diff --git a/.gitignore b/.gitignore
index b72dc7014..3c6151425 100644
--- a/.gitignore
+++ b/.gitignore
@@ -13,3 +13,9 @@ __pycache__
 *.pbxproj
 *.xcworkspacedata
 .ipynb_checkpoints
+
+# Auto-generated files by `R CMD check`
+tfio.Rcheck/
+tfio_*.tar.gz
+.Rproj.user
+
diff --git a/R-package/.Rbuildignore b/R-package/.Rbuildignore
index fc28d4b80..31becb436 100644
--- a/R-package/.Rbuildignore
+++ b/R-package/.Rbuildignore
@@ -1,3 +1,4 @@
 ^.*\.Rproj$
 ^\.Rproj\.user$
 ^man-roxygen/
+scripts
diff --git a/R-package/DESCRIPTION b/R-package/DESCRIPTION
index d6a78cb3b..e80872668 100644
--- a/R-package/DESCRIPTION
+++ b/R-package/DESCRIPTION
@@ -24,6 +24,7 @@ Imports:
     reticulate (>= 1.10), 
     tensorflow (>= 1.9),
     tfdatasets (>= 1.9),
+    forge,
     magrittr,
     rlang,
     tidyselect,
@@ -32,7 +33,5 @@ Roxygen: list(markdown = TRUE)
 RoxygenNote: 6.1.0
 Suggests:
     testthat,
-    knitr,
-    tfestimators,
-    keras
+    knitr
 VignetteBuilder: knitr
diff --git a/R-package/NAMESPACE b/R-package/NAMESPACE
index af3467069..256a822c8 100644
--- a/R-package/NAMESPACE
+++ b/R-package/NAMESPACE
@@ -1,9 +1,36 @@
 # Generated by roxygen2: do not edit by hand
 
 export("%>%")
+export(dataset_batch)
+export(dataset_cache)
+export(dataset_concatenate)
+export(dataset_filter)
+export(dataset_flat_map)
+export(dataset_interleave)
+export(dataset_map)
+export(dataset_map_and_batch)
+export(dataset_padded_batch)
+export(dataset_prefetch)
+export(dataset_prefetch_to_device)
+export(dataset_prepare)
+export(dataset_repeat)
+export(dataset_shard)
+export(dataset_shuffle)
+export(dataset_shuffle_and_repeat)
+export(dataset_skip)
+export(dataset_take)
+export(ignite_dataset)
 export(install_tensorflow)
+export(kafka_dataset)
+export(kinesis_dataset)
+export(next_batch)
+export(sequence_file_dataset)
 export(tf)
 export(tf_config)
+export(tf_version)
+export(until_out_of_range)
+export(with_dataset)
+import(forge)
 import(rlang)
 import(tfdatasets)
 import(tidyselect)
@@ -16,3 +43,25 @@ importFrom(reticulate,tuple)
 importFrom(tensorflow,install_tensorflow)
 importFrom(tensorflow,tf)
 importFrom(tensorflow,tf_config)
+importFrom(tensorflow,tf_version)
+importFrom(tfdatasets,dataset_batch)
+importFrom(tfdatasets,dataset_cache)
+importFrom(tfdatasets,dataset_concatenate)
+importFrom(tfdatasets,dataset_filter)
+importFrom(tfdatasets,dataset_flat_map)
+importFrom(tfdatasets,dataset_interleave)
+importFrom(tfdatasets,dataset_map)
+importFrom(tfdatasets,dataset_map_and_batch)
+importFrom(tfdatasets,dataset_padded_batch)
+importFrom(tfdatasets,dataset_prefetch)
+importFrom(tfdatasets,dataset_prefetch_to_device)
+importFrom(tfdatasets,dataset_prepare)
+importFrom(tfdatasets,dataset_repeat)
+importFrom(tfdatasets,dataset_shard)
+importFrom(tfdatasets,dataset_shuffle)
+importFrom(tfdatasets,dataset_shuffle_and_repeat)
+importFrom(tfdatasets,dataset_skip)
+importFrom(tfdatasets,dataset_take)
+importFrom(tfdatasets,next_batch)
+importFrom(tfdatasets,until_out_of_range)
+importFrom(tfdatasets,with_dataset)
diff --git a/R-package/R/dataset_utils.R b/R-package/R/dataset_utils.R
index c8418a83e..37bbef49c 100644
--- a/R-package/R/dataset_utils.R
+++ b/R-package/R/dataset_utils.R
@@ -1,15 +1,15 @@
 as_tf_dataset <- function (dataset) {
-  if (!is_dataset(dataset)) 
+  if (!is_dataset(dataset))
     stop("Provided dataset is not a TensorFlow Dataset")
-  if (!inherits(dataset, "tf_dataset")) 
+  if (!inherits(dataset, "tf_dataset"))
     class(dataset) <- c("tf_dataset", class(dataset))
   dataset
 }
 
 is_dataset <- function (x) {
-  inherits(x, "tensorflow.python.data.ops.dataset_ops.Dataset") || is_tfio_dataset(X)
+  inherits(x, "tensorflow.python.data.ops.dataset_ops.Dataset") || is_tfio_dataset(x)
 }
 
 is_tfio_dataset <- function(x) {
-  "tensorflow_io" %in% class(x)
+  grepl("tensorflow_io", class(x))
 }
diff --git a/R-package/R/hadoop_dataset.R b/R-package/R/hadoop_dataset.R
new file mode 100644
index 000000000..8386fbdbc
--- /dev/null
+++ b/R-package/R/hadoop_dataset.R
@@ -0,0 +1,14 @@
+#' Create a `SequenceFileDataset`.
+#'
+#' This function allows a user to read data from a hadoop sequence
+#' file. A sequence file consists of (key value) pairs sequentially. At
+#' the moment, `org.apache.hadoop.io.Text` is the only serialization type
+#' being supported, and there is no compression support.
+#'
+#' @param filenames A `tf.string` tensor containing one or more filenames.
+#'
+#' @export
+sequence_file_dataset <- function(filenames) {
+  dataset <- tfio_lib$hadoop$SequenceFileDataset(filenames = filenames)
+  as_tf_dataset(dataset)
+}
diff --git a/R-package/R/ignite_dataset.R b/R-package/R/ignite_dataset.R
new file mode 100644
index 000000000..3288c6fe8
--- /dev/null
+++ b/R-package/R/ignite_dataset.R
@@ -0,0 +1,56 @@
+#' Create a `IgniteDataset`.
+#'
+#' Apache Ignite is a memory-centric distributed database, caching, and
+#' processing platform for transactional, analytical, and streaming workloads,
+#' delivering in-memory speeds at petabyte scale. This contrib package
+#' contains an integration between Apache Ignite and TensorFlow. The
+#' integration is based on tf.data from TensorFlow side and Binary Client
+#' Protocol from Apache Ignite side. It allows to use Apache Ignite as a
+#' datasource for neural network training, inference and all other
+#' computations supported by TensorFlow. Ignite Dataset is based on Apache
+#' Ignite Binary Client Protocol.
+#'
+#' @param cache_name Cache name to be used as datasource.
+#' @param host Apache Ignite Thin Client host to be connected.
+#' @param port Apache Ignite Thin Client port to be connected.
+#' @param local Local flag that defines to query only local data.
+#' @param part Number of partitions to be queried.
+#' @param page_size Apache Ignite Thin Client page size.
+#' @param username Apache Ignite Thin Client authentication username.
+#' @param password Apache Ignite Thin Client authentication password.
+#' @param certfile File in PEM format containing the certificate as well as any
+#'   number of CA certificates needed to establish the certificate's
+#'   authenticity.
+#' @param keyfile File containing the private key (otherwise the private key
+#'   will be taken from certfile as well).
+#' @param cert_password Password to be used if the private key is encrypted and
+#'   a password is necessary.
+#'
+#' @export
+ignite_dataset <- function(
+  cache_name,
+  host = "localhost",
+  port = 10800,
+  local = FALSE,
+  part = -1,
+  page_size = 100,
+  username = NULL,
+  password = NULL,
+  certfile = NULL,
+  keyfile = NULL,
+  cert_password = NULL) {
+  dataset <- tfio_lib$ignite$IgniteDataset(
+    cache_name = cache_name,
+    host = host,
+    port = cast_scalar_integer(port),
+    local = cast_logical(local),
+    part = cast_scalar_integer(part),
+    page_size = cast_scalar_integer(page_size),
+    username = cast_nullable_string(username),
+    password = cast_nullable_string(password),
+    certfile = cast_nullable_string(certfile),
+    keyfile = cast_nullable_string(keyfile),
+    cert_password = cast_nullable_string(cert_password)
+  )
+  as_tf_dataset(dataset)
+}
diff --git a/R-package/R/kafka_dataset.R b/R-package/R/kafka_dataset.R
new file mode 100644
index 000000000..895a3f767
--- /dev/null
+++ b/R-package/R/kafka_dataset.R
@@ -0,0 +1,27 @@
+#' Creates a `KafkaDataset`.
+#'
+#' @param topics A `tf.string` tensor containing one or more subscriptions, in
+#'   the format of `[topic:partition:offset:length]`, by default length is -1
+#'   for unlimited.
+#' @param servers A list of bootstrap servers.
+#' @param group The consumer group id.
+#' @param eof If True, the kafka reader will stop on EOF.
+#' @param timeout The timeout value for the Kafka Consumer to wait (in
+#'   millisecond).
+#'
+#' @export
+kafka_dataset <- function(
+  topics,
+  servers = "localhost",
+  group = "",
+  eof = FALSE,
+  timeout = 1000) {
+  dataset <- tfio_lib$kafka$KafkaDataset(
+    topics = topics,
+    servers = servers,
+    group = group,
+    eof = cast_logical(eof),
+    timeout = cast_scalar_integer(timeout)
+  )
+  as_tf_dataset(dataset)
+}
diff --git a/R-package/R/kinesis_dataset.R b/R-package/R/kinesis_dataset.R
new file mode 100644
index 000000000..967bf585c
--- /dev/null
+++ b/R-package/R/kinesis_dataset.R
@@ -0,0 +1,28 @@
+#' Creates a `KinesisDataset`.
+#'
+#' Kinesis is a managed service provided by AWS for data streaming.
+#' This dataset reads messages from Kinesis with each message presented
+#' as a `tf.string`.
+#'
+#' @param stream A `tf.string` tensor containing the name of the stream.
+#' @param shard A `tf.string` tensor containing the id of the shard.
+#' @param read_indefinitely If `True`, the Kinesis dataset will keep retry again
+#'   on `EOF` after the `interval` period. If `False`, then the dataset will
+#'   stop on `EOF`. The default value is `True`.
+#' @param interval The interval for the Kinesis Client to wait before it tries
+#'   to get records again (in millisecond).
+#'
+#' @export
+kinesis_dataset <- function(
+  stream,
+  shard = "",
+  read_indefinitely = TRUE,
+  interval = 100000) {
+  dataset <- tfio_lib$kinesis$KinesisDataset(
+    stream = stream,
+    shard = shard,
+    read_indefinitely = cast_logical(read_indefinitely),
+    interval = cast_scalar_integer(interval)
+  )
+  as_tf_dataset(dataset)
+}
diff --git a/R-package/R/package.R b/R-package/R/package.R
index 8f93111f2..69583bde4 100644
--- a/R-package/R/package.R
+++ b/R-package/R/package.R
@@ -12,6 +12,7 @@ NULL
 #' @import tidyselect
 #' @import rlang
 #' @import tfdatasets
+#' @import forge
 NULL
 
 tfio_lib <- NULL
@@ -35,8 +36,7 @@ tfio_lib <- NULL
     }
   )
 
-  # TODO: This is commented out for now until we add the wrappers.
-  # tfio_lib <<- import("tensorflow_io", delay_load = delay_load)
+  tfio_lib <<- import("tensorflow_io", delay_load = delay_load)
 
 }
 
@@ -63,25 +63,3 @@ check_tensorflow_version <- function(displayed_warning) {
 .onDetach <- function(libpath) {
 
 }
-
-# Reusable function for registering a set of methods with S3 manually. The
-# methods argument is a list of character vectors, each of which has the form
-# c(package, genname, class).
-registerMethods <- function(methods) {
-  lapply(methods, function(method) {
-    pkg <- method[[1]]
-    generic <- method[[2]]
-    class <- method[[3]]
-    func <- get(paste(generic, class, sep = "."))
-    if (pkg %in% loadedNamespaces()) {
-      registerS3method(generic, class, func, envir = asNamespace(pkg))
-    }
-    setHook(
-      packageEvent(pkg, "onLoad"),
-      function(...) {
-        registerS3method(generic, class, func, envir = asNamespace(pkg))
-      }
-    )
-  })
-}
-
diff --git a/R-package/R/reexports.R b/R-package/R/reexports.R
index acd6b6096..4e5c8ff6c 100644
--- a/R-package/R/reexports.R
+++ b/R-package/R/reexports.R
@@ -21,3 +21,101 @@ tensorflow::install_tensorflow
 #' @importFrom tensorflow tf_config
 #' @export
 tensorflow::tf_config
+
+#' @importFrom tensorflow tf_version
+#' @export
+tensorflow::tf_version
+
+
+# Re-exports from tfdatasets dataset_iterators
+
+#' @importFrom tfdatasets next_batch
+#' @export
+tfdatasets::next_batch
+
+#' @importFrom tfdatasets with_dataset
+#' @export
+tfdatasets::with_dataset
+
+#' @importFrom tfdatasets until_out_of_range
+#' @export
+tfdatasets::until_out_of_range
+
+
+# Re-exports from tfdatasets dataset_methods
+
+#' @importFrom tfdatasets dataset_repeat
+#' @export
+tfdatasets::dataset_repeat
+
+#' @importFrom tfdatasets dataset_shuffle
+#' @export
+tfdatasets::dataset_shuffle
+
+#' @importFrom tfdatasets dataset_shuffle_and_repeat
+#' @export
+tfdatasets::dataset_shuffle_and_repeat
+
+#' @importFrom tfdatasets dataset_batch
+#' @export
+tfdatasets::dataset_batch
+
+#' @importFrom tfdatasets dataset_cache
+#' @export
+tfdatasets::dataset_cache
+
+#' @importFrom tfdatasets dataset_concatenate
+#' @export
+tfdatasets::dataset_concatenate
+
+#' @importFrom tfdatasets dataset_take
+#' @export
+tfdatasets::dataset_take
+
+#' @importFrom tfdatasets dataset_map
+#' @export
+tfdatasets::dataset_map
+
+#' @importFrom tfdatasets dataset_map_and_batch
+#' @export
+tfdatasets::dataset_map_and_batch
+
+#' @importFrom tfdatasets dataset_flat_map
+#' @export
+tfdatasets::dataset_flat_map
+
+#' @importFrom tfdatasets dataset_prefetch
+#' @export
+tfdatasets::dataset_prefetch
+
+#' @importFrom tfdatasets dataset_prefetch_to_device
+#' @export
+tfdatasets::dataset_prefetch_to_device
+
+#' @importFrom tfdatasets dataset_filter
+#' @export
+tfdatasets::dataset_filter
+
+#' @importFrom tfdatasets dataset_skip
+#' @export
+tfdatasets::dataset_skip
+
+#' @importFrom tfdatasets dataset_interleave
+#' @export
+tfdatasets::dataset_interleave
+
+#' @importFrom tfdatasets dataset_prefetch
+#' @export
+tfdatasets::dataset_prefetch
+
+#' @importFrom tfdatasets dataset_shard
+#' @export
+tfdatasets::dataset_shard
+
+#' @importFrom tfdatasets dataset_padded_batch
+#' @export
+tfdatasets::dataset_padded_batch
+
+#' @importFrom tfdatasets dataset_prepare
+#' @export
+tfdatasets::dataset_prepare
diff --git a/R-package/man/ignite_dataset.Rd b/R-package/man/ignite_dataset.Rd
new file mode 100644
index 000000000..5b6f4234b
--- /dev/null
+++ b/R-package/man/ignite_dataset.Rd
@@ -0,0 +1,49 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/ignite_dataset.R
+\name{ignite_dataset}
+\alias{ignite_dataset}
+\title{Create a \code{IgniteDataset}.}
+\usage{
+ignite_dataset(cache_name, host = "localhost", port = 10800,
+  local = FALSE, part = -1, page_size = 100, username = NULL,
+  password = NULL, certfile = NULL, keyfile = NULL,
+  cert_password = NULL)
+}
+\arguments{
+\item{cache_name}{Cache name to be used as datasource.}
+
+\item{host}{Apache Ignite Thin Client host to be connected.}
+
+\item{port}{Apache Ignite Thin Client port to be connected.}
+
+\item{local}{Local flag that defines to query only local data.}
+
+\item{part}{Number of partitions to be queried.}
+
+\item{page_size}{Apache Ignite Thin Client page size.}
+
+\item{username}{Apache Ignite Thin Client authentication username.}
+
+\item{password}{Apache Ignite Thin Client authentication password.}
+
+\item{certfile}{File in PEM format containing the certificate as well as any
+number of CA certificates needed to establish the certificate's
+authenticity.}
+
+\item{keyfile}{File containing the private key (otherwise the private key
+will be taken from certfile as well).}
+
+\item{cert_password}{Password to be used if the private key is encrypted and
+a password is necessary.}
+}
+\description{
+Apache Ignite is a memory-centric distributed database, caching, and
+processing platform for transactional, analytical, and streaming workloads,
+delivering in-memory speeds at petabyte scale. This contrib package
+contains an integration between Apache Ignite and TensorFlow. The
+integration is based on tf.data from TensorFlow side and Binary Client
+Protocol from Apache Ignite side. It allows to use Apache Ignite as a
+datasource for neural network training, inference and all other
+computations supported by TensorFlow. Ignite Dataset is based on Apache
+Ignite Binary Client Protocol.
+}
diff --git a/R-package/man/kafka_dataset.Rd b/R-package/man/kafka_dataset.Rd
new file mode 100644
index 000000000..8ff10110f
--- /dev/null
+++ b/R-package/man/kafka_dataset.Rd
@@ -0,0 +1,26 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/kafka_dataset.R
+\name{kafka_dataset}
+\alias{kafka_dataset}
+\title{Creates a \code{KafkaDataset}.}
+\usage{
+kafka_dataset(topics, servers = "localhost", group = "", eof = FALSE,
+  timeout = 1000)
+}
+\arguments{
+\item{topics}{A \code{tf.string} tensor containing one or more subscriptions, in
+the format of \code{[topic:partition:offset:length]}, by default length is -1
+for unlimited.}
+
+\item{servers}{A list of bootstrap servers.}
+
+\item{group}{The consumer group id.}
+
+\item{eof}{If True, the kafka reader will stop on EOF.}
+
+\item{timeout}{The timeout value for the Kafka Consumer to wait (in
+millisecond).}
+}
+\description{
+Creates a \code{KafkaDataset}.
+}
diff --git a/R-package/man/kinesis_dataset.Rd b/R-package/man/kinesis_dataset.Rd
new file mode 100644
index 000000000..986e2c119
--- /dev/null
+++ b/R-package/man/kinesis_dataset.Rd
@@ -0,0 +1,26 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/kinesis_dataset.R
+\name{kinesis_dataset}
+\alias{kinesis_dataset}
+\title{Creates a \code{KinesisDataset}.}
+\usage{
+kinesis_dataset(stream, shard = "", read_indefinitely = TRUE,
+  interval = 1e+05)
+}
+\arguments{
+\item{stream}{A \code{tf.string} tensor containing the name of the stream.}
+
+\item{shard}{A \code{tf.string} tensor containing the id of the shard.}
+
+\item{read_indefinitely}{If \code{True}, the Kinesis dataset will keep retry again
+on \code{EOF} after the \code{interval} period. If \code{False}, then the dataset will
+stop on \code{EOF}. The default value is \code{True}.}
+
+\item{interval}{The interval for the Kinesis Client to wait before it tries
+to get records again (in millisecond).}
+}
+\description{
+Kinesis is a managed service provided by AWS for data streaming.
+This dataset reads messages from Kinesis with each message presented
+as a \code{tf.string}.
+}
diff --git a/R-package/man/reexports.Rd b/R-package/man/reexports.Rd
index 8a1dd55e5..5f5f5725c 100644
--- a/R-package/man/reexports.Rd
+++ b/R-package/man/reexports.Rd
@@ -6,6 +6,28 @@
 \alias{tf}
 \alias{install_tensorflow}
 \alias{tf_config}
+\alias{tf_version}
+\alias{next_batch}
+\alias{with_dataset}
+\alias{until_out_of_range}
+\alias{dataset_repeat}
+\alias{dataset_shuffle}
+\alias{dataset_shuffle_and_repeat}
+\alias{dataset_batch}
+\alias{dataset_cache}
+\alias{dataset_concatenate}
+\alias{dataset_take}
+\alias{dataset_map}
+\alias{dataset_map_and_batch}
+\alias{dataset_flat_map}
+\alias{dataset_prefetch}
+\alias{dataset_prefetch_to_device}
+\alias{dataset_filter}
+\alias{dataset_skip}
+\alias{dataset_interleave}
+\alias{dataset_shard}
+\alias{dataset_padded_batch}
+\alias{dataset_prepare}
 \title{Objects exported from other packages}
 \keyword{internal}
 \description{
@@ -13,6 +35,8 @@ These objects are imported from other packages. Follow the links
 below to see their documentation.
 
 \describe{
-  \item{tensorflow}{\code{\link[tensorflow]{tf}}, \code{\link[tensorflow]{install_tensorflow}}, \code{\link[tensorflow]{tf_config}}}
+  \item{tensorflow}{\code{\link[tensorflow]{tf}}, \code{\link[tensorflow]{install_tensorflow}}, \code{\link[tensorflow]{tf_config}}, \code{\link[tensorflow]{tf_version}}}
+
+  \item{tfdatasets}{\code{\link[tfdatasets]{next_batch}}, \code{\link[tfdatasets]{with_dataset}}, \code{\link[tfdatasets]{until_out_of_range}}, \code{\link[tfdatasets]{dataset_repeat}}, \code{\link[tfdatasets]{dataset_shuffle}}, \code{\link[tfdatasets]{dataset_shuffle_and_repeat}}, \code{\link[tfdatasets]{dataset_batch}}, \code{\link[tfdatasets]{dataset_cache}}, \code{\link[tfdatasets]{dataset_concatenate}}, \code{\link[tfdatasets]{dataset_take}}, \code{\link[tfdatasets]{dataset_map}}, \code{\link[tfdatasets]{dataset_map_and_batch}}, \code{\link[tfdatasets]{dataset_flat_map}}, \code{\link[tfdatasets]{dataset_prefetch}}, \code{\link[tfdatasets]{dataset_prefetch_to_device}}, \code{\link[tfdatasets]{dataset_filter}}, \code{\link[tfdatasets]{dataset_skip}}, \code{\link[tfdatasets]{dataset_interleave}}, \code{\link[tfdatasets]{dataset_prefetch}}, \code{\link[tfdatasets]{dataset_shard}}, \code{\link[tfdatasets]{dataset_padded_batch}}, \code{\link[tfdatasets]{dataset_prepare}}}
 }}
 
diff --git a/R-package/man/sequence_file_dataset.Rd b/R-package/man/sequence_file_dataset.Rd
new file mode 100644
index 000000000..5da68ad3b
--- /dev/null
+++ b/R-package/man/sequence_file_dataset.Rd
@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/hadoop_dataset.R
+\name{sequence_file_dataset}
+\alias{sequence_file_dataset}
+\title{Create a \code{SequenceFileDataset}.}
+\usage{
+sequence_file_dataset(filenames)
+}
+\arguments{
+\item{filenames}{A \code{tf.string} tensor containing one or more filenames.}
+}
+\description{
+This function allows a user to read data from a hadoop sequence
+file. A sequence file consists of (key value) pairs sequentially. At
+the moment, \code{org.apache.hadoop.io.Text} is the only serialization type
+being supported, and there is no compression support.
+}
diff --git a/R-package/scripts/Dockerfile b/R-package/scripts/Dockerfile
new file mode 100644
index 000000000..f7f0385be
--- /dev/null
+++ b/R-package/scripts/Dockerfile
@@ -0,0 +1,18 @@
+FROM r-base
+COPY . .
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+      build-essential \
+      python-dev \
+      python-setuptools \
+      python-pip && \
+    rm -rf /var/lib/apt/lists/*
+
+# Dependencies
+RUN pip install tensorflow-io
+RUN Rscript -e 'install.packages(c("Rcpp", "reticulate", "knitr", "tensorflow", "tfdatasets", "forge", "tidyselect"))'
+
+# tfio package installation
+RUN R CMD build R-package/
+RUN R CMD INSTALL tfio_*.gz
diff --git a/R-package/tests/testthat/test-datasets-ops.R b/R-package/tests/testthat/test-datasets-ops.R
index f21796778..c3bdb0891 100644
--- a/R-package/tests/testthat/test-datasets-ops.R
+++ b/R-package/tests/testthat/test-datasets-ops.R
@@ -2,6 +2,7 @@ context("TensorFlow IO dataset ops")
 
 source("utils.R")
 
-test_succeeds("All TensorFlow IO dataset ops work", {
-  print("Placeholder for now")
+test_succeeds("sequence_file_dataset() works successfully", {
+  sequence_file_dataset("testdata/string.seq") %>%
+    dataset_repeat(2)
 })
diff --git a/R-package/tests/testthat/testdata/string.seq b/R-package/tests/testthat/testdata/string.seq
new file mode 100755
index 000000000..b7175338a
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@@ -78,6 +78,22 @@ $ # In docker
 $ R -e "devtools::test()"
 ```
 
+Alternatively, we also provided a reference Dockerfile [here](R-package/scripts/Dockerfile) for you
+so that you can use the R package directly for testing. You can build it via:
+```
+docker build -t tfio-r-dev -f R-package/scripts/Dockerfile .
+```
+
+Inside the container, you can start your R session, instantiate a `SequenceFileDataset`
+from an example [Hadoop SequenceFile](https://wiki.apache.org/hadoop/SequenceFile)
+[string.seq](R-package/tests/testthat/testdata/string.seq), and then use any [transformation functions](https://tensorflow.rstudio.com/tools/tfdatasets/articles/introduction.html#transformations) provided by [tfdatasets package](https://tensorflow.rstudio.com/tools/tfdatasets/) on the dataset like the following:
+
+```{R}
+library(tfio)
+dataset <- sequence_file_dataset("R-package/tests/testthat/testdata/string.seq") %>%
+    dataset_repeat(2)
+```
+
 ## License
 
 [Apache License 2.0](LICENSE)