’ location, images, motion, and user input. Mobile technologies could become a platform to document community needs and advocate for civic change, to understand personal habits and routines, or to document health problems and manage chronic illness. Simultaneously, new forms of data collection software utilize techniques traditionally employed by tools of surveillance: granular data gathering, sophisticated modeling, and inferences about a personal behavior and attributes.

There is a shifting and permeable boundary between data collection for individual or social goals, and corporate or government surveillance. This boundary invokes social values in design: the features, principles, or ethics we collectively value in the design...

The Lives and After Lives of Data

Tue, 29 Sep 2020 00:00:00 +0000

The most elusive term in data science is 'data'. While often treated as objects to be computed upon, data is a theory-laden concept with a long history. Data exist within knowledge infrastructures that govern how they are created, managed, and interpreted. By comparing models of data life cycles, implicit assumptions about data become apparent. In linear models, data pass through stages from beginning to end of life, which suggest that data can be recreated as needed. Cyclical models, in which data flow in a virtuous circle of uses and reuses, are better suited for irreplaceable observational data that may retain value indefinitely. In astronomy, for example, observations from one generation of telescopes may become calibration and modeling data for the next generation, whether digital sky surveys or glass plates. The value and reusability of data can be enhanced through investments in knowledge infrastructures, especially digital curation and preservation. Determining what data...

Keynote: Big Data, Little Data, or No Data? Why Human Interaction with Data is a Hard Problem (slides)

Fri, 14 Aug 2020 00:00:00 +0000

Enthusiasm for big data is obscuring the complexity and diversity of data in scholarship and the challenges of human interaction and retrieval. Data practices are local, varying from field to field, individual to individual, and country to country. As the number and variety of research partners expands, so do the difficulties of sharing, reusing, and sustaining access to data. Information retrieval is hindered by the lack of agreement on what are “data.” Complexities of human interaction with data will be illustrated with empirical examples from environmental sciences, sensor networks, astronomy, biomedicine, and other fields. Unless larger questions of knowledge infrastructures and stewardship are addressed by research communities, “no data” often becomes the norm. Implications for policy and practice in the information sciences will be explored, drawing upon the presenter’s book, Big Data, Little Data, No Data: Scholarship in the Networked World (MIT Press, 2015), and...

What lies beneath?: Knowledge infrastructures in the subseafloor biosphere and beyond

Thu, 23 Jul 2020 00:00:00 +0000

We present preliminary findings from a three-year research project comprised of longitudinal qualitative case studies of data practices in four large, distributed, highly multidisciplinary scientific collaborations. This project follows a 2 ×× 2 research design: two of the collaborations are big science while two are little science, two have completed data collection activities while two are ramping up data collection. This paper is centered on one of these collaborations, a project bringing together scientists to study subseafloor microbial life. This collaboration is little science, characterized by small teams, using small amounts of data, to address specific questions. Our case study employs participant observation in a laboratory, interviews (n=49n=49 to date) with scientists in the collaboration, and document analysis. We present a data workflow that is typical for many of the scientists working in the observed laboratory. In particular, we show that, although...

Ship space to database: emerging infrastructures for studies of the deep subseafloor biosphere

Thu, 23 Jul 2020 00:00:00 +0000

Background

An increasing array of scientific fields face a “data deluge.” However, in many fields data are scarce, with implications for their epistemic status and ability to command funding. Consequently, they often attempt to develop infrastructure for data production, management, curation, and circulation. A component of a knowledge infrastructure may serve one or more scientific domains. Further, a single domain may rely upon multiple infrastructures simultaneously. Studying how domains negotiate building and accessing scarce infrastructural resources that they share with other domains will shed light on how knowledge infrastructures shape science.

Methods

We conducted an eighteen-month, qualitative study of scientists studying the deep subseafloor biosphere, focusing on the Center for Dark Energy Biosphere Investigations (C-DEBI) and the Integrated Ocean Drilling Program (IODP) and its successor, the International Ocean Discovery Program (IODP2). Our...

Privacy & Information Technology Syllabus, Fall 2017, UCLA

Thu, 9 Jul 2020 00:00:00 +0000

Privacy is a broad topic that covers many disciplines, stakeholders, and concerns. This course addresses the intersection of privacy and information technology, surveying a wide array of topics of concern for research and practice in the information fields. Among the topics covered are the history and changing contexts of privacy; privacy risks and harms; law, policies, and practices; privacy in searching for information, in reading, and in libraries; surveillance, networks, and privacy by design; information privacy of students; uses of learning analytics; privacy associated with government data, at all levels of government; information security, cyber risk; and how privacy and data are governed by universities. We will touch on relationships between privacy, security, and risk; on identification and re-identification of individuals; privacy-enhancing technologies; the Internet of Things; open access to data; drones; and other current issues in privacy and information technology.

Library Cultures of Data Curation: Adventures in Astronomy

Mon, 29 Jun 2020 00:00:00 +0000

University libraries are partnering with disciplinary data producers to provide long-term digital curation of research datasets. Managing dataset producer expectations and guiding future development of library services requires understanding the decisions libraries make about curatorial activities, why they make these decisions, and the effects on future data reuse. We present a study, comprising interviews (n=43) and ethnographic observation, of two university libraries who partnered with the Sloan Digital Sky Survey (SDSS) collaboration to curate a significant astronomy dataset. The two libraries made different choices of the materials to curate and associated services, which resulted in different reuse possibilities. Each of the libraries offered partial solutions to the SDSS leaders’ objectives. The libraries’ approaches to curation diverged due to contextual factors, notably the extant infrastructure at their disposal (including technical infrastructure, staff expertise,...

Our knowledge of knowledge infrastructures: Lessons learned and future directions

Fri, 5 Jun 2020 00:00:00 +0000

The Knowledge Infrastructures Workshop conducted at UCLA in February 2020, and funded by the Alfred P. Sloan Foundation, revisited the goals and findings of the 2012 workshop held at the University of Michigan. Thirty scholars, from a diverse array of disciplines and backgrounds, charted a course for the next decade of KI research. Such infrastructures are increasingly fragile, and often brittle, in the face of open data and open source, the demise of gatekeepers, and shifting public and private boundaries that redistribute power. Participants identified new methods and new opportunities for studying KI. Among the many scholarly products they proposed are publications, grant proposals, conference sessions, and workshops on the role of libraries in data services, the death and afterlives of KI, misinformation and disinformation in KI, KI in the Anthropocene, “N simplish rules” to grow and sustain KI, university capacities for KI, designing sustainable KI, and inclusion of underrepresented...

Knowledge infrastructure workshop thought piece

Fri, 17 Apr 2020 00:00:00 +0000

Knowledge infrastructure workshop thought piece

Whose text, whose mining, and to whose benefit?

Mon, 13 Apr 2020 00:00:00 +0000

Scholarly content has become more difficult to find as information retrieval has devolved from bespoke systems that exploit disciplinary ontologies to keyword search on generic search engines. In parallel, more scholarly content is available through open access mechanisms. These trends have failed to converge in ways that would facilitate text data mining, both for information retrieval and as a research method for the quantitative social sciences. Scholarly content has become open to read without becoming open to mine, due both to constraints by publishers and to lack of attention in scholarly communication. The quantity of available text has grown faster than has the quality. Academic dossier systems are among the means to acquire more quality data for mining. Universities, publishers, and private enterprise may be able to mine these data for strategic purposes, however. On the positive front, changes in copyright may allow more data mining. Privacy, intellectual freedom, and...

Someone to do the work: The skilled trades in the 21st Century

Fri, 10 Apr 2020 00:00:00 +0000

Someone to do the work: The skilled trades in the 21st Century

Space Telescope Science Institute as a knowledge infrastructure

Fri, 10 Apr 2020 00:00:00 +0000

Space Telescope Science Institute as a knowledge infrastructure

Of domains, their knowledge, and their infrastructure

Fri, 10 Apr 2020 00:00:00 +0000

Of domains, their knowledge, and their infrastructure

Knowledge infrastructures in past, present, and future tense

Fri, 10 Apr 2020 00:00:00 +0000

Knowledge infrastructures in past, present, and future tense

Knowledge infrastructures: A research agenda thought piece

Fri, 10 Apr 2020 00:00:00 +0000

Knowledge infrastructures: A research agenda thought piece

Collaborative Ethnography at Scale: Reflections on 20 years of data integration

Thu, 13 Feb 2020 00:00:00 +0000

A 5-year STS project in geography, starting in 1999, evolved into 20 years of data collection about scientific data practices in sensor networks, environmental sciences, biology, seismology, undersea science, biomedicine, astronomy, and other fields. By emulating the ‘team science’ approaches of the scientists studied, the UCLA Center for Knowledge Infrastructures accumulated a comprehensive collection of qualitative data about how scientists generate, manage, use, and reuse data across domains. Building upon Paul N. Edwards’s model of ‘making global data’ – collecting signals via consistent methods, technologies, and policies – to ‘make data global’ – comparing and integrating those data, the research team has managed and exploited these data as a collaborative resource. This article reflects on the social, technical, organizational, economic, and policy challenges the team has encountered in creating new knowledge from data old and new. We reflect on continuity over generations...

Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier

Tue, 11 Feb 2020 00:00:00 +0000

Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier

Data, infrastructure, and stewardship

Tue, 28 Jan 2020 00:00:00 +0000

Data, infrastructure, and stewardship

Data: Unstable in concept and context

Fri, 15 Nov 2019 00:00:00 +0000

Data: Unstable in concept and context

Maintaining FITS! Some lessons from (and perils of) successful long-term software maintenance

Mon, 4 Nov 2019 00:00:00 +0000

Maintaining FITS! Some lessons from (and perils of) successful long-term software maintenance

Thorny Problems in Data (-Intensive) Science

Mon, 7 Oct 2019 00:00:00 +0000

Thorny Problems in Data (-Intensive) Science

Whose Science? Whose Data? Whose Evidence?

Thu, 8 Aug 2019 00:00:00 +0000

Whose Science? Whose Data? Whose Evidence?

Jupyter notebooks as discovery mechanisms for open science: Citation practices in the astronomy community

Tue, 6 Aug 2019 00:00:00 +0000

Citing data and software is a means to give scholarly credit and to facilitate access to research objects. Citation principles encourage authors to provide full descriptions of objects, with stable links, in their papers. As Jupyter notebooks aggregate data, software, and other objects, they may facilitate or hinder citation, credit, and access to data and software. We report on a study of references to Jupyter notebooks in astronomy over a 5-year period (2014-2018). References increased rapidly, but fewer than half of the references led to Jupyter notebooks that could be located and opened. Jupyter notebooks appear better suited to supporting the research process than to providing access to research objects. We recommend that authors cite individual data and software objects, and that they stabilize any notebooks cited in publications. Publishers should increase the number of citations allowed in papers and employ descriptive metadata-rich citation styles that facilitate credit...

Why Data Sharing and Reuse in Biomedicine are Hard to Do

Tue, 18 Jun 2019 00:00:00 +0000

Why Data Sharing and Reuse in Biomedicine are Hard to Do

Labor Out of Place: On the Varieties and Valences of (In)visible Labor in Data-Intensive Science

Thu, 9 May 2019 00:00:00 +0000

Labor Out of Place: On the Varieties and Valences of (In)visible Labor in Data-Intensive Science

Once FITS, Always FITS? Astronomical Infrastructure in Transition

Sat, 26 Jan 2019 00:00:00 +0000

The FITS file format has become the de facto standard for sharing, analyzing, and archiving astronomy data over the last four decades. FITS was adopted by astronomers in the early 1980s to overcome incompatibilities between operating systems. On the back of FITS’ success, astronomical data became both backwards compatible and easily shareable. However, new advances in astronomical instrumentation, computational technologies, and analytic techniques have resulted in new data that do not work well within the traditional FITS format. Tensions have arisen between the desire to update the format to meet new analytic challenges and adherence to the original edict for FITS files to be backwards compatible. We examine three inflection points in the governance of FITS: a) initial development and success, b) widespread acceptance and governance by the working group, and c) the challenges to FITS in a new era of increasing data and computational complexity within astronomy.

The principles of tomorrow's university

Thu, 27 Dec 2018 00:00:00 +0000

In the 21st Century, research is increasingly data- and computation-driven. Researchers, funders, and the larger community today emphasize the traits of openness and reproducibility. In March 2017, 13 mostly early-career research leaders who are building their careers around these traits came together with ten university leaders (presidents, vice presidents, and vice provosts), representatives from four funding agencies, and eleven organizers and other stakeholders in an NIH- and NSF-funded one-day, invitation-only workshop titled "Imagining Tomorrow's University." Workshop attendees were charged with launching a new dialog around open research – the current status, opportunities for advancement, and challenges that limit sharing.The workshop examined how the internet-enabled research world has changed, and how universities need to change to adapt commensurately, aiming to understand how universities can and should make themselves competitive and attract the best students, staff,...

Research Data Alliance in the Science Data-Sharing Landscape

Wed, 5 Dec 2018 00:00:00 +0000

RDA-France Conference in Partnership with National Open Science Plan for France

Paris, 5 December 2018

The Research Data Alliance, in less than six years since its founding, has grown to more than 7000 members, has held 12 international plenary meetings, and convened a vast array of groups interested in data sharing and data-drivenresearch.During this period of time, the array of countries, communities, funding agencies, and individual scholars concerned about open access to data has continued to expand. Concurrently, awareness of the challenges of open science, open data, open access, and eResearch also has grown. Data sharing is an essential requirement for open science, but it is not an end in itself. Making data reusable, and keeping data available in scientifically useful forms for long periods of time, are much harder problems. As the RDA community grows and matures, it faces complex issues of data stewardship, trust, economics, infrastructure, standards,...

Big Science, Little Science, and Open Science: Sustainability, Stewardship, and Knowledge Infrastructures

Tue, 4 Dec 2018 00:00:00 +0000

Conference on the National Open Science Plan for France: From Strategy to Action

Paris, 4 December 2018

As France launches a national plan for open science that spans open access publishing, open access to data, and integration with international partnerships on scholarly sustainability, the country is taking a leap forward in developing new knowledge infrastructures – robust networks of people, artifacts, and institutions for producing, exchanging, and sustaining knowledge. Research data have become scholarly objects in their own right, to be released, shared, and reused. Publications and datasets are distinct genres that serve scholarship in complementary ways. Data sharing is a complex and labor-intensive process, and data reuse is even more so. Whereas data sharing policies presume that research data are useful to others and that others will reuse those data, neither outcome is assured. Concerns for data sharing and open access raise questions about what data...

The invisible knowledge infrastructure of astronomy: A sharper focus on blurry data

Mon, 26 Nov 2018 00:00:00 +0000

Age-old patterns of research and publication were disrupted as scholarship moved online. Astronomy now conducts research at scales of data collection that were unforeseeable in the days of glass plates – and yet those glass plates, famously stored at CfA, remain valuable as records of irreproducible observations. Keeping digital data “alive” at scale is proving to be a complex and expensive challenge. Astronomy has built a particularly robust network of people, artifacts, and institutions for producing, exchanging, and sustaining knowledge that links publications, telescopes, digital data archives, and other scientific resources – a knowledge infrastructure. My research fellowship at CfA for October 2018 is devoted to advancing a decade-long study of astronomy data practices to ask questions about the durability and fragility of these infrastructures and the invisible work required to sustain access to data, tools, instruments, publications, documentation, and other infrastructure...

PhD Dissertation - From Open Data to Knowledge Production: Biomedical Data Sharing and Unpredictable Data Reuses

Wed, 7 Nov 2018 00:00:00 +0000

Using a US consortium for data sharing as the primary field site, this three-year ethnographic research project examines the socio-technical, epistemic, and ethical challenges of making biomedical research data openly available and reusable. Public policy arguments for releasing scientific data for reuse by others include increasing trust in science and leveraging public investments in research. In most types of scientific research, data release occurs in parallel with associated publications, after peer-review. In the consortium studied for this project, datasets may also be released independently without an associated publication. Such research datasets are conceptualized as “hypothesis free” resources from which novel knowledge can be extracted indefinitely. Among the findings of this project are that biomedical researchers do not download and re-analyze “hypothesis free” research data from open repositories as a regular practice. Data reuse is a complex, delicate, and often...

PhD Thesis - From Open Data to Knowledge Production:Biomedical Data Sharing and Unpredictable Data Reuses

Tue, 6 Nov 2018 00:00:00 +0000

Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier

Wed, 17 Oct 2018 00:00:00 +0000

Berkman Klein Luncheon Series

Harvard University, Cambridge, MA, Wednesday October 10 2018

The growth in availability of digital data resources is changing university practice in more ways than most faculty, administrators, and students are aware. Researchers provide open access to their data as a condition for obtaining grant funding or publishing results in journals, leading to an explosion of available scholarly content. Universities have automated many aspects of teaching, instruction, student services, libraries, personnel management, building management, and finance, leading to a profusion of discrete data about the activities of individuals. Many of these data, both research and operational, fall outside privacy regulations such as HIPAA, FERPA, and PII. Universities see great value of these data for learning analytics, faculty evaluation, strategic decisions, and other sensitive matters. Commercial entities, governments, and private individuals also see...

Beyond Privacy: The Emerging Ethics of Data Reuse

Wed, 3 Oct 2018 00:00:00 +0000

The workshop will explore the meaning of “Informed Consent” and its implication for reusing human subject open data from and for biomedical research. Patients and volunteers donate their data in the context of research designs that are vetted and approved by ethics committees. When research data are released in open access – especially observational data - these can be reused to explore a number of new hypotheses. As we know from previous studies, biomedical data can be reused in many unpredictable ways – new research communities are formed around pre-existing data, and the free availability of research data increases innovation, knowledge integration, and reproducibility. At the same time, openness of data could also expose donors to surveillance and discriminatory research practices that not only have ethical implications, but also were never agreed upon by the donors at the moment of data collection. In this workshop, cases of both successful and controversial data reuse practices...

If Data Sharing is the Answer, What is the Question?

Wed, 3 Oct 2018 00:00:00 +0000

Data sharing has become normative policy enforced by governments, funding agencies, journals, and other stakeholders. Reasons for data sharing include leveraging investments in research, reducing the need to collect new data, addressing new research questions by reusing or combining extant data, and reproducing research, which would lead to greater accountability, transparency, and less fraud. Much of the scholarship on data practices attempts to understand the sociotechnical barriers to sharing, with goals to design infrastructures, policies, and cultural interventions that will overcome these barriers. Yet data sharing and reuse are common practice in only a few fields. Astronomy and genomics in the sciences, survey research in the social sciences, and archaeology in the humanities are the typical exemplars, and remain the exceptions rather than the rule. The lack of success of data sharing policies, despite accelerating enforcement over the last decade, indicates the need not...

The Data Conservancy: Science-driven Information Science

Fri, 28 Sep 2018 00:00:00 +0000

The Data Conservancy –which is a National Science Foundation funded Datanet project with a diverse array of partners – embraces a shared vision: data curation is not an end, but rather a means to collect, organize, validate, and preserve data to address grand research challenges that face society. Key to the data conservancy approach is information science research on the data practices of the science domains. Three teams are conducting social studies of individual science domains. Prof. Carole Palmer of the University of Illinois will report on their comparative studies of multiple biosciences domains. Prof. Christine Borgman of the University of California, Los Angeles, will report on their studies of astronomers. We are in the first year of the project, and will focus on our research questions, methods, and what we hope to learn from this 5-year project. http://www.ibi.hu-berlin.de/institut/veranstaltungen/bbk/bbk-material/abstracts/

Digital Libraries: Now here, or nowhere? (Keynote)

Fri, 28 Sep 2018 00:00:00 +0000

Digital libraries have matured over the 15+ years since the term was coined. Yet the term “digital libraries” has never come into general use outside of a select group of conferences and journals. Have digital libraries been subsumed under the rubric of cyberinfrastructure and eResearch? Have they fallen prey to the eternal debates between the (digital) library of the future and the future of (digital) libraries? Has a focus on technology obscured the larger questions of social practice that surround digital libraries? Or is digital library research at an inflection point, in a pivotal position to respond to the next wave of challenges for an information society?

Open data, grey data, and stewardship: Universities at the privacy frontier

Fri, 28 Sep 2018 00:00:00 +0000

As universities recognize the inherent value in the data they collect and hold, they encounter unforeseen challenges in stewarding those data in ways that balance accountability, transparency, and protection of privacy, academic freedom, and intellectual property. Two parallel developments in academic data collection are converging: (1) open access requirements, whereby researchers must provide access to their data as a condition of obtaining grant funding or publishing results in journals; and (2) the vast accumulation of “grey data” about individuals in their daily activities of research, teaching, learning, services, and administration. The boundaries between research and grey data are blurring, making it more difficult to assess the risks and responsibilities associated with any data collection. Many sets of data, both research and grey, fall outside privacy regulations such as HIPAA, FERPA, and PII. Universities are exploiting these data for research, learning analytics,...

Scholarship in the Digital Age: Blurring the Boundaries between the Sciences and the Humanities (Keynote)

Fri, 28 Sep 2018 00:00:00 +0000

As the digital humanities mature, their scholarship is taking on many characteristics of the sciences, becoming more data-intensive, information-intensive, distributed, multi-disciplinary, and collaborative. While few scholars in the humanities or arts would wish to be characterized as emulating scientists, they do envy the comparatively rich technical and resource infrastructure of the sciences. The interests of all scholars in the university align with respect to access to data, library resources, and computing infrastructure. However, the scholarly interests of the sciences and humanities diverge regarding research practices, sources of evidence, and degrees of control over those sources. This talk will explore the common and competing interests of disciplines for scholarship in the digital age.

The Digital Archive: The Data Deluge arrives in the Humanities

Fri, 28 Sep 2018 00:00:00 +0000

The data deluge has began to overwhelm the sciences, as instruments such as sensor networks and space telescopes are generating far more data than can possibly be inspected manually. Only digital tools can make sense of these vast volumes of data. As the humanities draw more heavily on digital archives, their scholarship is taking on many characteristics of the sciences, becoming more data-intensive, information-intensive, distributed, multi-disciplinary, and collaborative. However, the humanities typically lack the technical infrastructure available to the sciences. The scholarly interests of the sciences and humanities also diverge with respect to research practices, sources of evidence, and degrees of control over those sources. This talk will explore some of the challenges facing humanities scholars in mining digital archives.

The Digital Future is Now: What the Humanities can Learn from eScience

Fri, 28 Sep 2018 00:00:00 +0000

The Research Library of the Future: Less Selection, More Curation

Fri, 28 Sep 2018 00:00:00 +0000

Only a decade ago, this definition of a research library seemed adequate (Borgman, 2000, p.38): Librarians tend to take a broad view of the concept of a library. In general terms, they see libraries as organizations that select, collect, organize, conserve, preserve, and provide access to information on behalf of a community of users. Revisiting this definition today, libraries seem both broader and narrower in scope. The scope is narrower in that libraries are doing far less selecting and collecting of journals as they move from purchase to lease models. Research libraries rapidly are approaching the “e-only tipping point” (Johnson & Luther, 2007) for journals, and some predict that the e-only tipping point for books is not too far away (Connaway & Wicht, 2007; Sandler, Armstrong & Nardini, 2007). Libraries also are doing fewer of the organizing tasks for their core collections, as digital catalog records accompany digital books, and as more printed books arrive “shelf-ready”...

The Sensed vs Sensing in Embedded Networked Sensing Data and data sharing at an ENS research center