Center for Knowledge Infrastructures

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).

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 question Christine L. Borgman addresses in her talk.

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 the norm for many fields. This talk will explore the stakes and stakeholders in research data, in interdisciplinary humanities research, and implications for policy and practice, drawing upon the presenter’s book, Big Data, Little Data, No Data: Scholarship in the Networked World (MIT Press, 2015), and subsequent research.

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,” “scarce data,” and “no data” are often the norm. The talk is illustrated with empirical examples from astronomy, environmental sciences, sensor networks, biomedicine, and other fields, drawing upon the presenter’s book, Big Data, Little Data, No Data: Scholarship in the Networked World (MIT Press, 2015), and subsequent research.

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.

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 subsequent research.