This dissertation seeks to answer the research questions that arise when digital technologies are used to support distributed, artifact-centric, scientific collaboration. Scientific research is fundamentally collaborative in nature, with researchers often forming collaborations that involve colleagues from other institutions and often other countries. Modern research tools, such as high-resolution scientific instruments and sophisticated computational simulations, are providing scientists with digital data at an unprecedented rate. Thus, digital artifacts are the focus of many of today’s scientific collaborations. The understanding of scientific data is difficult because of the complexity of the scientific phenomena that the data represents. Such data is often complex in structure, dynamic in nature (e.g. changes over time), and poorly understood (little a-priori knowledge about the phenomena). These issues are exacerbated when such collaborations take place between scientists who are working together at a distance. This dissertation studies the impact of distance on artifact-centric scientific collaboration. It utilizes a multi-dimensional research approach, considering scientific collaboration at multiple points along the methodological (qualitative/quantitative research methods), cognitive (encoding/decoding), community (many/single research groups), group locality (collocated/distributed), and technological (prototype/production) dimensions. This research results in three primary contributions: 1) a new framework (CoGScience) for the study of distributed, artifact-centric collaboration; 2) new empirical evidence about the human communication channels scientists use to collaborate (utilizing both longitudinal/naturalistic and laboratory studies); and 3) a set of guidelines for the design and creation of more effective distributed, scientific collaboration tools.